Brain computer interface, brain foundation models, EEG foundation model, neural…

failed62 qualified1 runApr 27, 8:18 PMbrain-computer-interface-brain-foundation-models-eeg-foundat-1777321119

Parsed4 topics · Hybrid · US or EU

Generating seed nodes

0 proposed

Explored 0 queries

0/0 done

Expanding nodes

queued

Qualifying candidates

queued

Qualified Candidates (34)

Alessandro Marin Vargas

high hireability

Postdoctoral Scholar@Stanford University

Previously: PHD Graduate Student @ Ecole polytechnique fédérale de Lausanne

San Francisco, US

Postdoc at Stanford NPTL (Neural Prosthetics Translational Lab) — core expertise is Brain-Machine Interface, Neural Decoding, and Computational Neuroscience. 2025 papers on imitation learning for motor cortex decoding and sensorimotor cortex representations directly relevant to BCI/neural decoding query. h_index 7
Based in Palo Alto, US
Hireability: HIGH — postdoc at Stanford (NPTL) working on BCI, likely 1-2 years into postdoc and on the academic/industry job market

Anders Gjølbye

high hireability

PHD Fellow@DTU Compute

Previously: Co-Founder & Board Member @ Copenhagen MedTech

Copenhagen, DK

Directly relevant EEG researcher at DTU Compute
Authored 'SPEED: Scalable Preprocessing of EEG Data for Self-Supervised Learning' (2024, IEEE MLSP) — essentially EEG foundation model preprocessing — and 'Concept-based Explainability for an EEG Transformer Model' (2023)
Research expertise spans Deep Learning, EEG, Signal Processing
Based in Copenhagen, EU
Hireability: HIGH — DTU profile now shows 'not affiliated with DTU', suggesting recent PhD completion/transition; NeurIPS 2025 paper still used DTU email, placing graduation around late 2025/early 2026. Prime transition window

Christina Sartzetaki

high hireability

PhD Candidate@University of Amsterdam

Previously: Machine Learning Engineer @ DeepLab

Amsterdam, NL

PhD candidate at University of Amsterdam with research expertise explicitly in Brain Computer Interfaces, EEG Decoding, and NeuroAI
Published EEG fine-tuning paper (IEEE 2023) and ICLR 2025 paper on neural alignment; recent active GitHub commits (April 2026)
Located in Amsterdam, NL (EU)
Hireability: HIGH — papers span 2022–2025 suggesting ~4th-5th year PhD student in prime final-year transition window

Deeksha M Shama

high hireability

Graduate Research Assistant@Johns Hopkins University

Previously: Research Intern - Brain Computer Interfaces @ Microsoft

Boston, US

ECE PhD student at JHU with a paper on 'Cognitive Load Estimation Using Brain Foundation Models and Interpretability for BCIs' accepted to ICASSP 2026 (from Microsoft Research internship) — directly on-query for BCI, brain foundation models, and EEG
Additional EEG work includes SzXAI (LLM-EEG alignment, MICCAI 2025) and DeepSOZ (multichannel EEG seizure localization)
Based in Cambridge, MA (US)
Hireability: HIGH — renamed CV to 'resume' in Dec 2025 (industry job search signal), MSFT Research intern paper just accepted Jan 2026, active website updates suggest final-year PhD

Dulhan Jayalath

high hireability

PhD Student@University of Oxford

Previously: Research Scientist Intern @ Meta

Oxford, GB

Direct BCI/neural decoding researcher at Oxford's Neural Processing Lab — works on brain-to-text, speech decoding from MEG/non-invasive neuroimaging, and scalable BCIs
ICML 2025 paper 'The Brain's Bitter Lesson' on scaling speech decoding with self-supervised learning is exactly on-query
Strong industry track record: internships at Meta (open-ended RL), Google DeepMind (long-context reasoning), Arm, Speechmatics
Location: Oxford, UK (EU-adjacent, note: not technically EU post-Brexit)
Hireability: HIGH — AWS-funded AIMS PhD started ~2022, in year 4 (final year); website copyright 2022-2026 corroborates timeline. Multiple industry internships signal strong openness to industry roles

Hao Fang

high hireability

Postdoctoral Scholar@University of Washington

Previously: Postdoctoral Scholar @ University of Central Florida

Seattle, US

Postdoc at UW with research expertise directly in Neural Decoding and Brain-Computer Interfaces. 2025 papers include SPINT (intracortical motor decoding transformer) and EEG-based emotion recognition via Riemannian manifolds — core to the BCI/EEG foundation model query
Based in Seattle, US
Hireability: HIGH — 19 months into postdoc, LinkedIn explicitly states openness to new opportunities and active search for industry research scientist positions

Igor Carrara

high hireability

Direct BCI/EEG researcher — PhD at INRIA/Université Côte d'Azur on motor imagery EEG classification using Riemannian geometry; 5 papers on BCI/EEG decoding (2023-2024), core contributor to MOABB (16+ commits)
EU (Sophia Antipolis, France)
Listed as 'Former student' on INRIA CRONOS team page, indicating recent PhD completion
Hireability: HIGH — recently completed PhD (2024-2025 likely), still actively contributing to MOABB as of Feb 2026, prime transition window post-PhD

Jingyuan Li

high hireability

Applied Scientist@Amazon

Previously: Research Internship @ Microsoft

Seattle, US

5th-year PhD candidate at UW NeuroAI Lab (Prof
Shlizerman) working directly on neural decoding and BCI: brain-to-text decoding (ICLR 2025), intracortical motor decoding (SPINT 2025), and neural activity forecasting (NeurIPS 2023)
Pinned repos include EEG-Datasets and neural_seq_decoder
In Seattle, US
Hireability: HIGH — 5th-year PhD student in prime transition window; Amazon Applied Scientist role (likely internship) shows industry-readiness

Joel Ye

high hireability

PhD Student@Carnegie Mellon University

Previously: Software Engineer Intern @ Microsoft

Pittsburgh, US

Core BCI and neural decoding PhD researcher at CMU — builds large neural data foundation models (ndt3: 'Pretrained decoders for intracortical BCI'; context_general_bci: 'Towards large neural data models'). 2025 paper: 'A Generalist Intracortical Motor Decoder'; 2024: FALCON neural decoding benchmark; 2023: NDT2 multi-context pretraining for neural spiking activity
Pittsburgh, US
Hireability: HIGH — ~5 years into CMU PhD (Neural Computation program, first papers 2021), squarely in the final-year transition window with no 'settled into new role' signals

Nicolas Guazzelli Kunigk

high hireability

Graduate Student Researcher@University of Pittsburgh

Previously: Undergraduate Research Assistant @ UF Herbert Wertheim College of Engineering

Pittsburgh, US

PhD student at RNEL (Univ. of Pittsburgh) under Jennifer Collinger
Co-author of NDT3 ('A Generalist Intracortical Motor Decoder'), a 350M-param intracortical BCI foundation model trained on 2000 hours of neural data from 30+ monkeys and humans across 10 labs — directly on-target for brain foundation models and neural decoding
Multiple BCI papers in Journal of Neural Engineering (motor imagery, microstimulation)
H-index 5
Hireability: HIGH — BS from UF in 2020, ~5-6 years into PhD program, very likely in final year and prime job-market transition window

Adam Smoulder

medium hireability

Postdoctoral Researcher@Boston University

Previously: Doctoral Student @ Carnegie Mellon University

Boston, US

Co-author of NDT3 (Neural Data Transformer 3), a 350M-parameter foundation model for motor decoding from intracortical microelectrodes, pretrained on 2000 hrs of neural population data from 30+ monkeys/humans across 10 labs
PhD CMU 2024 (Biomedical Engineering), now postdoc at Boston University working on motor and cognitive neuroscience
US-based, not a professor
Hireability: MEDIUM-HIGH — ~1.5 years into postdoc (PhD 2024), within typical transition window for industry move

alexandre barachant

medium hireability

Pioneer BCI/EEG researcher: creator of pyRiemann (Riemannian geometry for EEG), 89 commits on MOABB, won 6 intl brain signal competitions including Kaggle Grasp-and-Lift EEG
PhD Signal Processing, based in New York, NY
Recent BCI activity dropped off ~2021 (latest public BCI commits); most recent GitHub activity (June 2025) is home automation
Hireability: MEDIUM — current employer unknown, reduced public BCI activity since 2021, but no negative signals and deep EEG/neural decoding expertise aligns directly with the search query

Bruno Aristimunha

medium hireability

AI Research Scientist@Yneuro

Previously: Research Engineer / Joint PhD Student @ Inria

Paris, FR

PhD student at Université Paris-Saclay specializing in EEG decoding and brain foundation models
Core contributor to braindecode (EEG deep learning) and MOABB (BCI benchmarks)
Authored 'General-Purpose Brain Foundation Models for Time-Series Neuroimaging Data' (2024) and 'EEG Foundation Challenge: From Cross-Task to Cross-Subject EEG Decoding' (2025)
Currently AI Research Scientist at Yneuro in Paris (EU)
Hireability: MEDIUM — employed at Yneuro (small startup with 'We're hiring!' on LinkedIn), still active PhD student at Paris-Saclay with CV updated April 2026, suggesting career motion but recent role start

Cédric Rommel

medium hireability

Research Scientist@Meta

Previously: AI Research Scientist @ Valeo

Paris, FR

Research Scientist at Meta AI (Paris, EU) with strong EEG/neural decoding background: lead EEG data augmentation paper (111 citations, Journal of Neural Engineering), CADDA for EEG at ICLR 2022 (54 citations), and active braindecode contributor (deep learning for EEG/ECG/MEG decoding)
Website explicitly lists 'AI for neural interfaces' as primary research focus
Not a professor — matches query seniority criteria
Hireability: MEDIUM — estimated 2-4 years at Meta (within transition window), no explicit job search signals, but recent publications have shifted toward 3D pose estimation rather than neural interfaces

Chenggang Chen

medium hireability

Research Associate@Johns Hopkins University

Previously: Postdoctoral Research Scientist @ Johns Hopkins University

Baltimore, US

Postdoc at Johns Hopkins directly working on neural decoding and brain-machine interfaces — NeurIPS 2024 NER paper on long-term neural decoding from M1/PMd (86-97% variance explained), and NMR 2025 on manifold-aligned BCI motor decoding across 68 sessions
Research expertise explicitly includes 'brain-machine interfaces' and 'neural decoding'
Baltimore, US
Not a professor (Research Associate/Postdoc)
Hireability: MEDIUM — active postdoc with recent 2024-2025 papers, no explicit open-to-work signals, but postdocs at JHU are typically in a transition window

Christos Chatzichristos

medium hireability

Scientific Advisor@AINIGMA Technologies

Previously: Postdoctoral Researcher @ Janssen

Leuven, BE

Strong EEG/fMRI researcher (h_index 16) specializing in multimodal neural signal fusion and tensor decompositions for neural data
Research expertise directly matches query: EEG, fMRI, model fusion, neural signal foundation models
Postdoc at KU Leuven (STADIUS group) + Scientific Advisor at AINIGMA Technologies (EEG neurotechnology startup), located in Leuven, Belgium (EU)
Source tagged as 'professor' in DB discovery node but actual role is postdoc/scientific-advisor (not a professor)
Hireability: MEDIUM — postdoc stage typical transition window, but already has industry advisory foothold at EEG startup; no active job-seeking signals detected

Denis-Alexander Engemann

medium hireability

Biomarker & Experimental Medicine Leader@Roche

Previously: Researcher @ Inria

Basel, CH

Strong EEG foundation model researcher (h-index 29)
Directly relevant papers: self-supervised representation learning on EEG (2019, 101 cites), uncovering clinical EEG structure with SSL (2021, 300 cites), and 2025 work on learnable wavelets for EEG biomarkers (GREEN architecture)
Core MNE-Python contributor; pinned repo coffeine targets predictive M/EEG pipelines
Based in Basel, Switzerland (EU), industry employee at Roche — not a professor
Hireability: MEDIUM — 'Biomarker & Experimental Medicine Leader' at Roche, no open-to-work signals detected, no LinkedIn history changes, website last updated ~13 months ago; tenure at current role unclear but within plausible transition window

Diana C Dima

medium hireability

Postdoc@Johns Hopkins University

Baltimore, US

EEG/MEG neural decoding specialist (multivariate pattern analysis, EEG-fMRI fusion) focused on cognitive neuroscience; her 2024 paper on transformer-brain representational alignment is adjacent to brain foundation models
Primary work is decoding visual/action representations for cognitive neuroscience rather than BCI or building EEG foundation models specifically
Baltimore, US (JHU postdoc)
Hireability: MEDIUM — 7-year postdoc (2019-present) at JHU, unusually long tenure suggesting possible academic career track; no explicit job-seeking signals found

Furkan Ozcelik

medium hireability

CerCo, University of Toulouse III Paul Sabatier

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

Toulouse, FR

Core neural decoding researcher with landmark Brain-Diffuser paper (176 cites, Scientific Reports 2023) reconstructing images from fMRI using latent diffusion models, plus multi-subject brain decoding generalization work (2024)
Research expertise is Neural Decoding, Deep Learning, Computer Vision — strong fit for brain foundation models and neural decoding search
Based in Toulouse, FR (EU ✓)
Not a professor
Hireability: MEDIUM — PhD completed 2023 at Toulouse (VanRullen lab), likely postdoc at CerCo/CNRS ~3 years post-PhD; no explicit open-to-work signals but postdoc window

Hubert Banville

medium hireability

AI Research Scientist@Meta

Previously: Research Scientist @ Interaxon

London, GB

Directly on-target: leading EEG/BCI researcher at Meta FAIR London. 1,527-citation systematic review on deep learning for EEG, self-supervised EEG representation learning (foundation model-style, 300 citations), and active 2025 work on brain decoding scaling laws, brain-to-text, and fMRI decoding
GitHub pinned repos are all EEG/BCI
Note: location is London, UK (not strictly US/EU per query)
Hireability: MEDIUM — ~3-4 years at Meta FAIR, active publishing (no gap), no open-to-work signals detected

Huy Phan

medium hireability

Research Scientist@Meta

Previously: Senior Research Scientist @ Amazon

Paris, FR

Strong EEG foundation model researcher — co-authored 'STELAR: Dual-space training EEG Foundation Models for Transferable Representations' (2025) and MIN2Net for motor imagery EEG classification (BCI)
H-index 36, extensive EEG/biosignal decoding work
Research Scientist at Meta Paris (EU, matches location)
Not a professor
Recent Meta work includes audio AI, indicating some focus shift away from EEG
Hireability: MEDIUM — Research Scientist at Meta with no 'open to work' signals, no LinkedIn changes, but within a reasonable tenure window; worth reaching out given strong EEG foundation model alignment

Iris A.M. Huijben

medium hireability

Postdoctoral researcher@Universiteit Maastricht

Previously: Research Intern @ Meta

Postdoc at Maastricht Univ (NL/EU)
Research directly spans EEG foundation models, self-supervised learning for sleep EEG (SOM-CPC at ICML 2023), and biosignal processing; co-authored 'Sleep EEG foundation models reveal within-stage microstructure' and presented EEG sleep work at EMBC 2024
Contributor to TorchEEG library
Former intern at Qualcomm AI and Meta FAIR
H-index 14
Not a professor
Hireability: MEDIUM — postdoc likely 1-2 years in, industry internship history (Qualcomm, Meta FAIR) shows openness to industry; co-instructing at UAB (Birmingham, US) in Sep 2025 signals US engagement and active career exploration

Konstantinos Barmpas

medium hireability

Machine Learning Engineer@Cogitat

Previously: PhD Candidate @ Imperial College London

London, GB

Direct EEG/BCI foundation model researcher — published 'Are Large Brainwave Foundation Models Capable Yet?' at ICML 2025, 'LaBraM++' at NeurIPS 2025 Foundation Models workshop, and actively building NeuroRVQ (multi-scale EEG tokenization for generative brainwave models)
Postdoc at Imperial College London + ML Engineer at Cogitat (EEG/BCI startup)
H-index 7, based in London (GB)
Hireability: MEDIUM — postdoc status is an inherent transition window; cv_update in April 2025 and latest GitHub commit March 2026 signal active career motion

Marco Vilela

medium hireability

Lead Neurotech Research Engineer@Analog Devices

Previously: Associate Director @ Takeda

Boston, US

Lead Neurotech Research Engineer at Analog Devices (Boston)
Deep BCI and EEG expertise: built real-time BCI decoders at Brown University (LSTM/Kalman), led ML for EEG endpoint development at Takeda (narcolepsy, ALS), developed single-cell RNA foundation models as Associate Director at Takeda, now developing AI/ML where silicon interfaces with biological systems at Analog Devices
BCI decoder LSTM paper (56 cites), intracortical BCI home-use paper (178 cites)
Industry employee (not professor), h-index 15
Hireability: MEDIUM — started at Analog Devices Nov 2024 (~17 months), open_to_work: false, but historically switches roles every 2-3 years and may be approaching next transition window

Michael Hersche

medium hireability

Research Scientist@IBM

Previously: Research Associate @ IBM

Zurich, CH

IBM Research Scientist at Zurich working directly on EEG/iEEG foundation models: BrainCodec (neural compressor for EEG, ICLR 2025) and MVPFormer (generative brain foundation model for iEEG, 2025)
Multiple high-citation EEG/BCI papers (h-index 15, including EEG-TCNet with 351 citations)
Research expertise spans brain-computer interfaces, neural decoding, and hyperdimensional computing
Employee (not professor), Switzerland-based (EU-adjacent, not China)
Hireability: MEDIUM — Research Scientist at prestigious IBM Zurich Research; very active publication record through 2025-2026 but no open-to-work signals detected from pipeline signals or GitHub

Robin Tibor Schirrmeister

medium hireability

Researcher@Medical Center - University of Freiburg

Previously: Researcher @ Meta

Freiburg, DE

Core EEG/BCI deep learning researcher at Freiburg Medical Center (h-index 16)
Published EEG-CLIP (2025), 'Deep learning for brain-signal decoding from EEG' (2024), CoordConformer for heterogeneous EEG decoding (2024), EEG scaling benchmarks, and created the widely-used braindecode library
Research spans neural decoding, EEG pathology classification, and foundation-model-style pretraining for brain signals — directly on target
Germany (EU), not a professor
Hireability: MEDIUM — long-tenure researcher at university medical center with no open-to-work signals detected, but actively publishing recent EEG/BCI work through Jan 2025; within typical transition window for industry move

Trung Le

medium hireability

Visiting Researcher@Allen Institute

Previously: Research Scientist Intern @ Meta

Seattle, US

Strong BCI/neural decoding researcher at UW NeuroAI Lab — first author on STNDT (NeurIPS 2022, 44 citations), Brain-to-Text Decoding (2024), and SPINT intracortical motor decoding (2025); also on Brain-to-Text Benchmark '24
Research squarely in neural population modeling, neural decoding, and brain-computer interfaces
Seattle, US
Not a professor — PhD student
Hireability: MEDIUM — currently Visiting Researcher at Allen Institute while completing PhD at UW, suggesting transition phase but no explicit job market signals found

Xuan Ma

medium hireability

Researcher@Northwestern University

Strong intracortical BCI and neural decoding researcher at Northwestern University (US)
Co-author on 'Stabilizing brain-computer interfaces through alignment of latent dynamics' (2025, 79 citations), 'A Generalist Intracortical Motor Decoder' (2025) — directly relevant to brain foundation models, and FALCON few-shot neural decoding benchmark (2024). 'Using adversarial networks to extend BCI decoding accuracy over time' (2023, 45 citations)
Listed as 'Researcher' at Northwestern, not a professor
Note: GitHub account XMaBio in the DB is a different person (Chinese plant biologist at Tianjin Normal University)
Hireability: MEDIUM — long-term Researcher at Northwestern actively publishing through 2025; no pipeline signals of job-seeking, but peer co-author Fabio Rizzoglio is a postdoc in the same lab suggesting a postdoc-level role in transition window

Yohann Benchetrit

medium hireability

Researcher@Meta

Core brain decoding researcher at Meta FAIR (Paris, EU)
Published multiple directly relevant papers: 'Brain decoding: toward real-time reconstruction of visual perception' (ICLR 2024, MEG-based), 'Scaling laws for decoding images from brain activity' (EEG/MEG/fMRI across 84 subjects), 'Decoding individual words from non-invasive brain recordings' (EEG/MEG, 723 participants), and TRIBE (trimodal brain encoder for whole-brain fMRI)
GitHub repos include brain-diffuser, WAVE (fMRI foundation models), and mind-vis
Not a professor — employee at FAIR
Hireability: MEDIUM — actively publishing in exactly this domain (2024-2025 papers), no job-seeking signals detected; ~2-3 years at Meta FAIR within typical transition window

Alexandre Gramfort

low hireability

AI/ML Research Scientist@Meta

Previously: Senior Research Scientist @ Inria

Paris, FR

Creator of MNE-python (leading MEG/EEG Python library) and braindecode (deep learning for EEG/ECG/MEG decoding); Senior Research Scientist Manager at Meta Reality Labs (Paris) working on ML for surface EMG signal decoding — directly on-point for BCI and neural decoding
H-index 76, extensive EEG foundation model and neural decoding papers
EU (Paris)
Hireability: LOW — very senior position at Meta (SRSM + concurrent Inria Research Director), no open-to-work signals, no pipeline changes detected

Andrea Alamia

low hireability

Researcher@CNRS

Previously: Postdoctoral Researcher @ CNRS

Toulouse, FR

Computational neuroscientist at CNRS Toulouse with deep EEG expertise — cortical traveling waves, predictive coding, EEG-fMRI (h-index 20)
Strong overlap with EEG foundation models and neural decoding (EU location)
Hireability: LOW — permanent CNRS researcher running own lab with M1/M2 students; no open-to-work signals and website shows they are recruiting others

Cole Lincoln Hurwitz

low hireability

AI Architect, Core AI@IBM

Previously: Postdoctoral Researcher @ Columbia University

Boston, US

Strong match — co-creator of SpikeInterface, built IBL_MtM_model (IBL brain foundation model, pinned on GitHub), published 'Neural Encoding and Decoding at Scale' (2025) and 'Towards a Universal Translator for Neural Dynamics' (2024)
PhD Edinburgh + Columbia postdoc (Paninski lab, IBL member) in computational neuroscience; deep expertise in neural decoding, spike sorting, and foundation modeling for neural data
Now AI Architect at IBM Core AI in Cambridge MA
Hireability: LOW — joined IBM ~Dec 2025 (~5 months ago), currently building AgentOps product; new hire window applies

Reinmar J Kobler

low hireability

Research Scientist@Meta

Previously: Visiting Scientist @ RIKEN

Paris, FR

Research Scientist at Meta Reality Labs (Paris, FR) doing applied ML on bio/neural timeseries
Core EEG/BCI expertise: h-index 18, 842 citations, ICLR 2025 paper on EEG unsupervised domain adaptation (SPDIM), NeurIPS 2022 on SPD batch normalization for BCI
PhD TU Graz 2020, postdoc RIKEN 2020-2022
Hireability: LOW-MEDIUM — joined Meta January 2025 (~1.2 yrs in role), no open-to-work signals, still holds concurrent ATR research position in Japan

Vernon Lawhern

low hireability

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

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

Washington DC-Baltimore Area, US

Creator of EEGNet (2016), the foundational compact CNN for EEG-based BCI (h-index 24, thousands of citations)
Active in neural decoding research including 'Decoding Neural Activity to Assess Individual Latent State in Ecologically Valid Contexts' (2023) and BEETL EEG transfer learning competition (2022)
Senior Research Scientist at Army Research Laboratory, Washington DC, US — employee not professor
Hireability: LOW — 9+ years at government research lab, no LinkedIn profile changes and no website activity signals indicating job transition

Runs

#1failed0 qualified / 0 foundApr 27, 8:18 PMFunctionTimeoutError: Task's current input in-01KQ8BGHAATNRAXM4DSCVD6B2G:1777323230575-0 hit its timeout of 2100s