BCI · Neural Signal Decoding Researcher

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Qualified Candidates (213)

Adam Smoulder

high hireability

Postdoctoral Researcher@Boston University

Previously: Doctoral Student @ Carnegie Mellon University

Boston, US

Brain-Computer Interfaces72

Neural Signal Decoding70

Self-Supervised Neuro Learning18

Non-Invasive BCI8

EEG Foundation Models5

Strengths

NDT3 (2025) — generalist foundation model for intracortical motor decoding

PhD from CMU Chase/Batista lab — specialist in motor BCI signal decoding

Gaps

No EEG or non-invasive BCI work — entirely intracortical invasive recordings

…click to see all

Alessandro Marin Vargas

high hireability

Postdoctoral Scholar@Stanford University

Previously: PHD Graduate Student @ Ecole polytechnique fédérale de Lausanne

San Francisco, US

Brain-Computer Interfaces82

Neural Signal Decoding75

Self-Supervised Neuro Learning15

Non-Invasive BCI10

EEG Foundation Models5

Strengths

Postdoc at NPTL Stanford — top BCI lab (Frank Willett, speech BCI)

Cell 2024: task-driven models predict proprioceptive neural dynamics

Gaps

Work is invasive BCI (intracortical arrays) — not EEG/non-invasive

…click to see all

Bingchuan Liu

high hireability

Full Professor@Wuhan University of Science and Technology

Previously: Postdoctoral Researcher @ University of North Carolina at Charlotte

Wuhan, CN

Non-Invasive BCI92

Brain-Computer Interfaces88

Neural Signal Decoding85

EEG Foundation Models48

Self-Supervised Neuro Learning22

Strengths

EEG Conformer (806 cit, 2023) — high-impact transformer for EEG decoding

Decoding Natural Images from EEG, ICLR 2024 — top-venue EEG result

Gaps

No explicit EEG foundation model / large-scale self-supervised pretraining work

…click to see all

Chenggang Chen

high hireability

Research Associate@Johns Hopkins University

Previously: Postdoctoral Research Scientist @ Johns Hopkins University

Baltimore, US

Neural Signal Decoding78

Brain-Computer Interfaces75

Self-Supervised Neuro Learning32

Non-Invasive BCI12

EEG Foundation Models8

Strengths

ICLR 2025: Neural Manifold Regularization — motor BCI decoding

NeurIPS 2024: Neural Embeddings Rank — long-term latent dynamics decoding

Gaps

No EEG-specific work — likely invasive (primate electrophysiology) recordings

…click to see all

Elifnur Sunger

high hireability

Machine Learning Research Intern@Sanofi

Previously: AI Research Intern @ Signify

Boston, US

Non-Invasive BCI75

Brain-Computer Interfaces65

Neural Signal Decoding60

EEG Foundation Models5

Self-Supervised Neuro Learning5

Strengths

MarkovType (2024): POMDP-based EEG BCI typing — direct non-invasive BCI system

TMLR 2024 gesture paper: combination-homomorphic EMG encoder — neural decoding depth

Gaps

No EEG foundation model or large-scale pretraining work

…click to see all

Federico Nardi

high hireability

Teaching Assistant@Imperial College Business School

Previously: Graduate Teaching Assistant @ Imperial College London

London, GB

Neural Signal Decoding65

Non-Invasive BCI60

EEG Foundation Models55

Brain-Computer Interfaces55

Self-Supervised Neuro Learning50

Strengths

GNN pre-training for EEG representations in motor planning (2025 paper)

Second paper decodes motor learning neural patterns from EEG via GNN

Gaps

Pre-training is task-specific, not large-scale EEG foundation model

…click to see all

Gavin Mischler

high hireability

Graduate Research Assistant@Columbia University

Previously: Quant Trading Summer Associate @ Barclays

New York, US

Neural Signal Decoding75

Brain-Computer Interfaces65

Non-Invasive BCI55

Self-Supervised Neuro Learning25

EEG Foundation Models20

Strengths

Neuro2Semantic: language reconstruction from intracranial EEG (ICLR 2025)

SSVEP BCI keypad — end-to-end non-invasive BCI system

Gaps

No large-scale EEG foundation model or self-supervised pretraining work

…click to see all

Hossein Adeli

high hireability

Associate Research Scientist@Columbia University

Previously: Senior Postdoctoral Fellow @ Stony Brook University

New York, US

Neural Signal Decoding65

Self-Supervised Neuro Learning58

Non-Invasive BCI30

Brain-Computer Interfaces25

EEG Foundation Models15

Strengths

"Visual Decoding w/ Attention to Brain Representations" — direct decoding work (2025)

"NeuroAdapter" — masked self-supervised approach on brain representations (2025)

Gaps

Work fMRI-based visual neuroscience — no EEG/MEG or real-time BCI signals

…click to see all

Iris A.M. Huijben

high hireability

Postdoctoral researcher@Universiteit Maastricht

Previously: Research Intern @ Meta

Self-Supervised Neuro Learning82

Neural Signal Decoding72

Non-Invasive BCI45

EEG Foundation Models42

Brain-Computer Interfaces35

Strengths

SOM-CPC (ICML 2023): SSL + self-organizing maps on EEG time series

PhD thesis on discrete representation learning for sleep EEG (2024)

Gaps

Sleep-medicine application domain — not active BCI motor/speech control

…click to see all

Joseph Paillard

high hireability

Étudiant doctorant@Roche

Previously: Junior Scientist @ Roche

Basel, CH

Neural Signal Decoding40

Non-Invasive BCI35

EEG Foundation Models20

Self-Supervised Neuro Learning20

Brain-Computer Interfaces15

Strengths

EEG data augmentation paper (110 citations) — core EEG ML depth

GREEN architecture: novel lightweight EEG model (2025)

Gaps

PhD focus on explainability/variable importance, not BCI or decoding

…click to see all

Linh Le

high hireability

PhD student@University of Queensland

Previously: PhD student @ University of Queensland

Brisbane, AU

Neural Signal Decoding60

Self-Supervised Neuro Learning60

Non-Invasive BCI50

EEG Foundation Models30

Brain-Computer Interfaces30

Strengths

EEG-SSM (2024): SSM-based EEG decoding for dementia detection

EEG contrastive learning (2024): self-supervised EEG object perception

Gaps

Primary identity is NLP/NER — EEG is secondary, not core focus

…click to see all

Lucine L Oganesian

high hireability

Graduate Research Assistant@University of Southern California

Previously: Software Engineer @ Google

San Francisco, US

Self-Supervised Neuro Learning88

Neural Signal Decoding85

Brain-Computer Interfaces80

EEG Foundation Models60

Non-Invasive BCI20

Strengths

BaRISTA: self-supervised neurofoundation model for multiregional iEEG (NeurIPS 2025)

Masked latent reconstruction pretraining — methodology directly maps to EEG foundation models

Gaps

Work is iEEG (invasive intracranial) — no published EEG or non-invasive work found

…click to see all

Matteo Ferrante

high hireability

Post Doc@Università degli Studi di Roma "Tor Vergata"

Previously: PhD student @ Università di Roma Tor Vergata

Rome, IT

Neural Signal Decoding85

Brain-Computer Interfaces78

EEG Foundation Models75

Non-Invasive BCI72

Self-Supervised Neuro Learning72

Strengths

EEG/MEG/fMRI neural foundation model paper — aligns all modalities (2024)

Speech BCI paper with multitask learning (2025)

Gaps

Most decoding work uses fMRI, not EEG/MEG directly — less lightweight BCI

…click to see all

Muzhou Yu

high hireability

Self-Supervised Neuro Learning75

Neural Signal Decoding65

Brain-Computer Interfaces65

Non-Invasive BCI55

EEG Foundation Models10

Strengths

MindPainter (AAAI 2025): first brain-conditioned image painting via cross-modal SSL

MindCustomer (ICML 2025): visual brain signals → multi-context diffusion-based generation

Gaps

No evidence of EEG-specific foundation model work — papers use unspecified 'visual brain signals'

…click to see all

Osman Berke Guney

high hireability

PhD student in Electrical & Computer Engineering@Boston University

Previously: Graduate Teaching Assistant @ Boston University

Boston, US

Non-Invasive BCI85

Brain-Computer Interfaces85

Neural Signal Decoding70

Self-Supervised Neuro Learning18

EEG Foundation Models8

Strengths

Deep-SSVEP-BCI: DNN for SSVEP-based EEG BCI (129 citations, 2021)

Ensemble-of-DNNs: cross-subject transfer learning for BCI spellers (29 cits)

Gaps

Current research focus shifted to active feature acquisition / medical AI, not BCI

…click to see all

Peiliang Gong

high hireability

Postdoctoral Researcher@Nanyang Technological University

Previously: Visiting Researcher @ A*STAR

Singapore, SG

Brain-Computer Interfaces88

Non-Invasive BCI85

Neural Signal Decoding83

Self-Supervised Neuro Learning55

EEG Foundation Models48

Strengths

SNN + graph convolution for EEG-BCI (86 citations, 2023)

Cross-subject EEG cognitive workload + domain adaptation (41 citations)

Gaps

Foundation model work stated in headline but no published EEG FM papers found

…click to see all

Pierangelo Maria Rapa

high hireability

Dottorato@Università di Bologna

Previously: Visiting PHD Student @ University of California, Berkeley

Bologna, IT

Non-Invasive BCI62

Brain-Computer Interfaces55

EEG Foundation Models52

Neural Signal Decoding50

Self-Supervised Neuro Learning18

Strengths

PhysioWave: multi-modal physiological signal representation model covering EEG (NeurIPS 2025)

EEG-PPG drowsiness detection at edge — end-to-end non-invasive BCI system

Gaps

Primary focus is sEMG (muscle), not EEG brain signals

…click to see all

QIUHAO Zeng

high hireability

PhD Candidate@University of Western Ontario

Previously: Graduate Research Associate @ Nanyang Technological University

London, CA

Brain-Computer Interfaces85

Non-Invasive BCI80

Neural Signal Decoding80

Self-Supervised Neuro Learning30

EEG Foundation Models20

Strengths

TSception (304 citations): EEG temporal dynamics for emotion decoding

LGGNet (167 citations): graph-based neural representations for BCI

Gaps

No work on large EEG foundation/pretrained models

…click to see all

Richard Antonello

high hireability

Postdoc@Columbia University

Previously: PhD student @ University of Texas, Austin

New York, US

Neural Signal Decoding78

Brain-Computer Interfaces58

Non-Invasive BCI45

Self-Supervised Neuro Learning30

EEG Foundation Models25

Strengths

Neuro2Semantic: semantic language decoding from iEEG (2025)

Scaling laws for fMRI language encoding models (NeurIPS 2023)

Gaps

iEEG focus (invasive) — limited surface EEG / non-invasive BCI work

…click to see all

Sam Gijsen

high hireability

Postdoc Machine Learning in Neuroimaging@Charité - Universitätsmedizin Berlin

Previously: PhD Cognitive Computational Neuroscience @ Freie Universität Berlin

Berlin, DE

EEG Foundation Models96

Self-Supervised Neuro Learning95

Neural Signal Decoding72

Non-Invasive BCI55

Brain-Computer Interfaces42

Strengths

Brain-Semantoks (ICLR26) — self-distilled brain foundation model

ELM (ICML25) — EEG-language multimodal pretraining, label-efficient

Gaps

BCI closed-loop control not demonstrated — focused on representation learning

…click to see all

Thomas Strypsteen

high hireability

Postdoc@Katholieke Universiteit Leuven

Previously: PhD student @ Katholieke Universiteit Leuven

Leuven, BE

Brain-Computer Interfaces80

Non-Invasive BCI78

Neural Signal Decoding55

EEG Foundation Models10

Self-Supervised Neuro Learning5

Strengths

End-to-end EEG channel selection via Gumbel-softmax (J. Neural Eng. 2021)

Bandwidth-efficient distributed NN for neuro-sensor BCI (IEEE JBHI 2023)

Gaps

No EEG foundation model or large-scale pretraining work

…click to see all

Trung Le

high hireability

Visiting Researcher@Allen Institute

Previously: Research Scientist Intern @ Meta

Seattle, US

Neural Signal Decoding75

Brain-Computer Interfaces72

Self-Supervised Neuro Learning40

Non-Invasive BCI25

EEG Foundation Models15

Strengths

STNDT (NeurIPS 2022, 44 citations): spatiotemporal transformer for neural population

Brain-to-Text decoding with LLMs — end-to-end BCI decoding pipeline

Gaps

Core work is invasive (intracortical); limited EEG or non-invasive BCI publications

…click to see all

Vinam Arora

high hireability

Computer Science Ph.D. Student@University of Pennsylvania

Previously: chip-design engineer @ Texas Instruments

Philadelphia, US

Neural Signal Decoding82

Self-Supervised Neuro Learning82

Brain-Computer Interfaces55

Non-Invasive BCI52

EEG Foundation Models38

Strengths

Neural population decoding framework — 82 citations, NeurIPS 2023

CPEP: contrastive EMG pretraining for gesture generalization (NeurIPS 2025)

Gaps

Limited EEG-specific work — focus on electrophysiology (invasive) and EMG

…click to see all

Weibang Jiang

high hireability

PhD student@Shanghai Jiao Tong University

Previously: Intern @ Microsoft

Hangzhou, CN

EEG Foundation Models98

Non-Invasive BCI90

Brain-Computer Interfaces90

Self-Supervised Neuro Learning90

Neural Signal Decoding88

Strengths

LaBraM (ICLR 2024 spotlight): large pretrained EEG model for BCI

NeuroLM (ICLR 2025): 1.7B-param EEG-language foundation model

Gaps

No invasive/ECoG/intracortical work — purely non-invasive EEG

…click to see all

Xinxu Wei

high hireability

Ph.D. Student@Lehigh University

Previously: MS Student @ McGill University

Bethlehem, US

Self-Supervised Neuro Learning90

EEG Foundation Models85

Non-Invasive BCI35

Neural Signal Decoding25

Brain-Computer Interfaces15

Strengths

BrainGFM (ICLR 2026) — brain foundation model pre-training, any atlas/disorder

EEG_DisGCMAE (ICML 2025) — graph contrastive masked autoencoders for EEG

Gaps

No neural decoding work (intent/motor commands) — focuses on brain graph classification

…click to see all

Zesheng Ye

high hireability

Postdoctoral Research Fellow@University of Melbourne

Previously: PhD student @ University of New South Wales

Melbourne, AU

Self-Supervised Neuro Learning78

Neural Signal Decoding72

Non-Invasive BCI65

Brain-Computer Interfaces55

EEG Foundation Models30

Strengths

Self-supervised EEG visual retrieval (2024, 31 cit.) — SSL on brain signals

4 EEG/brain papers across 2022–2024 — sustained interest in BCI

Gaps

No EEG foundation model or large-scale neural pretraining work

…click to see all

Abdelhak Lemkhenter

medium hireability

Postdoc@Microsoft

Previously: PhD student @ University of Bern

Switzerland

Self-Supervised Neuro Learning65

Neural Signal Decoding50

Non-Invasive BCI38

Brain-Computer Interfaces22

EEG Foundation Models20

Strengths

Phase-swap SSL task for EEG bio-signals — directly relevant (GCPR 2020, 13 citations)

S2MAML: SSL meta-learning for sleep-stage EEG decoding (EMBC 2022)

Gaps

Current work (2023–2026) pivoted to world models and game AI — not BCI/EEG

…click to see all

Alan Du

medium hireability

Research Engineer@Meta

Previously: Tech Lead, Science Team @ Meta

New York, US

Non-Invasive BCI82

Brain-Computer Interfaces75

Neural Signal Decoding60

Self-Supervised Neuro Learning15

EEG Foundation Models5

Strengths

Non-invasive neuromotor interface paper (2025, 70 citations) — top BCI venue

emg2qwerty large-scale EMG dataset + baselines (ICML 2024)

Gaps

EMG-focused, not EEG/brain signals — limited brain imaging work

…click to see all

Alessio Burrello

medium hireability

Assistant Professor@Politecnico di Torino

Previously: Postdoc @ University of Bologna

Turin, IT

Neural Signal Decoding80

Non-Invasive BCI65

Brain-Computer Interfaces58

EEG Foundation Models40

Self-Supervised Neuro Learning18

Strengths

EEGformer (2022, 2024): compact transformer for wearable EEG seizure detection

BISeizuRe: BERT-inspired EEG pretraining for epilepsy monitoring

Gaps

Epilepsy monitoring focus — limited motor/speech/communication BCI work

…click to see all

Alexandre Gramfort

medium hireability

AI/ML Research Scientist@Meta

Previously: Senior Research Scientist @ Inria

Paris, FR

Non-Invasive BCI95

Neural Signal Decoding95

Brain-Computer Interfaces93

Self-Supervised Neuro Learning88

EEG Foundation Models85

Strengths

MNE-Python creator — gold standard MEG/EEG toolkit, used globally

EEG Foundation Challenge 2025 — cross-task/subject EEG decoding leadership

Gaps

No open-to-work signals; stable senior role at Meta

…click to see all

Amin Darabi

medium hireability

Support Researcher@Huawei

Previously: Graduate Student Researcher @ Mila

Montreal, CA

EEG Foundation Models85

Self-Supervised Neuro Learning65

Neural Signal Decoding55

Non-Invasive BCI50

Brain-Computer Interfaces45

Strengths

'General-Purpose Brain Foundation Models' — NeurIPS 2024 Workshop, EEG focus

Supervised by Irina Rish (Mila) — leading brain foundation model group

Gaps

Only 1 published paper; h-index null — very early-stage researcher

…click to see all

Andac Demir

medium hireability

Senior Expert Data Scientist@Novartis

Previously: Expert Data Scientist @ Novartis

Boston, US

Non-Invasive BCI65

Neural Signal Decoding60

Brain-Computer Interfaces60

Self-Supervised Neuro Learning15

EEG Foundation Models5

Strengths

EEG-GNN (EMBC 2021) — 129 citations, graph nets for EEG

EEG-GAT (EMBC 2022) — graph attention for EEG classification

Gaps

Fully pivoted to drug discovery since 2022 — no recent BCI work

…click to see all

Anders Gjølbye

medium hireability

PHD Fellow@DTU Compute

Previously: Co-Founder & Board Member @ Copenhagen MedTech

Copenhagen, DK

Self-Supervised Neuro Learning72

EEG Foundation Models62

Non-Invasive BCI38

Neural Signal Decoding35

Brain-Computer Interfaces35

Strengths

SPEED (2024): scalable EEG preprocessing for self-supervised learning

EEG transformer explainability via BENDR — foundation model familiarity

Gaps

No end-to-end BCI decoding pipeline — focuses on preprocessing/explainability

…click to see all

Arian Khorasani

medium hireability

Artificial Intelligence Researcher@Tech3Lab

Previously: Machine Learning Researcher @ Mila

Montreal, CA

Self-Supervised Neuro Learning80

EEG Foundation Models78

Non-Invasive BCI58

Neural Signal Decoding50

Brain-Computer Interfaces35

Strengths

'General-Purpose Brain Foundation Models' — NeurIPS 2024 workshop, EEG+fMRI

Tech3Lab: SSL for EEG + peripheral physiological signals, subject-transferable embeddings

Gaps

Workshop-only output; h-index = 0, no main-conference or journal papers

…click to see all

Arshia Afzal

medium hireability

Ph.D. student@EPFL

Lausanne, CH

Neural Signal Decoding70

Non-Invasive BCI55

Brain-Computer Interfaces50

EEG Foundation Models30

Self-Supervised Neuro Learning10

Strengths

REST (ICML 2024) — EEG seizure detection via efficient residual state transformer

MT-NAM (2025) — adaptive epileptic seizure detection model

Gaps

Pivoting to LLM efficiency (Cevher lab, Cartesia AI + Mistral AI internships)

…click to see all

Binghua Li

medium hireability

PhD student@Tokyo University of Agriculture and Technology

Tokyo, JP

Neural Signal Decoding45

Non-Invasive BCI42

Brain-Computer Interfaces38

EEG Foundation Models5

Self-Supervised Neuro Learning5

Strengths

Motor imagery signal classification — core non-invasive BCI task

Epileptic IEEG classification (CNN, 36 citations) — neural signal decoding

Gaps

No foundation model or self-supervised pretraining on EEG data

…click to see all

Bingzhao Zhu

medium hireability

PhD student@Cornell University

Brain-Computer Interfaces88

Neural Signal Decoding78

Non-Invasive BCI62

Self-Supervised Neuro Learning28

EEG Foundation Models15

Strengths

NeuralTree SoC: 256-channel neural classification + closed-loop neuromodulation (110 cit)

ECoG finger-movement decoding via Riemannian features + ML (2022, 38 cit)

Gaps

No EEG foundation model or large-scale self-supervised pretraining work

…click to see all

Binli Luo

medium hireability

Researcher@Central South University

Previously: Undergrad student @ Central South University

Neural Signal Decoding50

Brain-Computer Interfaces45

Non-Invasive BCI15

Self-Supervised Neuro Learning15

EEG Foundation Models5

Strengths

CRRL (2025): SoTA cross-day neural decoding on multiple BCI benchmarks

Co-authors with Yu_Qi and Yueming_Wang (ZJU BCI lab) — strong mentor signal

Gaps

Only one BCI paper, as 2nd author — not independently established in BCI

…click to see all

Ce Ju

medium hireability

Directrice des Relations Internationales@Inria

Previously: Adjointe Direction des Relations Internationales et des Partenariats Entreprises @ ENSTA Paris

Rocquencourt, FR

Brain-Computer Interfaces88

Neural Signal Decoding85

Non-Invasive BCI80

EEG Foundation Models18

Self-Supervised Neuro Learning12

Strengths

Tensor-CSPNet: geometric deep learning for motor imagery EEG (97 citations)

Federated Transfer Learning for EEG Classification — 202 citations, EMBC 2020

Gaps

No foundation model or self-supervised pretraining work on neural signals

…click to see all

Chaoqi Yang

medium hireability

Quantitative Researcher@Citadel Securities

Previously: Quantitative Research Intern @ Citadel Securities

Miami, US

EEG Foundation Models95

Self-Supervised Neuro Learning88

Neural Signal Decoding75

Non-Invasive BCI65

Brain-Computer Interfaces45

Strengths

BIOT (NeurIPS 2023) — large EEG pretraining framework, 172 citations, explicitly in brief

ContraWR: EEG self-supervised contrastive learning (JMIR AI'23)

Gaps

Career pivot to quant finance (Citadel) — may have intentionally left BCI field

…click to see all

Charan Santhirasegaran

medium hireability

MS student@Columbia University

Previously: Applied Science Intern @ Amazon

New York, US

Neural Signal Decoding55

Brain-Computer Interfaces50

Non-Invasive BCI20

EEG Foundation Models10

Self-Supervised Neuro Learning10

Strengths

sEEG speech decoding — core neural signal decoding expertise listed

MindEye2 (ICML 2024) — fMRI-to-image shared-subject pretraining

Gaps

No published sEEG or BCI paper indexed — expertise unverified by publication

…click to see all

Chenda Duan

medium hireability

PHD Student@UCLA

Previously: Research Assistant: Bolei Zhou's Group @ UCLA

Los Angeles, US

Self-Supervised Neuro Learning60

Neural Signal Decoding40

Non-Invasive BCI25

EEG Foundation Models20

Brain-Computer Interfaces20

Strengths

Omni-iEEG (ICLR 2026) — large-scale iEEG benchmark for epilepsy

Self-supervised HFO detection from EEG/iEEG data (2025, 5 citations)

Gaps

Primary focus is LLMs/VLMs, not BCI (own website statement)

…click to see all

Chenlin Zhou

medium hireability

PhD student@Peking University & Pengcheng Laboratory

Previously: Engineer @ Peng Cheng Laboratory

Beijing, CN

Neural Signal Decoding52

Non-Invasive BCI48

Brain-Computer Interfaces42

EEG Foundation Models5

Self-Supervised Neuro Learning5

Strengths

S²M-Former: EEG auditory attention decoding, NeurIPS 2025, SOTA on 3 benchmarks

SNN brings 5.8× energy efficiency over ANN methods on EEG decoding tasks

Gaps

BCI limited to one paper — core identity is SNN architect, not BCI specialist

…click to see all

Chenyu Liu

medium hireability

Non-Invasive BCI62

Brain-Computer Interfaces60

Neural Signal Decoding55

Self-Supervised Neuro Learning10

EEG Foundation Models8

Strengths

VBH-GNN (ICLR 2024): EEG cross-subject emotion recognition — top venue

BiMamba-TTA (NeurIPS 2025): multimodal physiological signal modeling

Gaps

Affective BCI only — no motor or speech decoding work

…click to see all

Christina Sartzetaki

medium hireability

PhD Candidate@University of Amsterdam

Previously: Machine Learning Engineer @ DeepLab

Amsterdam, NL

Neural Signal Decoding58

Brain-Computer Interfaces52

Non-Invasive BCI48

EEG Foundation Models45

Self-Supervised Neuro Learning28

Strengths

EEG fine-tuning paper (IEEE 2023) — cross-dataset EEG model generalization

ICLR 2025: 100 neural nets vs. video EEG — hands-on EEG alignment work

Gaps

Primarily representational alignment, not end-to-end BCI control or decoding for motor/speech

…click to see all

Christos Chatzichristos

medium hireability

Scientific Advisor@AINIGMA Technologies

Previously: Postdoctoral Researcher @ Janssen

Leuven, BE

Neural Signal Decoding65

Non-Invasive BCI60

EEG Foundation Models40

Brain-Computer Interfaces40

Self-Supervised Neuro Learning30

Strengths

EEG/fMRI fusion via tensor decompositions — core research identity

ECG Foundation Model papers (2025) — biosignal FM methodology

Gaps

No direct EEG foundation model paper — ECG FM, not brain signals

…click to see all

David M. Zoltowski

medium hireability

Postdoctoral Scholar in Statistics@Stanford University

Previously: PhD Student @ Princeton University

San Francisco, US

Neural Signal Decoding70

Brain-Computer Interfaces60

Non-Invasive BCI35

EEG Foundation Models25

Self-Supervised Neuro Learning20

Strengths

Brain-to-Text Benchmark'24 — evaluates neural-to-text decoding pipelines

Neural Latents Benchmark'21 (121 citations) — neural population activity modeling

Gaps

Primary focus probabilistic/Bayesian methods — limited end-to-end BCI engineering

…click to see all

Deeksha M Shama

medium hireability

Graduate Research Assistant@Johns Hopkins University

Previously: Research Intern - Brain Computer Interfaces @ Microsoft

Boston, US

EEG Foundation Models75

Neural Signal Decoding75

Non-Invasive BCI72

Brain-Computer Interfaces65

Self-Supervised Neuro Learning20

Strengths

Brain Foundation Models for BCIs paper accepted ICASSP 2026 (MS Research)

DeepSOZ: EEG-based temporal/spatial seizure onset localization

Gaps

No explicit self-supervised/contrastive pretraining on neural signals

…click to see all

Denis-Alexander Engemann

medium hireability

Biomarker & Experimental Medicine Leader@Roche

Previously: Researcher @ Inria

Basel, CH

Self-Supervised Neuro Learning93

Neural Signal Decoding92

Non-Invasive BCI83

EEG Foundation Models78

Brain-Computer Interfaces70

Strengths

MNE-Python co-creator — most-cited EEG/MEG open-source framework (4208 cites)

'Uncovering clinical EEG with SSL' (2021, 300 cites) — landmark self-supervised work

Gaps

BCI focus is biomarker/monitoring, not closed-loop control systems

…click to see all

Dexuan He

medium hireability

Postgraduate student@Shanghai Jiao Tong University

Shanghai, CN

Brain-Computer Interfaces40

Non-Invasive BCI35

Neural Signal Decoding25

EEG Foundation Models5

Self-Supervised Neuro Learning5

Strengths

ManiBCI (NeurIPS 2024): frequency-domain EEG backdoor shows deep signal understanding

Professor X (ICLR 2025): cross-subject robust attack on EEG BCI classifiers

Gaps

BCI security focus — no evidence of building or improving BCI decoding systems

…click to see all

Diana C Dima

medium hireability

Postdoc@Johns Hopkins University

Baltimore, US

Neural Signal Decoding45

EEG Foundation Models22

Self-Supervised Neuro Learning20

Non-Invasive BCI18

Brain-Computer Interfaces10

Strengths

Time-resolved MEG decoding pipeline — RSA + cross-decoding on visual cortex (2021)

Transformer-brain alignment paper (2024) — closest work to brain foundation models

Gaps

No BCI system design or intent decoding (motor/speech/imagined) work found

…click to see all

Dongdong Zhou

medium hireability

Postdoc@Dalian University of Technology

Previously: PhD student @ University of Jyväskylä

Neural Signal Decoding58

Non-Invasive BCI20

Brain-Computer Interfaces12

Self-Supervised Neuro Learning8

EEG Foundation Models5

Strengths

SingleChannelNet: 60-citation single-channel EEG sleep staging model (2024)

EEG emotion recognition with stable pattern detection (2025, 23 cites)

Gaps

No BCI systems — passive EEG monitoring only, no closed-loop control

…click to see all

Dong Nie

medium hireability

Staff Engineer@Meta

Previously: Head of Perception @ Alibaba

San Francisco, US

Neural Signal Decoding72

Self-Supervised Neuro Learning52

Brain-Computer Interfaces38

Non-Invasive BCI18

EEG Foundation Models12

Strengths

fMRI-to-Text (NeurIPS 2025 spotlight) — direct brain decoding to language

BrainX: universal brain decoding framework with disentangled neuro-geometric representations

Gaps

All brain decoding work is fMRI-based — no EEG, MEG, or fNIRS work found

…click to see all

Dulhan Jayalath

medium hireability

PhD Student@University of Oxford

Previously: Research Scientist Intern @ Meta

Oxford, GB

Non-Invasive BCI90

Neural Signal Decoding90

Brain-Computer Interfaces90

Self-Supervised Neuro Learning90

EEG Foundation Models70

Strengths

"Brain's Bitter Lesson" — ICML 2025, self-supervised MEG speech decoding at scale

"LibriBrain" — 50+ hours MEG corpus enabling scalable speech decoding (2025)

Gaps

MEG-focused — limited published EEG-specific work

…click to see all

Ebrahim Feghhi

medium hireability

PhD student@University of California, Los Angeles

Previously: Undergrad student @ University of California, Los Angeles

Los Angeles, US

Neural Signal Decoding80

Brain-Computer Interfaces80

Non-Invasive BCI65

Self-Supervised Neuro Learning30

EEG Foundation Models8

Strengths

NeurIPS 2025 first-author: neural speech decoding via time-masked transformers

SplashNet: 31% zero-shot gain on surface EMG typing (non-invasive BCI)

Gaps

No EEG-specific work; focuses on neural population signals + surface EMG

…click to see all

Eray Erturk

medium hireability

PhD student@USC

Previously: Sensing Data & Interaction Software Intern @ Apple

Los Angeles, US

Neural Signal Decoding92

Brain-Computer Interfaces80

EEG Foundation Models55

Non-Invasive BCI50

Self-Supervised Neuro Learning45

Strengths

ICLR 2025: real-time neural decoding of nonlinear latent factors

NeurIPS 2025: spike-LFP cross-modal distillation — multi-scale neural signals

Gaps

EEG/non-invasive BCI not primary focus — work centers on LFP/spike multi-scale signals

…click to see all

Fabio Rizzoglio

medium hireability

Postdoctoral Researcher@Northwestern University

Previously: Visiting Research Scholar @ Northwestern University

Chicago, US

Brain-Computer Interfaces85

Neural Signal Decoding80

Self-Supervised Neuro Learning45

Non-Invasive BCI15

EEG Foundation Models5

Strengths

Unsupervised piecewise linear decoding for multi-task BCI (J Neural Eng 2025)

FALCON benchmark — neural decoding generalization across sessions/subjects

Gaps

All work is intracortical/invasive — no EEG or non-invasive BCI publications

…click to see all

Francesco S. Carzaniga

medium hireability

Researcher@IBM

Previously: PhD student @ Universität Bern

Zurich, CH

EEG Foundation Models88

Neural Signal Decoding82

Self-Supervised Neuro Learning78

Brain-Computer Interfaces75

Non-Invasive BCI65

Strengths

BrainCodec (ICLR 2025): iEEG→EEG self-supervised compressor enabling non-invasive transfer

MVPFormer (NeurIPS 2025): iEEG foundation model with novel MVPA attention mechanism

Gaps

Primary focus is iEEG (invasive); EEG/non-invasive is secondary transfer target

…click to see all

Furkan Ozcelik

medium hireability

CerCo, University of Toulouse III Paul Sabatier

Previously: PhD student @ Université Paul Sabatier (Toulouse III)

Toulouse, FR

Neural Signal Decoding85

Non-Invasive BCI60

Brain-Computer Interfaces60

Self-Supervised Neuro Learning30

EEG Foundation Models25

Strengths

Brain-Diffuser: fMRI→image via latent diffusion (176 citations)

Brain Captioning: multimodal fMRI→text+image decoding

Gaps

Work is fMRI-based — limited EEG or MEG neural decoding

…click to see all

Galen Pogoncheff

medium hireability

PhD Student@University of California, Santa Barbara

Santa Barbara, US

Non-Invasive BCI65

Brain-Computer Interfaces62

Neural Signal Decoding60

Self-Supervised Neuro Learning32

EEG Foundation Models8

Strengths

Earable ML Lead 3 yrs — EEG wearable decoding motor intent & cognitive state

Earable pilot study: facial muscle/eye movement EEG classification (2022)

Gaps

No published work on EEG foundation models or large-scale neural pretraining

…click to see all

Gary H Blumenthal

medium hireability

Postdoctoral Associate@University of Pittsburgh

Previously: PhD student @ Drexel University

Pittsburgh, US

Neural Signal Decoding72

Brain-Computer Interfaces70

Self-Supervised Neuro Learning50

EEG Foundation Models18

Non-Invasive BCI8

Strengths

NDT3 (2025): 350M-param foundation model for intracortical motor decoding

Pretrained on 2000 hrs neural data from 30+ subjects across 10 labs

Gaps

All BCI work is invasive intracortical — no EEG, fNIRS, or MEG work found

…click to see all

Geethan Karunaratne

medium hireability

Researcher@IBM

Previously: Postdoctoral Researcher @ IBM

Zurich, CH

Brain-Computer Interfaces45

Non-Invasive BCI40

Neural Signal Decoding40

EEG Foundation Models5

Self-Supervised Neuro Learning5

Strengths

Energy Efficient In-memory HDC Encoding for Spatio-temporal Signal Processing — direct EEG/EMG work

In-memory hyperdimensional computing (Nature Electronics 2019, 355 cites) — BCI-applicable HDC

Gaps

Primary expertise is hardware acceleration + HDC, not end-to-end BCI systems

…click to see all

Georgios Zoumpourlis

medium hireability

Senior Machine Learning Engineer@ORB Innovations

Previously: Machine Learning Engineer @ Cogitat

London, GB

Brain-Computer Interfaces87

Non-Invasive BCI82

Neural Signal Decoding80

EEG Foundation Models22

Self-Supervised Neuro Learning15

Strengths

CovMix + Ensemble-MI papers — motor imagery EEG decoding (2022)

Causal brainwave modeling for BCI paper (2024)

Gaps

No large-scale EEG foundation model or self-supervised pretraining work

…click to see all

Hafez Ghaemi

medium hireability

Doctoral Researcher@Mila

Previously: Graduate Teaching Assistant @ Université de Montréal

Montreal, CA

Brain-Computer Interfaces85

Non-Invasive BCI80

Neural Signal Decoding80

Self-Supervised Neuro Learning28

EEG Foundation Models15

Strengths

Motor imagery EEG systematic review — 24 citations, 2024

CCSPNet: subject-independent motor imagery framework (real-world BCI, 2023)

Gaps

No EEG foundation model or large-scale pretraining work

…click to see all

Haishuai Wang

medium hireability

Visiting Assistant Professor@Harvard University

Previously: Research Fellow @ Harvard University

Boston, US

Neural Signal Decoding65

EEG Foundation Models45

Non-Invasive BCI35

Brain-Computer Interfaces25

Self-Supervised Neuro Learning20

Strengths

3 direct EEG papers: emotion recognition + seizure detection (2022-2024)

Physiological signal foundation model adaptation paper (2025)

Gaps

EEG work on emotion/seizure — not BCI control or motor/speech decoding

…click to see all

Haiteng Jiang

medium hireability

Research Professor@Zhejiang University

Previously: Postdoctoral Researcher @ Carnegie Mellon University

Hangzhou, CN

EEG Foundation Models92

Neural Signal Decoding82

Self-Supervised Neuro Learning78

Non-Invasive BCI75

Brain-Computer Interfaces72

Strengths

CBraMod (ICLR 2025) — criss-cross EEG foundation model, 52 citations

BrainUICL (ICLR 2025) — unsupervised individual continual EEG learning

Gaps

China-based PI with PhD students — relocation/recruitment complex

…click to see all

Hanqi Wang

medium hireability

PhD Student, Fudan University

Self-Supervised Neuro Learning75

Neural Signal Decoding65

Non-Invasive BCI60

Brain-Computer Interfaces60

EEG Foundation Models25

Strengths

Cascaded SSL for EEG — self-supervised cross-subject emotion recognition (2024)

MMOC 2025 — contrastive+reconstruction routing for EEG emotion decoding

Gaps

Emotion recognition only — no motor control, speech decoding, or intent BCI

…click to see all

Hanwen Shi

medium hireability

PhD student@Shanghai Jiaotong University

Previously: Undergrad student @ Shanghai Jiaotong University

Shanghai, CN

Neural Signal Decoding82

Non-Invasive BCI78

Brain-Computer Interfaces75

EEG Foundation Models45

Self-Supervised Neuro Learning20

Strengths

EEG2Video NeurIPS 2024 — decodes visual perception from EEG end-to-end

BCMI Lab SJTU — premier Chinese BCI research group (Bao-liang Lu)

Gaps

No self-supervised or contrastive pretraining work evident

…click to see all

Hao Fang

medium hireability

Postdoctoral Scholar@University of Washington

Previously: Postdoctoral Scholar @ University of Central Florida

Seattle, US

Brain-Computer Interfaces82

Neural Signal Decoding78

Non-Invasive BCI52

EEG Foundation Models22

Self-Supervised Neuro Learning18

Strengths

SPINT (2025): iBCI motor decoder generalizing across sessions via permutation-invariant transformer

EEG meta-learning paper (2025): inter-subject emotion recognition from EEG

Gaps

No explicit EEG foundation model or self-supervised pretraining work

…click to see all

Hongwei Mao

medium hireability

Postdoc@University of Pittsburgh

Previously: Faculty Associate @ Arizona State University

Tempe, US

Neural Signal Decoding70

Brain-Computer Interfaces70

Self-Supervised Neuro Learning40

EEG Foundation Models15

Non-Invasive BCI10

Strengths

NDT3 (2025): foundation model for neural data, 2000h pretraining across 10 labs

Intracortical motor decoding — direct BCI application

Gaps

Invasive BCI focus (intracortical spikes) — no EEG or non-invasive work found

…click to see all

Hua Xie

medium hireability

Research Faculty@Children's National Hospital

Previously: Postdoctoral Associate @ University of Maryland

EEG Foundation Models80

Self-Supervised Neuro Learning80

Neural Signal Decoding65

Non-Invasive BCI55

Brain-Computer Interfaces35

Strengths

Graph Contrastive MAE for EEG distillation paper (2025, OpenReview)

Multi-modal self-supervised fMRI+EEG fusion (Neural Networks 2025)

Gaps

Primary focus clinical neuroimaging (depression, autism) — not BCI control

…click to see all

Hubert Banville

medium hireability

AI Research Scientist@Meta

Previously: Research Scientist @ Interaxon

London, GB

Non-Invasive BCI95

Neural Signal Decoding95

Self-Supervised Neuro Learning95

Brain-Computer Interfaces90

EEG Foundation Models80

Strengths

SSL-EEG pioneer: 300-citation 2020 paper + 101-citation 2019 paper

Brain-to-text decoding (non-invasive, 2025) — direct query alignment

Gaps

No explicit large pretrained EEG foundation model akin to LLM at scale yet

…click to see all

Huy Phan

medium hireability

Research Scientist@Meta

Previously: Senior Research Scientist @ Amazon

Paris, FR

EEG Foundation Models90

Neural Signal Decoding85

Brain-Computer Interfaces80

Non-Invasive BCI78

Self-Supervised Neuro Learning68

Strengths

STELAR (2025): authored EEG Foundation Models paper — direct axis hit

AADNet (2024): auditory attention decoding from EEG/neural signals

Gaps

Focus is signal ML/decoding — limited end-to-end closed-loop BCI system work

…click to see all

Jiadong Pan

medium hireability

PhD student@Zhejiang University

Non-Invasive BCI75

Neural Signal Decoding72

Brain-Computer Interfaces70

Self-Supervised Neuro Learning65

EEG Foundation Models15

Strengths

LoongX (NeurIPS 2025): EEG+fNIRS+PPG BCI-driven image editing pipeline

Contrastive pretraining of neural encoders to semantic intent spaces

Gaps

No foundation model pretraining at scale — LoongX encodes but doesn't pretrain large EEG models

…click to see all

Jianxiong Gao

medium hireability

Intern@Shanghai Artificial Intelligence Laboratory

Previously: Intern @ Kuaishou Technology

Shanghai, CN

Neural Signal Decoding65

Self-Supervised Neuro Learning45

Brain-Computer Interfaces30

Non-Invasive BCI25

EEG Foundation Models5

Strengths

MinD-3D: fMRI → 3D object reconstruction, 13 citations (ECCV 2024)

MinD-3D++: advanced fMRI 3D reconstruction with textured mesh generation

Gaps

fMRI only — no EEG, MEG, or non-surgical BCI modality work

…click to see all

Jiaqi Wang

medium hireability

Ph.D. Candidate@Harbin Institute of Technology Shenzhen & Pengcheng Laboratory

Previously: AI Engineer Intern @ Huawei ICT

Shenzhen, CN

Neural Signal Decoding90

Non-Invasive BCI85

Self-Supervised Neuro Learning85

Brain-Computer Interfaces82

EEG Foundation Models75

Strengths

CET-MAE (ACL 2024) — contrastive EEG-text pretraining, transferable representations

BrainECHO — VQ spectrogram reconstruction for EEG-to-text (arXiv 2024)

Gaps

3rd-year PhD — mid-program, not nearing graduation

…click to see all

Jiaxuan Chen

medium hireability

PhD student@Zhejiang University

Neural Signal Decoding82

Non-Invasive BCI78

Brain-Computer Interfaces72

Self-Supervised Neuro Learning60

EEG Foundation Models15

Strengths

MindGPT: fMRI → natural language decoder, non-invasive (2024, 12 citations)

MindArt: brain recording → image, self-supervised OT learning (2025)

Gaps

All work is fMRI-based — no EEG or MEG expertise found

…click to see all

Jinglei Lv

medium hireability

Senior Research Fellow@University of Sydney

Previously: Research Scientist @ QIMR Berghofer

Neural Signal Decoding82

Non-Invasive BCI72

Brain-Computer Interfaces72

EEG Foundation Models52

Self-Supervised Neuro Learning18

Strengths

GCNs-net: decoding time-resolved EEG motor imagery (204 citations, 2022)

MEET: multi-band EEG Transformer for brain state decoding (2023)

Gaps

Foundation model work is fMRI-focused, not EEG-specific large-scale pretraining

…click to see all

Jinglei Lv

medium hireability

Senior Research Fellow@The University of Sydney

Previously: Senior Lecturer @ University of Melbourne

Neural Signal Decoding85

Non-Invasive BCI80

Brain-Computer Interfaces78

EEG Foundation Models65

Self-Supervised Neuro Learning55

Strengths

GCNs-net: 204-citation EEG motor imagery decoding paper (2022)

MEET: multi-band EEG transformer for brain state decoding (2023)

Gaps

Foundation model work focuses on fMRI, not EEG-native pretraining

…click to see all

Jingyuan Li

medium hireability

Applied Scientist@Amazon

Previously: Research Internship @ Microsoft

Seattle, US

Neural Signal Decoding82

Brain-Computer Interfaces82

Non-Invasive BCI75

Self-Supervised Neuro Learning40

EEG Foundation Models28

Strengths

Brain-to-Text Decoding (ICLR 2025): WER 9.93% → 5.77% via context-aware EEG reps

EEG mental imagery → 35-character translation (ICASSP 2025)

Gaps

No EEG foundation model work — decoding is task-specific, not large pretrained

…click to see all

Jingyun Xiao

medium hireability

PhD student in Machine Learning@Georgia Institute of Technology

Previously: MS student @ Georgia Institute of Technology

Self-Supervised Neuro Learning78

Neural Signal Decoding65

Brain-Computer Interfaces65

EEG Foundation Models45

Non-Invasive BCI20

Strengths

Self-supervised Perceiver for human iEEG — NeurIPS 2025 BrainBodyFM workshop

GAFormer (first author): scalable group-aware neural time series transformer, ICLR 2024

Gaps

No non-invasive EEG-specific work — focus is on iEEG/intracranial recordings

…click to see all

Jinzhao Zhou

medium hireability

PhD student@AAII

Sydney, AU

Neural Signal Decoding92

Brain-Computer Interfaces90

EEG Foundation Models88

Non-Invasive BCI85

Self-Supervised Neuro Learning85

Strengths

DeWave NeurIPS 2023 (63 cites) — EEG-to-text decoding landmark

BELT + BELT-2: contrastive EEG-language pretraining series

Gaps

No LinkedIn — career trajectory harder to assess

…click to see all

Joana Soldado-Magraner

medium hireability

Postdoctoral Research Associate@Carnegie Mellon University

Previously: PhD student @ University College London, University of London

Pittsburgh, US

Brain-Computer Interfaces60

Neural Signal Decoding35

Non-Invasive BCI10

EEG Foundation Models5

Self-Supervised Neuro Learning5

Strengths

MiSO (NeurIPS 2024): CNN closed-loop stimulation optimization, neural state control

Explicit BCI expertise: neuromodulation and intracortical recordings in research profile

Gaps

All BCI work is invasive/intracortical — no EEG, fNIRS, or MEG experience

…click to see all

Joel Ye

medium hireability

PhD Student@Carnegie Mellon University

Previously: Software Engineer Intern @ Microsoft

Pittsburgh, US

Brain-Computer Interfaces88

Neural Signal Decoding85

Self-Supervised Neuro Learning82

EEG Foundation Models40

Non-Invasive BCI20

Strengths

NDT2 (NeurIPS 2023): multi-context pretraining for neural spiking activity

ndt3: pretrained intracortical BCI decoders — active Jan 2026

Gaps

Primarily invasive/intracortical focus — limited EEG or non-invasive BCI work

…click to see all

Joséphine Raugel

medium hireability

Doctoral Student@Meta

Previously: Research Engineer @ École normale supérieure

Paris, FR

Neural Signal Decoding65

Brain-Computer Interfaces60

Non-Invasive BCI55

EEG Foundation Models30

Self-Supervised Neuro Learning25

Strengths

NeurIPS 2025 Spotlight — LLM-brain computational path alignment

CCN 2024 — decoding hierarchical speech inference from MEG signals

Gaps

Current PhD is brain-AI alignment, not BCI engineering or EEG systems

…click to see all

Kaicheng Fu

medium hireability

Full Professor@Chinese Academy of Sciences

Previously: Associate Professor @ Chinese Academy of Sciences

Beijing, CN

Neural Signal Decoding78

Brain-Computer Interfaces72

Non-Invasive BCI65

Self-Supervised Neuro Learning55

EEG Foundation Models40

Strengths

BraVL: visual neural decoding via multimodal brain-visual-linguistic model (2022)

BraiNav: self-supervised brain encoder on large-scale brain activity dataset (ICLR 2025)

Gaps

No explicit EEG-specific work — lab likely uses fMRI (visual stimuli paradigms)

…click to see all

Kaining Peng

medium hireability

MS student@Southern University of Science and Technology

Self-Supervised Neuro Learning65

Neural Signal Decoding25

Brain-Computer Interfaces20

Non-Invasive BCI15

EEG Foundation Models15

Strengths

DCA (NeurIPS 2025): pretrained autoencoder for brain atlas generation

MAE on fMRI (2024): self-supervised learning on brain imaging data

Gaps

No direct EEG or non-invasive BCI papers found

…click to see all

Kanhao Zhao

medium hireability

PhD student@Medicine, UCLA

Bethlehem, US

Self-Supervised Neuro Learning85

EEG Foundation Models82

Neural Signal Decoding65

Non-Invasive BCI45

Brain-Computer Interfaces35

Strengths

EEG-DisGCMAE: graph contrastive masked autoencoder SSL for EEG (ICLR 2025)

Cross-domain SSL pretraining fusing fMRI+EEG modalities

Gaps

No direct BCI control loop or closed-loop neural interface work

…click to see all

Konstantinos Barmpas

medium hireability

Machine Learning Engineer@Cogitat

Previously: PhD Candidate @ Imperial College London

London, GB

EEG Foundation Models95

Non-Invasive BCI90

Brain-Computer Interfaces90

Neural Signal Decoding85

Self-Supervised Neuro Learning75

Strengths

LaBraM++ author — NeurIPS 2025 EEG foundation model workshop

NeuroRVQ: multi-scale EEG tokenization (RVQ codebook approach)

Gaps

h=7; limited citation traction on newest foundation model papers

…click to see all

Konstantinos Kontras

medium hireability

Postdoctoral Research Visitor@MIT

Previously: PHD Researcher @ KU Leuven

Boston, US

Neural Signal Decoding45

Self-Supervised Neuro Learning40

Non-Invasive BCI25

Brain-Computer Interfaces15

EEG Foundation Models5

Strengths

CoRe-Sleep (TNSRE 2024): multimodal EEG sleep staging, 26 citations

EpilepsyChallenge: EEG seizure detection on TUH dataset

Gaps

No BCI control/closed-loop system design — passive signal analysis only

…click to see all

Kuan Han

medium hireability

Machine Learning Scientist, TikTok

Previously: Machine Learning Scientist @ TikTok

Neural Signal Decoding78

Self-Supervised Neuro Learning72

Non-Invasive BCI38

Brain-Computer Interfaces30

EEG Foundation Models20

Strengths

VAE for fMRI visual cortex decoding — 226 citations (2019)

Representation learning of resting-state fMRI via VAE (2024, 71 citations)

Gaps

fMRI-focused — not EEG; different modality from query's primary focus

…click to see all

Leilei Zhao

medium hireability

PhD student

Non-Invasive BCI68

Neural Signal Decoding65

Brain-Computer Interfaces65

EEG Foundation Models40

Self-Supervised Neuro Learning10

Strengths

S²M-Former: EEG auditory attention decoding — NeurIPS 2025

DB-tagged expertise: "EEG foundation model, RWKV, time series"

Gaps

Only one confirmed publication — sparse profile

…click to see all

Li Ruilin

medium hireability

Researcher@Shanda

Previously: Postdoc @ National University of Singapore

Brain-Computer Interfaces85

EEG Foundation Models82

Non-Invasive BCI80

Self-Supervised Neuro Learning78

Neural Signal Decoding75

Strengths

Brain-JEPA (NeurIPS 2024 spotlight) — brain dynamics foundation model

Brain Harmony (NeurIPS 2025) — multimodal brain foundation model, 70K fMRI+MRI samples

Gaps

Foundation models are fMRI-based, not EEG — EEG foundation model work is indirect

…click to see all

Mattia Orlandi

medium hireability

PHD Fellow@Alma Mater Studiorum - Università di Bologna

Previously: Studente tirocinante @ Institute of Neuroinformatics, University of Zurich and ETH Zurich

Bologna, IT

EEG Foundation Models40

Neural Signal Decoding35

Self-Supervised Neuro Learning30

Non-Invasive BCI25

Brain-Computer Interfaces20

Strengths

PhysioWave (2025) — pretrained EEG+EMG+ECG multimodal representation model

EEG-PPG sensor fusion for drowsiness detection (BioCAS 2024)

Gaps

Primary expertise is sEMG on edge hardware, not brain signals

…click to see all

Michael Hersche

medium hireability

Research Scientist@IBM

Previously: Research Associate @ IBM

Zurich, CH

Neural Signal Decoding90

Brain-Computer Interfaces90

Non-Invasive BCI85

EEG Foundation Models82

Self-Supervised Neuro Learning55

Strengths

EEG-TCNet (351 cites) — landmark motor imagery EEG decoding paper

ICLR 2025 neural compressor: iEEG→EEG domain transfer for cleaner signals

Gaps

Recent focus shifting toward neuro-symbolic AI and reasoning — BCI now secondary

…click to see all

Mina Jamshidi Idaji

medium hireability

research scientist@BIFOLD and TU Berlin

Previously: doctoral researcher @ Max Planck Institute for Human Cognitive and Brain Sciences

Brain-Computer Interfaces80

Non-Invasive BCI75

Neural Signal Decoding70

EEG Foundation Models58

Self-Supervised Neuro Learning12

Strengths

OSTDA: SSVEP-based BCI tensor pipeline — direct BCI decoding work

Sensorimotor BCI mu-rhythm paper (J. Neural Eng. 2024) — EEG BCI signal analysis

Gaps

Primary current focus shifted to AI in oncology/digital pathology — EEG is secondary

…click to see all

Na Lee

medium hireability

Data & AI/ML Engineer@Cogitat

Previously: Quantitative Developer @ Brevan Howard

London, GB

EEG Foundation Models90

Non-Invasive BCI75

Brain-Computer Interfaces70

Neural Signal Decoding65

Self-Supervised Neuro Learning50

Strengths

4 papers on Large Brainwave Foundation Models — all published 2025

ICML 2025 poster: fine-tuning insights for EEG foundation models

Gaps

h_index=1, limited citation footprint despite active 2025 publications

…click to see all

Nanda H Krishna

medium hireability

Visiting Researcher@ServiceNow Research

Previously: Graduate Student @ Mila

Montreal, CA

Neural Signal Decoding85

Brain-Computer Interfaces80

Self-Supervised Neuro Learning65

EEG Foundation Models20

Non-Invasive BCI15

Strengths

POSSM (NeurIPS 2025): real-time SSM neural decoder, 9x faster than Transformers

Multimodal neural decoding (NeurIPS 2025): self-supervised, spikes + LFPs

Gaps

Work is on invasive recordings (intracortical), not non-invasive EEG/MEG

…click to see all

Nan Huang

medium hireability

PhD student

Montreal, CA

EEG Foundation Models92

Self-Supervised Neuro Learning88

Neural Signal Decoding72

Non-Invasive BCI60

Brain-Computer Interfaces28

Strengths

LEAD (2025): EEG FM with self-supervised pretraining on 11 EEG datasets, 813 subjects

Sample + subject-level contrastive learning for inter-subject variation — direct axis match

Gaps

No BCI control work — EEG work is diagnostic (Alzheimer's detection), not intent/motor decoding

…click to see all

Nanlin Shi

medium hireability

Data Scientist, Risk Management@Bank OZK

Previously: Research Assistant, Data Analyst, Healthcare @ Duke University

Durham, US

Brain-Computer Interfaces85

Non-Invasive BCI80

Neural Signal Decoding80

Self-Supervised Neuro Learning75

EEG Foundation Models55

Strengths

EEG image decoding via contrastive self-supervised learning — SOTA 2024

MEG-EEG hybrid BCI: 312 bits/min, solved BCI illiteracy non-invasively

Gaps

No evidence of large-scale multi-dataset EEG foundation model pretraining

…click to see all

Nona Rajabi

medium hireability

Visiting PHD Student@EPFL

Previously: MSc Student @ Sharif University of Technology

Lausanne, CH

Non-Invasive BCI80

Brain-Computer Interfaces78

Neural Signal Decoding75

EEG Foundation Models40

Self-Supervised Neuro Learning18

Strengths

"Human-Aligned Image Models Improve Visual Decoding from Brain" (2025)

"Mind Meets Robots" EEG-BRI review covering 87 studies (2024)

Gaps

No dedicated work training EEG-specific foundation or self-supervised models

…click to see all

Philipp Bomatter

medium hireability

PhD student@University of Edinburgh

Previously: Researcher @ F. Hoffmann-La Roche Ltd.

Edinburgh, GB

Self-Supervised Neuro Learning65

Neural Signal Decoding55

EEG Foundation Models35

Non-Invasive BCI30

Brain-Computer Interfaces15

Strengths

"ML of brain-specific biomarkers from EEG" — eBioMedicine 2025, 28 citations

Explicit self-supervised learning evaluation for EEG scaling (arXiv 2025)

Gaps

No BCI interface or closed-loop control work — pure biomarker focus

…click to see all

Philipp Thölke

medium hireability

MS student@University of Montreal

Previously: Researcher @ Université de Montréal

Osnabrück, DE

EEG Foundation Models90

Non-Invasive BCI78

Neural Signal Decoding75

Brain-Computer Interfaces75

Self-Supervised Neuro Learning70

Strengths

REVE (NeurIPS 2025): EEG foundation model on 25,000 subjects — state-of-the-art scale

Neuro-GPT (2024, 78 citations): co-built large pretrained EEG model

Gaps

MS student — junior seniority, limited industry experience

…click to see all

Pierre Guetschel

medium hireability

EEG Foundation Models95

Self-Supervised Neuro Learning85

Non-Invasive BCI82

Brain-Computer Interfaces82

Neural Signal Decoding80

Strengths

OpenEEGBench: primary maintainer, benchmarks LaBraM/BIOT/BENDR/SignalJEPA

braindecode foundation model channel interpolation PRs (Apr 2026)

Gaps

No explicit open-to-work signal — timing of PhD completion unclear

…click to see all

Puli Wang

medium hireability

PhD student@zhejiang university

Neural Signal Decoding72

Brain-Computer Interfaces70

Self-Supervised Neuro Learning30

Non-Invasive BCI15

EEG Foundation Models5

Strengths

ICML 2025 paper on flow matching for few-trial neural adaptation

Behavioral decoding via hierarchical domain adaptation

Gaps

No EEG or non-invasive BCI work — research is on invasive motor cortex recordings

…click to see all

Quentin Barthélemy

medium hireability

ML researcher, PhD @ Foxstream

Previously: Researcher @ Foxstream

Brain-Computer Interfaces82

Non-Invasive BCI76

Neural Signal Decoding72

Self-Supervised Neuro Learning8

EEG Foundation Models5

Strengths

pyRiemann core maintainer (244 commits) — top Riemannian EEG/BCI library

P300 BCI Bayesian Riemannian paper (arXiv 2022)

Gaps

No EEG foundation model or large pretrained brain signal work

…click to see all

Ran Liu

medium hireability

Research Scientist@Apple

Previously: Graduate Research Assistant @ Georgia Institute of Technology

San Francisco, US

Neural Signal Decoding90

Self-Supervised Neuro Learning88

Brain-Computer Interfaces72

EEG Foundation Models68

Non-Invasive BCI35

Strengths

ICLR 2025 Spotlight: multi-session neural decoding, cell-types and brain regions

NeurIPS 2025 BrainBodyFM: unified pretraining on mixed neural modalities

Gaps

Most work on invasive recordings (electrophysiology, calcium imaging), not EEG

…click to see all

Reinmar J Kobler

medium hireability

Research Scientist@Meta

Previously: Visiting Scientist @ RIKEN

Paris, FR

Brain-Computer Interfaces92

Non-Invasive BCI90

Neural Signal Decoding88

EEG Foundation Models20

Self-Supervised Neuro Learning15

Strengths

Closed-loop EEG decoding for robotic arm control (97-cite 2020 paper)

SPD domain adaptation for EEG, NeurIPS 2022 + ICLR 2025

Gaps

No EEG foundation model or large-scale pretraining papers

…click to see all

Rikuto Kotoge

medium hireability

PhD student@Osaka University

Previously: MS student @ Osaka University

EEG Foundation Models82

Self-Supervised Neuro Learning80

Neural Signal Decoding72

Non-Invasive BCI62

Brain-Computer Interfaces52

Strengths

EvoBrain (NeurIPS 2025 Spotlight) — EEG seizure detection via dynamic GNNs

SplitSEE — self-supervised contrastive EEG pretraining, ICDM 2024

Gaps

Clinical signal analysis (seizure, sleep) — not closed-loop BCI control

…click to see all

Robin Tibor Schirrmeister

medium hireability

Researcher@Medical Center - University of Freiburg

Previously: Researcher @ Meta

Freiburg, DE

Neural Signal Decoding95

Brain-Computer Interfaces92

Non-Invasive BCI85

EEG Foundation Models65

Self-Supervised Neuro Learning65

Strengths

braindecode co-creator — foundational deep learning EEG/BCI library

265-citation EEG pathology diagnostics paper (2020)

Gaps

No large-scale foundation model work (pretraining billions of parameters on EEG)

…click to see all

Salar Abbaspourazad

medium hireability

Senior Machine Learning Scientist@Apple

Previously: Research Assistant @ University of Southern California

Self-Supervised Neuro Learning82

Neural Signal Decoding72

Brain-Computer Interfaces65

EEG Foundation Models28

Non-Invasive BCI25

Strengths

Large-scale Training of Foundation Models for Wearable Biosignals — ICLR 2024, 84 citations

Time-varying Representations via Self-supervised Learning — NeurIPS 2024

Gaps

No EEG-specific work; foundation models trained on ECG/PPG wrist wearables

…click to see all

Sébastien RIMBERT

medium hireability

ISFP@Inria

Bordeaux, FR

Brain-Computer Interfaces95

Non-Invasive BCI90

Neural Signal Decoding85

EEG Foundation Models22

Self-Supervised Neuro Learning18

Strengths

20+ EEG-BCI papers at Inria; h=13 — recognized BCI authority

Non-invasive EEG throughout: motor imagery, ERD/ERS, Riemannian geometry

Gaps

No explicit EEG foundation model or pretraining work found

…click to see all

Shihao Yang

medium hireability

PhD student@Stevens Institute of Technology

Neural Signal Decoding75

Non-Invasive BCI60

EEG Foundation Models40

Brain-Computer Interfaces35

Self-Supervised Neuro Learning10

Strengths

Multi-modal EEG+MEG source imaging via attention networks (2024, 15 citations)

XDL-ESI: explainable deep learning for EEG/iEEG source imaging (2024, 10 citations)

Gaps

No end-to-end BCI system work — source imaging, not closed-loop control

…click to see all

Shreyas Kaasyap

medium hireability

Neural Signal Decoding75

Brain-Computer Interfaces72

Self-Supervised Neuro Learning40

Non-Invasive BCI5

EEG Foundation Models5

Strengths

NeurIPS 2025: neural speech decoding, 20% WER reduction over GRU baseline

Time-masking + compact Transformer (83% fewer params, 52% less GPU memory)

Gaps

All work on invasive intracranial recordings, not EEG/MEG/fNIRS

…click to see all

Shuangchen Zhao

medium hireability

PhD student@Ph.D student at Institute of Automation, Chinese Academic of Sciences

Neural Signal Decoding35

Non-Invasive BCI28

Brain-Computer Interfaces25

EEG Foundation Models5

Self-Supervised Neuro Learning5

Strengths

NeuralOOD (2025): fMRI brain-machine fusion for CV robustness

EmoGrowth (2025): emotion decoding on brain activity datasets

Gaps

No EEG-specific or ECoG/MEG signal decoding work found

…click to see all

Sim Kuan Goh

medium hireability

Assistant Professor@Xiamen University Malaysia

Previously: Assistant Professor @ Xiamen University Malaysia

EEG Foundation Models82

Self-Supervised Neuro Learning78

Neural Signal Decoding75

Non-Invasive BCI65

Brain-Computer Interfaces60

Strengths

NeurIPT: Foundation Model for Neural Interfaces — masked pretraining, NeurIPS 2025

EEGDM: diffusion-based EEG representation learning (self-supervised, 2025)

Gaps

No evidence of closed-loop BCI control or real-time BCI system design

…click to see all

Simon Dahan

medium hireability

Postdoc@Meta

Previously: Postdoc @ Université de Lausanne

San Francisco, US

Self-Supervised Neuro Learning80

Neural Signal Decoding75

Brain-Computer Interfaces55

EEG Foundation Models50

Non-Invasive BCI35

Strengths

NeurIPS 2024: sEEG neural decoding paper (seegnificant) — direct signal decoding

Surface Masked Autoencoders — self-supervised pretraining on cortical brain data

Gaps

Most work on fMRI/cortical surface, not EEG specifically

…click to see all

Stefano Fenu

medium hireability

PhD student@Georgia Institute of Technology

Brain-Computer Interfaces60

Neural Signal Decoding45

Self-Supervised Neuro Learning40

Non-Invasive BCI35

EEG Foundation Models15

Strengths

BCI taxonomy paper (2025, 14 cit.) — application-level BCI field breadth

Self-supervised physiological time-series representations (2025)

Gaps

Primary work is invasive DBS, not non-invasive EEG-based BCI

…click to see all

Stéphane d'Ascoli

medium hireability

Research Scientist@Meta

Previously: AI4Science research fellow @ EPFL

Neural Signal Decoding90

Brain-Computer Interfaces88

Non-Invasive BCI85

EEG Foundation Models65

Self-Supervised Neuro Learning60

Strengths

Brain-to-text decoding: non-invasive approach via typing (2025, 22 citations)

Decoding individual words from 723 participants — large-scale non-invasive BCI

Gaps

Paris-based — may require relocation for US roles

…click to see all

Stylianos Bakas

medium hireability

BCI & AI/ML Engineer@Cogitat Ltd.

Previously: MS student @ Aristotle University of Thessaloniki

Brain-Computer Interfaces88

Non-Invasive BCI87

Neural Signal Decoding82

EEG Foundation Models78

Self-Supervised Neuro Learning58

Strengths

"Assessing LBMs" (ICLR 2025 workshop) — directly benchmarks EEG foundation models

Latent alignment for EEG decoding (2025, 9 citations) — core decoding research

Gaps

No dedicated self-supervised pretraining paper as primary contribution

…click to see all

Tasuku Kimura

medium hireability

Specially Appointed Assistant Professor@Osaka University

Osaka, JP

Self-Supervised Neuro Learning75

EEG Foundation Models60

Neural Signal Decoding55

Non-Invasive BCI45

Brain-Computer Interfaces30

Strengths

EvoBrain (NeurIPS 2025 spotlight): dynamic EEG graph + Mamba for seizure detection

SplitSEE: self-supervised EEG pretraining, time+freq domain contrastive clustering

Gaps

No closed-loop BCI systems — work is analysis/classification, not control interfaces

…click to see all

Thibault de Surrel

medium hireability

PhD Student@Université Paris Dauphine-PSL

Previously: Chercheur stagiaire @ Université Paris Dauphine-PSL

Paris, FR

Brain-Computer Interfaces75

Non-Invasive BCI72

Neural Signal Decoding55

Self-Supervised Neuro Learning35

EEG Foundation Models15

Strengths

"Interpretability of Riemannian tools in BCI" — IEEE MLSP 2025

PhD thesis on context-invariant EEG representations (BCI focus)

Gaps

No deep learning / transformer-based EEG modeling — purely geometric approach

…click to see all

Vadym Gryshchuk

medium hireability

PhD Fellow@University of Copenhagen

Previously: Visiting Researcher @ Universität Luxemburg

Copenhagen, DK

Non-Invasive BCI80

Neural Signal Decoding75

Brain-Computer Interfaces75

Self-Supervised Neuro Learning65

EEG Foundation Models25

Strengths

'Predicting Document Relevance from Brain Recordings' — EEG decoding with bimodal arch

23K word-level EEG dataset publicly released at HuggingFace

Gaps

No large pretrained EEG foundation model work — benchmarks existing models only

…click to see all

Valérie Marissens Cueva

medium hireability

PhD student@Inria

Previously: Predoctoral student @ CHRU de Nancy

Nancy, FR

Non-Invasive BCI72

Brain-Computer Interfaces72

Neural Signal Decoding65

Self-Supervised Neuro Learning45

EEG Foundation Models15

Strengths

"Reliable predictor of MI-BCI performance" — J. Neural Engineering 2025

Contrastive SSL for motor imagery — BCI Meeting 2023

Gaps

No large-scale EEG foundation model work — SSL is workshop/poster scale

…click to see all

Vernon Lawhern

medium hireability

Senior Research Scientist (Statistics / Machine Learning)@Army Research Laboratory

Previously: Research Scientist (Statistics / Machine Learning) @ Army Research Laboratory

Washington DC-Baltimore Area, US

Neural Signal Decoding95

Brain-Computer Interfaces95

Non-Invasive BCI92

EEG Foundation Models65

Self-Supervised Neuro Learning15

Strengths

EEGNet (2018): compact CNN for EEG BCI, de facto community baseline

arl-eegmodels repo: 1.5k stars, spans 4+ BCI paradigms

Gaps

Post-2022 research shifted to RL/reward learning, less active in EEG/BCI

…click to see all

Weihan Li

medium hireability

PhD student@Georgia Tech

Previously: MS student @ Zhejiang University

Neural Signal Decoding55

Brain-Computer Interfaces38

Self-Supervised Neuro Learning35

Non-Invasive BCI8

EEG Foundation Models5

Strengths

Online neural sequence detection — NeurIPS 2022 (core decoding work)

ICML 2025 Oral on scalable multi-region brain communication models

Gaps

All work uses invasive electrophysiology in animal studies — zero EEG work

…click to see all

Xiaohui Gao

medium hireability

PhD student@Northwestern Polytechnical University

Xi'an, CN

EEG Foundation Models82

Brain-Computer Interfaces75

Neural Signal Decoding72

Non-Invasive BCI68

Self-Supervised Neuro Learning58

Strengths

EpilepsyFM: EEG/SEEG foundation model, SOTA seizure detection (ICLR 2025)

MI-BCI classification paper — end-to-end motor imagery decoding from EEG

Gaps

No work on fNIRS or MEG-based non-invasive BCI

…click to see all

Xiaojun Ning

medium hireability

PhD student@Beijing Jiaotong University

Beijing, CN

Non-Invasive BCI75

Neural Signal Decoding75

Brain-Computer Interfaces70

Self-Supervised Neuro Learning50

EEG Foundation Models20

Strengths

GraphSleepNet (307 cites) — EEG spatial-temporal decoding for sleep stages

Multi-View Contrastive Learning on sleep signals — self-supervised neuro pretraining

Gaps

No evidence of large-scale pretrained foundation models for EEG

…click to see all

Xiaoyu Chen

medium hireability

PhD student@Institute of automation, Chinese academy of science, Chinese Academy of Sciences

Neural Signal Decoding72

Non-Invasive BCI65

Brain-Computer Interfaces65

Self-Supervised Neuro Learning28

EEG Foundation Models8

Strengths

fMRI audio reconstruction: SOTA on Brain2Sound/Music/Speech (2025)

Coarse-to-fine decoding pipeline — CLAP semantic + AudioMAE latent + LDM

Gaps

No EEG or MEG work — fMRI-only; less transferable to wearable BCI

…click to see all

Xinke Shen

medium hireability

Research Assistant Professor@Southern University of Science and Technology

Previously: Postdoctoral Fellow @ Southern University of Science and Technology

Shenzhen, CN

Self-Supervised Neuro Learning92

Non-Invasive BCI85

Neural Signal Decoding85

Brain-Computer Interfaces85

EEG Foundation Models80

Strengths

NeurIPS 2025 multi-dataset EEG pretraining — direct EEG foundation model work

IEEE TAC 2022 contrastive EEG reps — 262 citations, ESI Highly Cited

Gaps

China-based (Shenzhen) — relocation needed for most Western roles

…click to see all

Xuange Gao

medium hireability

PhD student@Institute of Automation, Chinese Academy of Sciences

EEG Foundation Models88

Self-Supervised Neuro Learning82

Neural Signal Decoding72

Non-Invasive BCI65

Brain-Computer Interfaces65

Strengths

EEGPT: first generalist EEG foundation model, autoregressive pretraining

Scales to 1.1B params — largest EEG architecture in literature

Gaps

EEGPT was withdrawn from ICLR 2025 — not peer-reviewed yet

…click to see all

Xuanliu Zhu

medium hireability

MS student

Neural Signal Decoding42

Self-Supervised Neuro Learning40

Brain-Computer Interfaces35

Non-Invasive BCI30

EEG Foundation Models5

Strengths

"Animate Your Thoughts" (2024) — fMRI-to-video neural decoding, 3 citations

Tri-modal contrastive learning over fMRI signals — self-supervised neuro approach

Gaps

Uses fMRI only — no EEG/MEG work; weak on core EEG BCI axes

…click to see all

Xuan Ma

medium hireability

Researcher@Northwestern University

Brain-Computer Interfaces80

Neural Signal Decoding75

Self-Supervised Neuro Learning28

EEG Foundation Models18

Non-Invasive BCI5

Strengths

Nature Comms 2025: BCI stabilization via latent dynamics alignment (79 citations)

eLife 2023: adversarial-network BCI decoder robustness (45 citations)

Gaps

No EEG or non-invasive BCI work — all research is intracortical/invasive

…click to see all

Xueyi Zhang

medium hireability

Intern@Nanyang Technological University

Previously: Intern @ The Chinese University of Hong Kong

Neural Signal Decoding72

Brain-Computer Interfaces70

Non-Invasive BCI52

EEG Foundation Models8

Self-Supervised Neuro Learning8

Strengths

CerebroVoice: sEEG brain-to-speech dataset + MoBSE framework

NeurIPS 2025 paper on sEEG auditory reconstruction (hypergraphs)

Gaps

No work on EEG foundation models or large-scale pretraining

…click to see all

Xujin Li

medium hireability

PhD student@NeuBCI Institute of Automation, Chinese Academy of Science

Brain-Computer Interfaces90

Non-Invasive BCI88

Neural Signal Decoding85

Self-Supervised Neuro Learning25

EEG Foundation Models20

Strengths

TSformer-SA: first-author EEG transformer decoder, Neural Networks 2025

Cross-task zero-calibration RSVP-BCI — practical deployment, Machine Intelligence Research 2025

Gaps

No evidence of large pretrained EEG foundation model work specifically

…click to see all

Xupeng Chen

medium hireability

Research Scientist@TikTok

New York, US

Neural Signal Decoding82

Brain-Computer Interfaces78

Non-Invasive BCI38

Self-Supervised Neuro Learning28

EEG Foundation Models18

Strengths

NMI 2024 neural speech decoding paper — 93 citations, flagship BCI work

flinkerlab/neural_speech_decoding — end-to-end ECoG speech synthesis pipeline

Gaps

Core speech BCI work uses invasive ECoG, not EEG/non-invasive signals

…click to see all

Yansen Wang

medium hireability

Researcher@Microsoft

Previously: MS student @ Carnegie Mellon University

Beijing, CN

EEG Foundation Models93

Neural Signal Decoding85

Brain-Computer Interfaces82

Non-Invasive BCI80

Self-Supervised Neuro Learning60

Strengths

EEGFormer (2024, 40 citations): large-scale EEG foundation model

NeuroLM (2025, 49 citations): multi-task foundation model bridging language + EEG

Gaps

No invasive BCI or neural implant work — purely EEG/non-invasive

…click to see all

Yassine El Ouahidi

medium hireability

IMT Atlantique

Previously: PhD student @ IMT Atlantique

EEG Foundation Models92

Neural Signal Decoding85

Brain-Computer Interfaces85

Non-Invasive BCI82

Self-Supervised Neuro Learning78

Strengths

REVE (NeurIPS 2025): SOTA EEG foundation model across 10 downstream tasks

60,000 hrs / 25,000 subjects pretraining — largest EEG pretraining effort to date

Gaps

h_index 4 — early career, limited citation footprint

…click to see all

Yi Ding

medium hireability

Research Assistant Professor@Nanyang Technological University

Previously: Postdoc @ Nanyang Technological University

Singapore, SG

Brain-Computer Interfaces92

Non-Invasive BCI88

Neural Signal Decoding85

EEG Foundation Models75

Self-Supervised Neuro Learning55

Strengths

LGGNet (168 citations) — graph EEG representations for BCI

TSception (142 citations) — spatial-temporal EEG decoding framework

Gaps

Focused on affective/emotion EEG — less work on speech or motor decoding

…click to see all

Yijie Ding

medium hireability

Master of Engineering student@Media Interaction and Computing Lab (MICL) within the College of Computing and Data Science at Nanyang Technological University

Previously: Undergrad student @ Nanyang Technological University

EEG Foundation Models95

Brain-Computer Interfaces95

Neural Signal Decoding92

Non-Invasive BCI90

Self-Supervised Neuro Learning78

Strengths

Brain Foundation Models survey (2025) — co-defined the field

Uni-NTFM: EEG foundation model paper (2025) — direct match

Gaps

Master's student — less industry experience than PhD or postdoc candidates

…click to see all

Yiqun Duan

medium hireability

Senior Research Scientist@Meta

Previously: Research Scientist @ TikTok

San Francisco, US

Neural Signal Decoding92

Brain-Computer Interfaces90

EEG Foundation Models88

Non-Invasive BCI85

Self-Supervised Neuro Learning83

Strengths

DeWave (NeurIPS 2023) — EEG-to-text via discrete codex, 400+ GitHub stars

BELT-2: multi-task EEG-language alignment with self-supervised pretraining

Gaps

Only ~9 months at Meta — low mobility window

…click to see all

Yi Zhong

medium hireability

PhD student@Beijing University of Posts and Telecommunications

Neural Signal Decoding60

Non-Invasive BCI55

Brain-Computer Interfaces55

EEG Foundation Models8

Self-Supervised Neuro Learning5

Strengths

S2M-Former (NeurIPS 2025): EEG decoding for auditory attention

AAD benchmarks: KUL, DTU, AV-GC-AAD — non-invasive EEG setup

Gaps

BCI is one paper only; primary research is medical imaging

…click to see all

Yizhuo Lu

medium hireability

Ph.D. student@Institute of Automation, Chinese Academy of Sciences

Previously: Undergrad student @ Beijing Institute of Technology

Beijing, CN

Neural Signal Decoding82

Brain-Computer Interfaces78

Non-Invasive BCI75

EEG Foundation Models38

Self-Supervised Neuro Learning30

Strengths

ICLR 2025 'Animate Your Thoughts' — fMRI→dynamic video BCI decoding

MindDiffuser (ACM MM 2023, 60 citations) — brain activity image reconstruction

Gaps

Most decoding work is fMRI-based, not EEG — limited non-invasive EEG depth

…click to see all

Yizi Zhang

medium hireability

PhD student@Columbia University

Neural Signal Decoding88

Self-Supervised Neuro Learning82

Brain-Computer Interfaces72

EEG Foundation Models20

Non-Invasive BCI8

Strengths

NEDS (ICML 2025 Spotlight) — bidirectional neural foundation model, 83 animals

Universal Translator NeurIPS 2024 — self-supervised cross-animal spike decoding

Gaps

All work on invasive recordings (Neuropixels, Utah arrays) — no EEG/fNIRS

…click to see all

Yohann Benchetrit

medium hireability

Researcher@Meta

Neural Signal Decoding95

Non-Invasive BCI90

Brain-Computer Interfaces85

EEG Foundation Models72

Self-Supervised Neuro Learning60

Strengths

"Decoding words from non-invasive brain recordings" — EEG+MEG, 723 participants (2024)

Real-time MEG visual decoding — ICLR 2024 brain decoding paper

Gaps

Most work is fMRI/MEG-centric — less dedicated EEG foundation model work

…click to see all

Yonghao Song

medium hireability

Non-Invasive BCI95

Neural Signal Decoding95

Brain-Computer Interfaces90

Self-Supervised Neuro Learning88

EEG Foundation Models80

Strengths

NICE-EEG (ICLR 2024): image decoding from M/EEG, contrastive learning

EEG-Conformer (TNSRE 2023): pioneering transformer for EEG decoding

Gaps

Based in China (Tsinghua/Shanghai AI Lab) — timezone/relocation consideration

…click to see all

Yong Jiao

medium hireability

Postdoc@Lehigh University

Self-Supervised Neuro Learning85

EEG Foundation Models80

Non-Invasive BCI45

Neural Signal Decoding35

Brain-Computer Interfaces30

Strengths

EEG-DisGCMAE (ICML'25): graph contrastive + masked autoencoder EEG pretraining

fMRI+EEG multi-modal self-supervised fusion paper (2024)

Gaps

No published work on explicit BCI decoding (intent/speech/motor commands)

…click to see all

Yu-Ting Lan

medium hireability

Shanghai Jiao Tong Unviersity

Previously: Researcher @ ByteDance

Self-Supervised Neuro Learning80

Neural Signal Decoding78

Non-Invasive BCI75

EEG Foundation Models65

Brain-Computer Interfaces55

Strengths

NeuroImagen: EEG-to-visual image reconstruction via latent diffusion (29 cites)

REmoNet: masked channel modeling + contrastive self-supervision on EEG (MM 2024)

Gaps

No closed-loop BCI systems or real-time control work

…click to see all

Zhuoyi Li

medium hireability

PhD student@Northwestern Polytechnical University

Neural Signal Decoding85

Brain-Computer Interfaces85

Non-Invasive BCI80

EEG Foundation Models78

Self-Supervised Neuro Learning35

Strengths

EpilepsyFM: domain-specific EEG foundation model (Neural Networks 2025)

Speech imagery multi-character EEG classification (42 citations, 2024)

Gaps

EpilepsyFM is epilepsy-specific — no general-purpose EEG FM work

…click to see all

Ziyu Jia

medium hireability

Assistant Professor@Institute of Automation, Chinese Academy of Sciences

EEG Foundation Models92

Non-Invasive BCI87

Neural Signal Decoding85

Brain-Computer Interfaces85

Self-Supervised Neuro Learning60

Strengths

CodeBrain & Uni-NTFM: actively building EEG foundation models (2025)

Brain Foundation Models survey (2025, 13 cites) — recognized authority

Gaps

No invasive (ECoG/implant) signal decoding — purely non-invasive EEG focus

…click to see all

Zongsheng Li

medium hireability

PhD student@The Chinese University of Hong Kong, Shenzhen

Shenzhen, CN

EEG Foundation Models82

Self-Supervised Neuro Learning72

Neural Signal Decoding68

Non-Invasive BCI60

Brain-Computer Interfaces45

Strengths

mdJPT NeurIPS 2025 — multi-dataset joint EEG pre-training, outperforms SOTA large-scale EEG models

Zero-shot cross-dataset EEG generalization without per-subject calibration

Gaps

Focus is emotion/affective EEG — not motor, speech, or intent decoding

…click to see all

Abbas Rahimi

low hireability

Research Staff Member@IBM

Previously: Postdoctoral Researcher @ UC Berkeley

Zurich, CH

Neural Signal Decoding80

EEG Foundation Models72

Brain-Computer Interfaces65

Non-Invasive BCI52

Self-Supervised Neuro Learning38

Strengths

MVPFormer: first open-source iEEG foundation model, SOTA seizure detection (NeurIPS 2025 WS)

ICLR 2025: neural compressor enabling iEEG-to-noisy-EEG transfer

Gaps

Most prominent BCI work is iEEG (invasive), not non-invasive EEG

…click to see all

Adeen Flinker

low hireability

Assistant Professor@New York University

Previously: Postdoc @ New York University

New York, US

Neural Signal Decoding85

Brain-Computer Interfaces70

Self-Supervised Neuro Learning20

EEG Foundation Models15

Non-Invasive BCI5

Strengths

Nature MI 2024: deep learning speech decoding from ECoG — 87 citations

Transformer-based neural speech decoding (2025) — latest decoding methods

Gaps

ECoG-only — invasive modality, not EEG or non-invasive BCI

…click to see all

Alexander Mathis

low hireability

Assistant Professor@EPFL

Previously: Postdoctoral Fellow @ Harvard University

Lausanne, CH

Self-Supervised Neuro Learning90

Neural Signal Decoding75

Brain-Computer Interfaces55

EEG Foundation Models40

Non-Invasive BCI15

Strengths

CEBRA: contrastive SSL for neural data, Nature 2023, 415 cites

"Decoding the brain" review paper (2024) — direct axis match

Gaps

No EEG-specific or non-invasive BCI work found

…click to see all

Alireza Amirshahi

low hireability

AI Engineer@Logitech

Previously: Doctoral Assistant @ ESL - Embedded Systems Lab

Lausanne, CH

Neural Signal Decoding72

Non-Invasive BCI70

Brain-Computer Interfaces65

Self-Supervised Neuro Learning8

EEG Foundation Models5

Strengths

EPFL ESL PhD 2019–2024 on EEG seizure detection for wearables

esl-epfl/metawears contributor — TUSZ/Seina EEG, MAML few-shot seizure detection

Gaps

No EEG foundation model or large-scale pretraining work

…click to see all

Amy L Orsborn

low hireability

Assistant Professor@University of Washington

Previously: Postdoctoral Researcher @ New York University

Seattle, US

Brain-Computer Interfaces90

Neural Signal Decoding85

Non-Invasive BCI20

Self-Supervised Neuro Learning12

EEG Foundation Models5

Strengths

Closed-loop decoder adaptation shapes neural plasticity (2014, 332 citations)

Design + analysis of closed-loop decoder adaptation algorithms (2013, 136 citations)

Gaps

Primarily invasive BCI (intracortical/ECoG) — limited EEG or non-invasive scope

…click to see all

Antoine Collas

low hireability

Postdoctoral Researcher@Inria

Previously: PhD @ CentraleSupélec

Paris, FR

Neural Signal Decoding80

EEG Foundation Models75

Non-Invasive BCI68

Brain-Computer Interfaces55

Self-Supervised Neuro Learning40

Strengths

Karavela.ai models lead — building brain foundation model for decoding

NeurIPS 2024 spotlight on EEG domain adaptation via Riemannian geometry

Gaps

No published work on large pretrained EEG transformer/foundation models

…click to see all

Berkay Döner

low hireability

Doctoral Researcher@EPFL

Previously: Project Engineer @ CIRRUS Consultancy and Engineering

Lausanne, CH

EEG Foundation Models90

Self-Supervised Neuro Learning80

Non-Invasive BCI70

Neural Signal Decoding65

Brain-Computer Interfaces50

Strengths

LUNA: topology-agnostic EEG foundation model, NeurIPS 2025

Self-supervised masked-patch pretraining on 21,000h raw EEG data

Gaps

Recently joined Apple — new hire, likely <1 year in role

…click to see all

Blake Aaron Richards

low hireability

Researcher@Google

Previously: Senior Vice President & General Counsel @ HALO Networks

Montréal, CA

Neural Signal Decoding90

Self-Supervised Neuro Learning85

Brain-Computer Interfaces60

EEG Foundation Models40

Non-Invasive BCI10

Strengths

'Multi-session neural decoding' transformer on Allen Brain Observatory (ICLR 2025 Spotlight)

'Universal Translator' — MtM self-supervised foundation model for spiking data (NeurIPS 2024)

Gaps

All decoding work in invasive modalities (Neuropixels, Ca2+ imaging) — no EEG/MEG work

…click to see all

Boyla Mainsah

low hireability

Assistant Research Professor in the Department of Electrical and Computer Engineering@Duke University

Previously: Assistant Professor in Neurology @ Duke University

Durham, US

Non-Invasive BCI88

Brain-Computer Interfaces85

Neural Signal Decoding80

EEG Foundation Models18

Self-Supervised Neuro Learning18

Strengths

bigP3BCI (2025): open P300-BCI dataset — active non-invasive EEG research

10+ papers on P300/ERP neural decoding for spelling BCI

Gaps

No EEG foundation model or large-scale neural pretraining work

…click to see all

Bruno Aristimunha

low hireability

AI Research Scientist@Yneuro

Previously: Research Engineer / Joint PhD Student @ Inria

Paris, FR

Neural Signal Decoding93

Brain-Computer Interfaces92

Non-Invasive BCI90

EEG Foundation Models80

Self-Supervised Neuro Learning50

Strengths

Braindecode lead (672 commits) — gold-standard EEG deep learning library

MOABB lead maintainer — BCI reproducibility benchmark (46 citations)

Gaps

New hire at Yneuro (<1 year) — unlikely to leave so soon

…click to see all

Cédric Rommel

low hireability

Research Scientist@Meta

Previously: AI Research Scientist @ Valeo

Paris, FR

Neural Signal Decoding75

Brain-Computer Interfaces68

Non-Invasive BCI65

Self-Supervised Neuro Learning45

EEG Foundation Models30

Strengths

102 commits to braindecode — core contributor to EEG/MEG deep learning library

EEG data augmentation paper: 111 citations (J. Neural Engineering 2022)

Gaps

No published foundation model or large-scale pretraining work on EEG

…click to see all

Changde Du

low hireability

Associate Researcher@Institute of Automation, Chinese Academy of Sciences

Previously: Researcher @ Huawei Technologies Ltd.

Beijing, CN

Neural Signal Decoding92

Non-Invasive BCI82

Brain-Computer Interfaces80

Self-Supervised Neuro Learning55

EEG Foundation Models35

Strengths

BraVL: visual neural decoding via brain-visual-linguistic multimodal learning (127 citations)

EEG emotion recognition with domain adaptation — 290 citations, foundational work

Gaps

No explicit EEG foundation model (large-scale pretrained over EEG) — uses EEG but not pretraining paradigm

…click to see all

Cunhang Fan

low hireability

associate professor@School of Computer Science and Technology, Anhui University

Previously: PhD student @ Institute of automation, Chinese academy of science

Hefei, CN

Neural Signal Decoding90

Non-Invasive BCI85

Brain-Computer Interfaces80

Self-Supervised Neuro Learning28

EEG Foundation Models22

Strengths

DBPNet/DARNet: dual-path auditory attention decoding from EEG (NeurIPS 2024)

SSM2Mel: Mamba state-space model decoding EEG → Mel spectrogram

Gaps

No EEG foundation model work — no large pretrained models over broad neural time-series

…click to see all

Dalin Zhang

low hireability

Lixing Distinguished Professor@Hangzhou Dianzi University

Previously: Associate Professor @ Aalborg University

Hangzhou, CN

Neural Signal Decoding85

Brain-Computer Interfaces85

Non-Invasive BCI80

Self-Supervised Neuro Learning70

EEG Foundation Models20

Strengths

329-cite EEG BCI paper (2018) — motor imagery, intention recognition core track record

Self-Supervised EEG Representation Learning (2024) — direct SSL neuro learning evidence

Gaps

No EEG/neural foundation model work — self-supervised paper is emotion-focused, not large-scale pretraining

…click to see all

Emadeldeen Eldele

low hireability

Assistant Professor@Khalifa University

Previously: Research Scientist @ A*STAR

Abu Dhabi, AE

Self-Supervised Neuro Learning85

EEG Foundation Models65

Neural Signal Decoding60

Non-Invasive BCI55

Brain-Computer Interfaces35

Strengths

AttnSleep: 625-citation EEG sleep staging (single-channel, TNSRE 2021)

TS-TCC: 768-citation self-supervised contrastive for time-series (IJCAI 2021)

Gaps

EEG work limited to sleep staging — no motor imagery, P300, or SSVEP BCI tasks

…click to see all

Fabien Lotte

low hireability

Research Director@Inria

Previously: Research Scientist @ INRIA Bordeaux Sud-Ouest

Talence, FR

Brain-Computer Interfaces97

Non-Invasive BCI92

Neural Signal Decoding88

EEG Foundation Models5

Self-Supervised Neuro Learning5

Strengths

h=56 — one of world's top BCI/EEG researchers

Motor imagery EEG decoding via Riemannian geometry — seminal work

Gaps

No foundation model or self-supervised pretraining work at all

…click to see all

Fani Deligianni

low hireability

Senior Lecturer (Associate Professor)@University of Glasgow

Previously: Lecturer @ University of Glasgow

Glasgow, GB

Non-Invasive BCI70

Brain-Computer Interfaces65

Neural Signal Decoding55

Self-Supervised Neuro Learning45

EEG Foundation Models18

Strengths

Cross-subject EEG transfer learning (Riemannian tangent space, 2025)

fMRI-EEG connectome fusion — 162-citation paper (2014)

Gaps

EEG foundation models: no pretrained large-scale EEG model work found

…click to see all

Florian Yger

low hireability

Associate Professor@Institut National des Sciences Appliquées de Rouen

Previously: Associate Professor @ Université Paris-Dauphine

Rouen, FR

Brain-Computer Interfaces90

Non-Invasive BCI80

Neural Signal Decoding75

EEG Foundation Models5

Self-Supervised Neuro Learning5

Strengths

EEG-BCI classification review (2018): 2,465 citations — field-defining authority

Riemannian approaches in BCI review (2017): 473 citations

Gaps

No work on foundation models or large-scale neural pretraining

…click to see all

Gang Pan

low hireability

Professor@Zhejiang University

Previously: Associate Professor @ Zhejiang University

Hangzhou, CN

Brain-Computer Interfaces95

EEG Foundation Models92

Neural Signal Decoding92

Non-Invasive BCI88

Self-Supervised Neuro Learning55

Strengths

CBraMod (2025) — EEG foundation model, 52 citations, directly on-target

EEGMamba (2025) — second EEG foundation model, Mamba architecture

Gaps

Tenured professor (2003) + State Key Lab director — near-zero mobility

…click to see all

Giulia Lioi

low hireability

Associate Professor@IMT Atlantique

Previously: Postdoc @ INRIA

EEG Foundation Models97

Self-Supervised Neuro Learning92

Brain-Computer Interfaces88

Non-Invasive BCI85

Neural Signal Decoding82

Strengths

REVE: largest EEG pretraining effort (92 datasets, 25K subjects, NeurIPS 2025)

Masked autoencoding self-supervised pretraining on 60K hours of EEG

Gaps

Tenured French academic — low mobility without strong incentive

…click to see all

Guy Gaziv

low hireability

Postdoctoral Researcher, AI / Computational Neuroscience@MIT

Previously: Postdoctoral Fellow, AI / Computational Neuroscience @ Weizmann Institute of Science

Boston, US

Self-Supervised Neuro Learning85

Neural Signal Decoding72

Non-Invasive BCI62

Brain-Computer Interfaces58

EEG Foundation Models10

Strengths

163-citation self-supervised fMRI decoding paper — landmark in brain decoding

3 self-supervised brain reconstruction papers (2019–2022)

Gaps

fMRI-focused, not EEG — limited transfer to real-time BCI

…click to see all

Han Zhang

low hireability

Research Scientist@Meta

Previously: Co-Founder @ Reve

San Francisco, US

Non-Invasive BCI65

Neural Signal Decoding65

Brain-Computer Interfaces60

EEG Foundation Models10

Self-Supervised Neuro Learning5

Strengths

EEG Motor Imagery Classification (IEEE TNSRE 2020, 83 citations) — direct non-invasive BCI

Motor imagery recognition with automatic EEG channel selection (2020, 97 citations)

Gaps

No EEG foundation model or self-supervised pretraining work

…click to see all

Jean-Remi King

low hireability

CNRS researcher@École Normale Supérieure

Neural Signal Decoding97

Non-Invasive BCI93

Brain-Computer Interfaces90

Self-Supervised Neuro Learning88

EEG Foundation Models82

Strengths

Decoding speech perception from non-invasive brain recordings (NMI 2023, 288 cit)

Brain2Qwerty: non-invasive MEG typing system (2025, 22 cit)

Gaps

Dual tenured positions (CNRS permanent + Meta FAIR) — very hard to recruit

…click to see all

Jérémy Rapin

low hireability

Research Engineer@Meta

Previously: Chief Data Officer @ CardioLogs

Paris, FR

Neural Signal Decoding90

Non-Invasive BCI88

Brain-Computer Interfaces75

EEG Foundation Models35

Self-Supervised Neuro Learning28

Strengths

'Decoding speech perception from non-invasive brain recordings' (Nature MI 2023, 288 cit.)

Brain-to-Text Decoding 2025: MEG non-invasive typing — direct BCI system work

Gaps

No explicit self-supervised pretraining paper (SSL/contrastive) for brain signals

…click to see all

Jiquan Wang

low hireability

Research Fellow@State Key Laboratory of Brain-Machine Intelligence, Zhejiang University

Previously: PhD student @ Zhejiang University

Hangzhou, CN

EEG Foundation Models95

Neural Signal Decoding90

Brain-Computer Interfaces90

Non-Invasive BCI85

Self-Supervised Neuro Learning70

Strengths

CBraMod (ICLR 2025) — first-author EEG foundation model, 52 citations, 306 stars

EEGMamba + DeeperBrain — two additional EEG foundation models in 2025-2026

Gaps

Low hireability — 1 year into Research Fellow role, grants through 2027, recruiting students

…click to see all

Kan Ren

low hireability

Assistant Professor@ShanghaiTech University

Previously: Researcher @ Microsoft

Shanghai, CN

Neural Signal Decoding88

EEG Foundation Models85

Non-Invasive BCI78

Brain-Computer Interfaces75

Self-Supervised Neuro Learning62

Strengths

EEG2Video (NeurIPS 2024) — EEG-to-video visual perception decoding

EEGFormer — large-scale transferable EEG foundation model (2024)

Gaps

Primary focus shifting to LLMs/data agents — EEG is one of several streams

…click to see all

Khaled Kamal Saab

low hireability

Member of Technical Staff@OpenAI

Previously: Senior Research Scientist @ DeepMind

San Francisco, US

Neural Signal Decoding80

Self-Supervised Neuro Learning75

Non-Invasive BCI45

EEG Foundation Models40

Brain-Computer Interfaces30

Strengths

Self-Supervised GNN for EEG Seizure Analysis — ICLR 2022, core topic match

GNN + SSM for multivariate biosignals — ICLR 2023 Oral

Gaps

Clinical EEG focus (seizure detection), not motor/speech BCI decoding

…click to see all

Klaus Robert Muller

low hireability

Researcher@Google

Brain-Computer Interfaces95

Neural Signal Decoding90

Non-Invasive BCI88

EEG Foundation Models30

Self-Supervised Neuro Learning22

Strengths

Co-founder Berlin BCI lab — foundational EEG/BCI authority

fNIRS deep learning review (IEEE Rev. Biomed. Eng. 2026) — non-invasive BCI

Gaps

No EEG foundation model or self-supervised pretraining work found

…click to see all

Liming Zhao

low hireability

Phd Candidate@Shanghai Jiao Tong University

Previously: Researcher @ Emotionhelper

Shanghai, CN

EEG Foundation Models82

Brain-Computer Interfaces75

Non-Invasive BCI72

Neural Signal Decoding65

Self-Supervised Neuro Learning60

Strengths

LaBraM (ICLR 2024 spotlight): large brain model for EEG — 601 stars

SJTU BCMI lab — top-tier EEG/BCI group under Bao-liang Lu

Gaps

Stale profile — website last updated 2019; current role/status unknown

…click to see all

Lu Mi

low hireability

Assistant Professor@Georgia Institute of Technology

Previously: Shanahan Foundation Fellow @ Allen Institute

Atlanta, US

Neural Signal Decoding80

Brain-Computer Interfaces78

Self-Supervised Neuro Learning65

Non-Invasive BCI40

EEG Foundation Models20

Strengths

SPINT NeurIPS 2025: cross-session intracortical motor BCI decoding

BrainMIND: fMRI voxel → semantic concept decoding pipeline

Gaps

No EEG-specific work — focuses on intracortical and fMRI modalities

…click to see all

Mahsa Shoaran

low hireability

Assistant Professor@EPFL

Previously: Assistant Professor @ Cornell University

Lausanne, CH

Brain-Computer Interfaces90

Neural Signal Decoding82

Non-Invasive BCI42

Self-Supervised Neuro Learning20

EEG Foundation Models18

Strengths

MiBMI (2024): miniaturized chip for 31-class brain-to-text decoding

REST (2024): EEG seizure analysis via efficient state-update model

Gaps

No EEG foundation model work — ML focus is on-chip inference, not pretraining

…click to see all

Mariya Toneva

low hireability

Assistant Professor@Max Planck Institute for Software Systems

Previously: Postdoc @ Princeton University

Saarbrücken, DE

Neural Signal Decoding70

EEG Foundation Models45

Self-Supervised Neuro Learning45

Non-Invasive BCI40

Brain-Computer Interfaces35

Strengths

NeurIPS 2020: zero-shot MEG prediction of brain meaning representations

Brain-tuning (2024–25): brain recordings as fine-tuning signal for speech LLMs

Gaps

No end-to-end BCI engineering — purely computational neuroscience perspective

…click to see all

Michael Tangermann

low hireability

Head of the Brain State Decoding Lab@University of Freiburg

Previously: Postdoc researcher @ Technical University of Berlin

Freiburg, DE

Brain-Computer Interfaces98

Neural Signal Decoding97

Non-Invasive BCI93

EEG Foundation Models82

Self-Supervised Neuro Learning78

Strengths

CNN-EEG decoding paper (2017): 3,865 citations — field-defining work

S-JEPA (2024): self-supervised JEPA for seamless cross-dataset EEG transfer

Gaps

Tenured professor (h=43) — very unlikely to leave academia

…click to see all

Motoaki Kawanabe

low hireability

Department Head@Advanced Telecommunications Research Institute International

Previously: PhD student @ The University of Tokyo

Brain-Computer Interfaces85

Non-Invasive BCI82

Neural Signal Decoding75

Self-Supervised Neuro Learning30

EEG Foundation Models15

Strengths

'Stationary CSP for BCI' — 285 cites; foundational EEG decoding paper

'LDA adaptation for BCI' — 360 cites; unsupervised BCI calibration

Gaps

No EEG foundation model or large-scale pretraining work

…click to see all

Nima Ryan Hadidi

low hireability

PhD student@University of California, Los Angeles

Trabuco Canyon, US

Brain-Computer Interfaces80

Neural Signal Decoding75

Non-Invasive BCI60

Self-Supervised Neuro Learning25

EEG Foundation Models15

Strengths

Neural speech decoding paper (intracranial → speech, Transformer, 2025)

SplashNet sEMG typing BCI — SOTA non-invasive character decoding

Gaps

No EEG or MEG work — lab uses invasive intracranial recordings primarily

…click to see all

Qibin Zhao

low hireability

Team Director@RIKEN

Previously: Team Leader @ RIKEN

Tokyo, JP

Brain-Computer Interfaces85

Non-Invasive BCI75

Neural Signal Decoding68

Self-Supervised Neuro Learning22

EEG Foundation Models12

Strengths

SPD batch-norm for EEG domain adaptation — 82 citations (2022)

17+ years of BCI/EEG research (2007–2025)

Gaps

No EEG foundation model or large pretrained neural-signal model work

…click to see all

Qinhua Jenny Sun

low hireability

Senior Algorithm Engineer@Edwards Lifesciences

Previously: Graduate Student @ UC Irvine

Irvine, US

Neural Signal Decoding60

Non-Invasive BCI35

Brain-Computer Interfaces30

Self-Supervised Neuro Learning20

EEG Foundation Models8

Strengths

NCVA (Neuroimage 2024): EEG + VAE for cognitive parameter decoding

EEG-Decision-SincNet: interpretable ML on multi-channel EEG

Gaps

No foundation model or large-scale pretrained EEG model work

…click to see all

Rajkumar Saini

low hireability

Senior Lecturer@Luleå University of Technology

Previously: Postdoctoral Researcher @ EISLAB Machine Learning

Luleå, SE

Non-Invasive BCI78

Brain-Computer Interfaces74

Neural Signal Decoding72

EEG Foundation Models12

Self-Supervised Neuro Learning10

Strengths

Inner speech decoding via EEG+fMRI (2022–2024 series, reproducibility study)

Envisioned speech recognition from EEG sensors (2018, 127 citations)

Gaps

No EEG foundation model work — traditional ML/DL, not large-scale pretraining

…click to see all

Sebastian Michelmann

low hireability

Assistant Professor@New York University

Previously: PhD student @ University of Birmingham

New York, US

Neural Signal Decoding60

Non-Invasive BCI45

Brain-Computer Interfaces42

EEG Foundation Models12

Self-Supervised Neuro Learning8

Strengths

P300 classification (Riemannian ensemble, 2024) — direct BCI paradigm

'Podcast' ECoG dataset for neural language modeling (2025)

Gaps

Primary focus is episodic memory/cognitive neuroscience, not BCI engineering

…click to see all

Steffen Schneider

low hireability

Principal Researcher@Helmholtz Munich

Previously: PhD student @ Swiss Federal Institute of Technology Lausanne

Munich, DE

Self-Supervised Neuro Learning88

Neural Signal Decoding75

Brain-Computer Interfaces52

Non-Invasive BCI12

EEG Foundation Models12

Strengths

CEBRA: contrastive neural decoding, 415 cites, Nature 2023

Decodes motor/position from spike trains and calcium imaging

Gaps

No EEG or non-invasive BCI work — all work is on invasive recordings

…click to see all

SUBBA REDDY OOTA

low hireability

Research Scientist@ADIA

Previously: Sr. Machine Learning Scientist @ Woundtech

Neural Signal Decoding72

Non-Invasive BCI52

Brain-Computer Interfaces40

EEG Foundation Models18

Self-Supervised Neuro Learning15

Strengths

"fMRI Semantic Category Decoding" (2018) — direct neural signal decoding

"Multi-view and Cross-view Brain Decoding" COLING 2022 — multimodal decoding

Gaps

No EEG-specific papers; work focuses on fMRI and MEG, not EEG

…click to see all

Sylvain Chevallier

low hireability

Full Professor@Université Paris-Saclay

Previously: Scientific Researcher @ Université Paris-Saclay

Paris, FR

Brain-Computer Interfaces97

Non-Invasive BCI95

Neural Signal Decoding92

Self-Supervised Neuro Learning42

EEG Foundation Models35

Strengths

MOABB: largest EEG/BCI benchmark study — primary creator and maintainer

PyRiemann: widely-used Riemannian EEG ML package, 28 citations v0.5 alone

Gaps

No dedicated foundation model or SSL pretraining work on EEG

…click to see all

Thomas Moreau

low hireability

researcher@INRIA

Previously: PhD student @ ENS Paris-Saclay

Neural Signal Decoding78

Non-Invasive BCI75

Brain-Computer Interfaces72

EEG Foundation Models68

Self-Supervised Neuro Learning65

Strengths

S-JEPA (2024): JEPA-based cross-dataset EEG transfer — foundation model approach

MOABB: co-author of largest EEG BCI reproducibility benchmark

Gaps

Permanent INRIA position — low mobility, not actively on job market

…click to see all

Wei-Long Zheng

low hireability

Associate Professor@Shanghai Jiao Tong University

Previously: Postdoc Associate @ Massachusetts Institute of Technology

Shanghai, CN

Non-Invasive BCI92

Brain-Computer Interfaces92

Neural Signal Decoding88

Self-Supervised Neuro Learning88

EEG Foundation Models85

Strengths

Gram (2025): large-scale general EEG model — foundation model approach

EEG2Video (2024): decodes dynamic visual perception from EEG

Gaps

Tenured Associate Professor — low mobility, unlikely to leave academia

…click to see all

William Speier

low hireability

Assistant Professor@University of California, Los Angeles

Previously: Postdoctoral Scholar @ University of California, Los Angeles

Los Angeles, US

Brain-Computer Interfaces90

Non-Invasive BCI88

Neural Signal Decoding82

EEG Foundation Models78

Self-Supervised Neuro Learning65

Strengths

Mentality (2025): Mamba-based EEG foundation model — direct match

P300 speller BCI: 6+ papers over 2019–2025, non-invasive EEG

Gaps

Primary focus includes medical imaging (non-BCI) — BCI is a sub-line

…click to see all

Wojciech Samek

low hireability

Head of AI Department@Fraunhofer HHI

Brain-Computer Interfaces78

Neural Signal Decoding75

Non-Invasive BCI70

EEG Foundation Models15

Self-Supervised Neuro Learning10

Strengths

"Deep Learning for Whole-Brain Cognitive Decoding" (BCI 2022) — direct fMRI/brain decoding

"Interpretable Deep Neural Networks for Single-Trial EEG Classification" (2016)

Gaps

No EEG foundation model or large-scale neural pretraining work found

…click to see all

Xiang Zhang

low hireability

Assistant Professor@University of North Carolina at Charlotte

Previously: Postdoctoral Fellow @ Harvard University

Charlotte, US

Non-Invasive BCI90

Brain-Computer Interfaces88

Self-Supervised Neuro Learning88

Neural Signal Decoding85

EEG Foundation Models55

Strengths

Survey on deep learning non-invasive brain signals (2021, 518 citations)

TF-C self-supervised contrastive pretraining for time series (ICLR 2022, 446 citations)

Gaps

No evidence of large pretrained EEG foundation models specifically

…click to see all

Xiaodong Qu

low hireability

PhD student@The George Washington University

Non-Invasive BCI85

Brain-Computer Interfaces82

Neural Signal Decoding75

EEG Foundation Models20

Self-Supervised Neuro Learning5

Strengths

EEG4Home: end-to-end EEG BCI with personalization loop (HCI 2022)

Multi-class time continuity voting for EEG — Best Paper Award 2020

Gaps

No EEG foundation model or large-scale pretraining work

…click to see all

Xuan-Hao Liu

low hireability

Ph.D student@Shanghai Jiao Tong University

Previously: M.S student @ Shanghai Jiao Tong University

Shanghai, CN

Neural Signal Decoding92

Brain-Computer Interfaces88

Non-Invasive BCI85

Self-Supervised Neuro Learning72

EEG Foundation Models48

Strengths

EEG2Video (NeurIPS 2024): decodes video from EEG — core neural decoding work

EEGMirror (ICCV 2025): self-supervised EEG model across montages and datasets

Gaps

Early-stage PhD (year 2 of program) — low hireability window

…click to see all

Yangxuan Zhou

low hireability

PhD student@Zhejiang University

Montreal, CA

EEG Foundation Models92

Non-Invasive BCI85

Neural Signal Decoding82

Brain-Computer Interfaces80

Self-Supervised Neuro Learning80

Strengths

CBraMod (ICLR 2025, 165 citations) — criss-cross transformer EEG foundation model

EEGMamba (2025, 20 citations) — EEG foundation model with Mamba architecture

Gaps

PhD program 2024–2027 — 2+ years from graduation, low near-term availability

…click to see all

Yannis Panagakis

low hireability

Senior Researcher@Archimedes

Previously: Research Fellow @ Imperial College London

Athens, GR

EEG Foundation Models92

Neural Signal Decoding80

Non-Invasive BCI78

Brain-Computer Interfaces78

Self-Supervised Neuro Learning32

Strengths

NeuroRVQ (2025): multi-scale EEG tokenization for generative brainwave models

Codebook-Based Brainwave Foundation Model (2025): direct EEG FM authorship

Gaps

Tenured professor at U Athens — historically low hireability

…click to see all

Yasuko Matsubara

low hireability

Professor@Osaka University

Previously: Associate Professor @ Osaka University

EEG Foundation Models72

Self-Supervised Neuro Learning65

Neural Signal Decoding55

Non-Invasive BCI25

Brain-Computer Interfaces20

Strengths

Sequential EEG Foundation Models — NeurIPS 2025 BrainBodyFM workshop

SplitSee: self-supervised single-channel EEG representation learning (2024)

Gaps

No BCI control or closed-loop interface work — clinical EEG analysis focus

…click to see all

Yasushi Sakurai

low hireability

Director, Artificial Intelligence Research Center@ISIR, Osaka University

Previously: Professor @ Kumamoto University

Osaka, JP

EEG Foundation Models78

Self-Supervised Neuro Learning72

Neural Signal Decoding65

Non-Invasive BCI35

Brain-Computer Interfaces15

Strengths

'Learning Structured Sleep Transitions with Sequential EEG Foundation Models' (NeurIPS 2025)

'Dynamic multi-channel EEG graph modeling for time-evolving brain network' (ICLR 2025)

Gaps

No end-to-end BCI system or motor imagery decoding work

…click to see all

Yawei Li

low hireability

Group Associate@ETH Zurich

Previously: Postdoctoral Researcher @ ETH Zurich

Zurich, CH

EEG Foundation Models85

Self-Supervised Neuro Learning65

Neural Signal Decoding30

Non-Invasive BCI25

Brain-Computer Interfaces15

Strengths

LUNA (NeurIPS 2025): topology-agnostic EEG foundation model

FEMBA: Mamba-based EEG foundation model — scalable pretraining

Gaps

Primary expertise is CV/image restoration — EEG is a secondary area

…click to see all

Yijun Wang

low hireability

Researcher@Institute of Semiconductors, Chinese Academy of Sciences

Previously: Assistant Project Scientist @ University of California, San Diego

Beijing, CN

Brain-Computer Interfaces95

Non-Invasive BCI90

Neural Signal Decoding85

EEG Foundation Models20

Self-Supervised Neuro Learning15

Strengths

h=60 — decades of high-impact BCI research at CAS

Decoding Natural Images from EEG for Object Recognition (2024)

Gaps

No foundation model or SSL pretraining work visible

…click to see all

Yi Lin

low hireability

PhD student@National University of Singapore

Previously: MS student @ National University of Singapore

Non-Invasive BCI70

Brain-Computer Interfaces70

Neural Signal Decoding50

Self-Supervised Neuro Learning40

EEG Foundation Models35

Strengths

BrainHarmonix (NeurIPS 2025): first multimodal brain foundation model on fMRI + sMRI

SSVEP-based BCI (IROS 2021): non-invasive EEG control of humanoid robot

Gaps

BrainHarmonix uses fMRI/MRI — not EEG or EEG foundation models specifically

…click to see all

Yueming Wang

low hireability

Student Internship@University of California, Berkeley

Zhejiang, CN

Brain-Computer Interfaces95

Neural Signal Decoding90

Non-Invasive BCI65

Self-Supervised Neuro Learning50

EEG Foundation Models45

Strengths

MindGPT (2023): non-invasive brain-to-visual decoding — direct query match

ECoG gesture decoding via RNN (2018, 61 cit) — early neural decoding pioneer

Gaps

Primarily invasive/intracortical BCI — non-invasive work is a minority of output

…click to see all

Zheng Chen

low hireability

Assistant Professor@Osaka University

Previously: Postdoctoral Researcher @ Osaka University

Osaka, JP

EEG Foundation Models92

Neural Signal Decoding82

Self-Supervised Neuro Learning80

Non-Invasive BCI52

Brain-Computer Interfaces35

Strengths

'Learning Structured Sleep Transitions with Sequential EEG Foundation Models' — NeurIPS 2025

'Tokenizing Single-Channel EEG with Time-Frequency Motif Learning' — NeurIPS 2025 TS4H

Gaps

No end-to-end BCI control loop work — clinical/diagnostic focus, not motor intent decoding

…click to see all

Zhengyu Ma

low hireability

Associate Professor@Peng Cheng Lab

Previously: Postdoc @ Northwestern University

Neural Signal Decoding78

EEG Foundation Models72

Self-Supervised Neuro Learning72

Non-Invasive BCI68

Brain-Computer Interfaces65

Strengths

EEG-to-text decoding: contrastive masked autoencoder pretraining (2024)

Brain Auditory Attention Detection: SM-Former spiking transformer (2025)

Gaps

Associate Professor in CN national lab — low mobility, stable academic role

…click to see all

Zhenxi Song

low hireability

Associate Professor@Harbin Institute of Technology, Shenzhen

Previously: PhD student @ Tianjin University

Shenzhen, CN

Neural Signal Decoding88

Non-Invasive BCI85

Brain-Computer Interfaces85

Self-Supervised Neuro Learning80

EEG Foundation Models75

Strengths

BrainECHO (ACL 2025): semantic brain-to-text decoding, VQ spectrogram

SSVEP-BiMA (ICASSP 2025): core non-invasive SSVEP BCI system

Gaps

Associate Professor — low likelihood of leaving academic post

…click to see all

Ziquan Wei

low hireability

PhD candidate@University of North Carolina at Chapel Hill

Previously: Pre-doc Fellow Trainee @ University of North Carolina at Chapel Hill

Chapel Hill, US

Self-Supervised Neuro Learning70

Neural Signal Decoding40

EEG Foundation Models35

Non-Invasive BCI25

Brain-Computer Interfaces25

Strengths

BrainMoE: brain foundation model via MoE joint embedding (NeurIPS 2025)

Large Connectome Model: fMRI foundation model with multitask pretraining (AAAI 2026)

Gaps

fMRI/connectome focus — no EEG or BCI-specific work found

…click to see all

Ziyi Ye

low hireability

Assistant Professor@Fudan University

Previously: PhD student @ Tsinghua University

Shanghai, CN

Brain-Computer Interfaces92

Non-Invasive BCI85

Neural Signal Decoding85

EEG Foundation Models72

Self-Supervised Neuro Learning48

Strengths

PhD dissertation: Brain Computer Interface for Information Retrieval

'Generative language reconstruction from brain recordings' — Comm. Bio. 2025

Gaps

Newly appointed AP at Fudan — unlikely to leave academic track

…click to see all

Runs

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