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Researchers based in the US who have done work at the intersection of EEG and De…

completed24 qualified1 runMar 4, 6:19 AMresearchers-based-in-the-us-who-have-done-work-at-the-inters

Qualified Candidates (24)

AV

Alessandro Marin Vargas

high hireability

Postdoctoral Scholar@Stanford University

Previously: PHD Graduate Student @ Ecole polytechnique fédérale de Lausanne

San Francisco, US

  • Postdoc at Stanford Neurosurgery with explicit focus on brain-machine interfaces and neural population dynamics; 2025 publication on population response geometry in digital twins of mouse visual cortex shows active, cutting-edge BMI+deep-learning work
  • DB hireability HIGH; LinkedIn data present but no history changes, meaning no recent job transition detected — likely in second or third year of postdoc and approaching job market
  • Core BCI + deep learning + computational neuroscience intersection
  • Hireability: HIGH — Stanford postdoc in BMI, h=7 and publishing actively, plausibly on industry job market in 2025-2026
BZ

Bingzhao Zhu

high hireability

PhD student@Cornell University

  • Cornell PhD (Applied & Engineering Physics, Mahsa Shoaran lab) specializing in neural interfaces, BCI, and ML for neural signal classification — exact intersection. h=13 as a PhD student is exceptional and signals prolific output on hardware-software neural interface co-design (NeuralTree SoC, closed-loop neural prosthetics)
  • Cornell commencement 2024 program suggests likely graduated or near graduation, making him immediately available
  • DB hireability HIGH
  • Hireability: HIGH — exceptional h-index for a PhD student, likely graduated 2024, now on the job market for industry or academic BCI roles
HF

Hao Fang

high hireability

Postdoctoral Scholar@University of Washington

Previously: Postdoctoral Scholar @ University of Central Florida

Seattle, US

  • UW Orsborn lab postdoc explicitly stating on website: 'I am looking for a full-time research scientist in the industry' — the strongest possible hireability signal
  • Research covers adaptive BCI control algorithms, consistent neural signal decoding with ML, and FPGA real-time closed-loop BCI, which is a precise match for BCI+deep-learning
  • Website had position_update tracked changes May 2025
  • LinkedIn data present, DB hireability HIGH
  • Hireability: HIGH — explicitly self-declared open to industry RS roles, BCI/neural-decoding is his primary specialty, UW pedigree is strong
IH

Iris A.M. Huijben

high hireability

Postdoctoral researcher@Universiteit Maastricht

Previously: Research Intern @ Meta

NL

  • PhD defended cum laude Oct 2024 (TU/e) on 'Uncovering sleep structure through discrete representation learning' — self-supervised EEG representation learning is a direct match for the BCI+EEG+deep-learning query
  • Now postdoc at Maastricht; November 2025 publication in Journal of Neuroscience Methods confirms active output. h=14 cum laude PhD is a very strong signal
  • DB hireability HIGH
  • Location is Netherlands but no explicit relocation requirement in query
  • Hireability: HIGH — fresh postdoc post cum-laude PhD, excellent track record in EEG self-supervised learning, likely open to strong industry or academic opportunities
SD

Simon Dahan

high hireability

Postdoc@Meta

Previously: Postdoc @ Université de Lausanne

San Francisco, US

  • KCL PhD student (MeTriCs Lab, Emma Robinson + Daniel Rueckert) now postdoc at Meta — the key new evidence is his GitHub: repo 'seegnificant' is codebase for 'Neural decoding from stereotactic EEG: accounting for electrode variability across subjects' published at NeurIPS 2024
  • This is direct EEG neural decoding work that was missed in the original review
  • He also forked 'awesome-brain-fm' (brain foundation models) and 'surface-masked-autoencoders', showing active engagement with brain deep learning
  • Primary KCL PhD work is brain MRI/fMRI surface analysis (neonatal cortical development via vision transformers), which qualifies under the broadened criteria (brain MRI/fMRI explicitly counts)
  • OpenReview shows 'Postdoc, Facebook' — LinkedIn confirms Meta
  • Pipeline signals: LinkedIn data present, no change history detected, no website activity
  • DB hireability HIGH
  • Hireability: HIGH — NeurIPS 2024 EEG neural decoding paper + brain MRI PhD + Meta postdoc is a strong combination; postdoc at Meta typically means actively building industry credentials and open to opportunities
YZ

Yizi Zhang

high hireability

PhD student@Columbia University

  • Columbia Zuckerman Institute PhD working on BCI, neural decoding, and foundation models for neural data (NEDS — Neural Encoding and Decoding at Scale); published in Neuron Oct 2025 on exploiting trial correlations for neural decoding
  • The foundation model angle for neural data is exactly the frontier BCI+deep-learning intersection
  • No LinkedIn or pipeline signals (no data in DB), but query-level fit is strong
  • DB hireability HIGH
  • Graduation estimated 2025-2026
  • Hireability: HIGH — Columbia PhD in BCI/neural-decoding/foundation-models, DB-rated HIGH, actively publishing through late 2025
YW

Yule Wang

high hireability

Graduate Research Assistant@Georgia Institute of Technology

Previously: Research Scientist Intern @ Meta

Atlanta, US

  • BrainML 4th-year PhD (Fall 2022) under Anqi Wu, publishing diffusion models for neural population dynamics — directly foundational for BCI signal modeling
  • NeurIPS 2023 spotlight, NeurIPS 2024, ICLR 2026, three COSYNE 2026 posters; RS internship at Meta Reality Labs (Summer 2025) proves industry fit
  • Website shows 37 tracked changes with a March 2025 position_update, actively maintained
  • GitHub confirms NeurIPS 2023 and 2024 repos plus ICLR 2026
  • Hireability: HIGH — graduating 2026/2027, strong industry signal from Meta internship, DB rating confirmed HIGH, h=6 and rising rapidly
DE

Denis-Alexander Engemann

medium hireability

Biomarker & Experimental Medicine Leader@Roche

Previously: Researcher @ Inria

Basel, CH

  • h=29 with deep EEG/MEG/MRI ML expertise including Riemannian geometry, brain age modeling, and disorders of consciousness; now leading biomarker science at Roche Pharma
  • While already in industry, this is the senior/experienced profile bucket — someone who could lead a team in BCI or neural signal ML
  • Website has 2 tracked paper changes Mar-Apr 2025
  • OpenReview confirms Roche affiliation
  • DB hireability MEDIUM (appropriately — senior industry role)
  • No LinkedIn change history, stable at Roche
  • Hireability: MEDIUM — strong EEG/ML depth (h=29) but stably placed at Roche; opportunistic outreach only, not a hot lead
DZ

Dongdong Zhou

medium hireability

Postdoc@Dalian University of Technology

Previously: PhD student @ University of Jyväskylä

CN

  • PhD completed at University of Jyvaskyla, Finland (March 2023) — confusion resolved: he is now a postdoc at Dalian University of Technology (confirmed by ResearchGate profile showing 'PostDoc Position' at DUT)
  • His EEG sleep staging work is a clear match under the broadened criteria (clinical EEG explicitly counts): developed SingleChannelNet (automatic sleep stage classification from single-channel raw EEG, Biomedical Signal Processing and Control 2022), published on class imbalance in sleep staging (IEEE TIM 2022), LightSleepNet (IEEE EMBC 2021), and interpretability-focused sleep stage classification via Layer-Wise Relevance Propagation (2024)
  • GitHub confirms: SingleChannelNet repo (1 star) and deepsleepnet fork, both raw single-channel EEG deep learning
  • Methods span CNN, LSTM, Transformer, and time-frequency analysis for brain EEG signals
  • Pipeline signals: no LinkedIn, no website activity in DB
  • DB hireability HIGH (possibly elevated)
  • Location is China (DUT postdoc), which may limit near-term US-based hiring
  • Hireability: MEDIUM — strong technical EEG/deep-learning fit (clinical EEG qualifies under broadened criteria), h=8 as a recent PhD (2023) is reasonable; China-based placement limits immediate availability but postdocs are transitional roles
HP

Huy Phan

medium hireability

Research Scientist@Meta

Previously: Senior Research Scientist @ Amazon

Paris, FR

  • Research Scientist at Meta Reality Labs Paris (previously Amazon Alexa/AGI, QMUL Lecturer, Alan Turing Fellow) with h=36 — the highest h-index in this candidate batch
  • EEG sleep staging work directly qualifies under the broadened criteria: authored XSleepNet, SeqSleepNet (IEEE-EMBS Best Paper Award 2019-20), SleepTransformer, L-SeqSleepNet, and a survey on 'Automatic Sleep Staging of EEG Signals' — a substantial body of brain EEG deep learning work
  • GitHub has 55 repos including SleepTransformer (33 stars) and l-seqsleepnet (16 stars)
  • At Meta Reality Labs he works on AI modeling for surface EMG signals — biosignal and neural interface work adjacent to BCI
  • Meta had a NeurIPS 2025 demo on the noninvasive neuromotor wristband (sEMG)
  • Pipeline signals: LinkedIn data present, no change history, website 11 changes with most recent 47 days ago
  • DB hireability MEDIUM
  • Hireability: MEDIUM — senior RS at Meta with EEG sleep staging and sEMG background; stable at Meta but the biosignal/neural interface angle is highly relevant; EEG brain work clearly satisfies broadened criteria
JW

Jiyi Wang

medium hireability

Visiting Researcher@Slavakis Lab

Previously: Software Engineer Intern @ Narwal Robotics

Yokohama, JP

  • Just started ME PhD at GaTech (Spring 2026) advised by Anqi Wu; research on computational neuroscience, RL, and hippocampal replay — foundational for neural decoding and BCI model development
  • DB hireability is HIGH likely reflecting pre-PhD background; GitHub bio still shows Peking University undergrad, confirming this is very early-career
  • Website had 17 tracked changes through June 2025
  • Qualifying as a BrainML member; flag as long-horizon pipeline
  • Hireability: MEDIUM — DB shows HIGH but this is a brand-new PhD student (Spring 2026), not hiring-ready now; good candidate to track for internships or 2029-2030 graduation
JS

Joana Soldado-Magraner

medium hireability

Postdoctoral Research Associate@Carnegie Mellon University

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

Pittsburgh, US

  • CMU Neuroscience Institute postdoc (Byron Yu + Matthew Smith) working on intracortical BCIs, single neuron/MEA recordings, ML for neural data, and RNN-based computational models — directly relevant to BCI+deep-learning
  • Co-founder of CaMinA computational neuroscience program shows research leadership
  • No pipeline data (no LinkedIn in DB, no website changes)
  • DB hireability not set; estimating MEDIUM given senior postdoc status without explicit job search signals
  • Hireability: MEDIUM — strong BCI/intracortical background at CMU, mid-career postdoc; likely approaching faculty or industry job market but no explicit signals
KB

Konstantinos Barmpas

medium hireability

Machine Learning Engineer@Cogitat

Previously: PhD Candidate @ Imperial College London

London, GB

  • Imperial College postdoc + Cogitat ML Engineer (dual role since 2021) with PhD thesis 'Enhancing Motor-Imagery BCIs Through Deep Learning' — exact BCI+EEG+deep-learning match
  • Working on generative foundation models for biosignals (brainwave foundation models); MLSP 2025 paper on large brainwave model evaluation
  • Website has 41 tracked changes with most recent 10 days ago — the most actively maintained website in this batch, signaling high engagement
  • DB hireability MEDIUM
  • PhD defended no-corrections, 2nd place G-Research Imperial PhD Prize 2024
  • Hireability: MEDIUM — stably employed across two roles in BCI (postdoc + industry), but highly active and the parallel industry role signals openness to the right opportunity
PG

Peiliang Gong

medium hireability

Postdoctoral Researcher@Nanyang Technological University

Previously: Visiting Researcher @ A*STAR

Singapore, SG

  • NTU Singapore postdoc focusing on BCI, domain adaptation for EEG (cross-subject/cross-session generalization), and time-series foundation models — clear BCI+EEG+deep-learning match. h=10, website 26 changes with most recent 7 days ago (RECENT), LinkedIn detected location change Nanjing→Singapore (scrape Feb 2026) confirming recent move to NTU
  • Editorial board appointment and inviting collaborators suggests mid-career academic track
  • DB hireability MEDIUM
  • Hireability: MEDIUM — recently relocated to Singapore for postdoc, productive (h=10, website very active), but no explicit job search signal; open to collaboration
RS

Robin Tibor Schirrmeister

medium hireability

Researcher@Medical Center - University of Freiburg

Previously: Researcher @ Meta

Freiburg, DE

  • Founding contributor of braindecode (canonical deep-learning-for-EEG library), published the widely-cited 2017 deep CNN for EEG decoding paper; h=16
  • Currently at Tonio Ball's Neuromedical AI Lab at Freiburg (top BCI academic group), actively publishing in 2025 on EEG-CLIP and deep network interpretability for EEG
  • GitHub shows braindecode origin repos and mindwave mobile (EEG hardware)
  • LinkedIn shows Alpica (likely a side startup)
  • No explicit job search signal but the profile depth and lab prestige are strong
  • Hireability: MEDIUM — established EEG/BCI deep-learning researcher in Germany, worth reaching; no clear job search signal but high expertise fit
SK

Soon Ho Kim

medium hireability

postdoctoral fellow/visiting assistant professor@Georgia Institute of Technology

Previously: postdoctoral fellow @ Korea Institute of Technology Brain Science Institute

Atlanta, US

  • Postdoc/VAP at GaTech (School of Mathematics, mentored by Hannah Choi) with meaningful brain/neural signal work qualifying under the broadened criteria: develops mathematical models of neural computation, population activity inference, and brain state discovery
  • Published 'One-hot generalized linear model for switching brain state discovery' (ICLR 2024) and 'Neural information processing and computations of two-input synapses' (Neural Computation 2022) — both directly model neural signals
  • Research spans dendrite computation, neural population dynamics, inhibitory cell type heterogeneity in V1, and liquid state machine dynamics; 209 total citations, h=9 for a postdoc is solid
  • Pipeline signals: no LinkedIn history, no website activity, 1 GitHub repo (information theory)
  • VAP role at GaTech is temporary academic placement suggesting he will be on the job market
  • Hireability: MEDIUM — theoretical neuroscience is a clear brain/neural specialization under the broadened criteria; VAP positions typically lead to a job search within 1-2 years; worth reaching out
WL

Weihan Li

medium hireability

PhD student@Georgia Tech

Previously: MS student @ Zhejiang University

US

  • BrainML 3rd-year PhD (Fall 2023) under Anqi Wu, working on state-space models and Gaussian processes for multi-region brain communications — directly applicable to EEG/neural signal modeling pipelines
  • ICML 2025 Oral, NeurIPS 2024, ICLR 2024 Spotlight show consistently strong output for year 3
  • GitHub bio 'AI for Neuroscience' with BRAINML-GT org repos and a Kalman-SNN filter repo confirm the neuro-signal angle
  • Website has 9 tracked changes through Sept 2025 though quieter recently
  • DB hireability is LOW but correcting upward to MEDIUM given strong publication trajectory and expected graduation 2027-2028 making him a pipeline candidate
  • Hireability: MEDIUM — not graduating soon, but strong BrainML profile worth tracking
CL

Chengrui Li

low hireability

research scientist@Meta

Previously: Intern @ A*STAR

Atlanta, US

  • BrainML PhD alumnus (GaTech 2025, Anqi Wu) now at Meta CTRL-Labs doing neural surface electromyography — the most directly BCI-relevant placement of any BrainML member
  • LinkedIn confirms location change Atlanta→New York and headline/title change scraped Feb 2026, just started at Meta ~Jan 2026; website updated Feb 19 2026 (RECENT, 13 days ago)
  • Qualifying despite low
  • hireability: his current role IS the BCI intersection we care about (sEMG/neural interface at Meta's BCI arm), and noting him for future pipeline
  • Hireability: LOW — just started at Meta CTRL-Labs, not actively seeking, but profile is highly relevant for network mapping
FW

Feiyang Wu

low hireability

Summer Intern@Georgia Tech Research Institute

Previously: Teaching Assistant @ Georgia Institute of Technology

Atlanta, US

  • BrainML co-advised PhD (Fall 2023) under Anqi Wu + Ye Zhao; research on RL, optimization, and robotics applied to behavior and computational neuroscience
  • ICML 2025 and ICRA 2026 papers, qualified exam passed May 2025
  • BrainML adjacency is moderate (RL+neuro) rather than direct BCI/EEG, but lab membership and computational neuroscience framing satisfy the 'BrainML member' qualifier criterion
  • LinkedIn change Feb 2026: intern→RA title, confirming active PhD
  • Hireability: LOW — early-stage PhD (yr 2-3), not graduating until 2027-2028, RL/robotics is adjacent but not core BCI/EEG. Qualifying per instructions to be generous with BrainML members
JK

Jingyang Ke

low hireability

Graduate Research Assistant@Georgia Institute of Technology

Previously: Undergraduate Research Assistant @ Georgia Institute of Technology

Atlanta, US

  • BrainML co-advised PhD (Fall 2023, Anqi Wu + Jeff Markowitz) working on inverse RL to decode and characterize animal behavior from neural data — directly relevant to neural decoding pipelines that underlie BCI
  • ICML 2025 poster on IRL with switching rewards for animal behavior characterization
  • BS CS GaTech 2023 (fast pipeline into PhD)
  • No website activity in pipeline and no LinkedIn history, but OpenReview confirms active affiliation
  • Qualifying as BrainML member with behavior-neural decoding focus
  • Hireability: LOW — early-stage PhD (yr 2-3), not graduating until 2027-2028, but the IRL-for-neural-behavior work is directly pipeline-relevant for BCI
LC

Lei Chu

low hireability

Researcher@University of Southern California

Previously: Postdoctoral Research Associate @ University of Southern California

Los Angeles, US

  • USC WiDeS group researcher (PhD, SJTU 2020) with h=23
  • Re-evaluated under broadened criteria: EEG and IMU data analysis are listed in his research profile, and he works on time series modeling and few-shot learning that transfers to biosignal analysis
  • His EEG/IMU work includes activity recognition and wearable sensor data (MARS repo: 'Mixed Virtual and Real Wearable Sensors for Human Activity Recognition', CVPR-accepted human pose estimation from inertial sensors) — wearable biosignal analysis does touch the broader brain/neural periphery
  • However, confirmed via website and GitHub that primary research is wireless communications (V2V/V2X channel prediction, 5G/B5G localization), not brain/neural
  • The ICCV 2025 diffusion model work is computer vision
  • EEG tag in DB is a secondary modality, not his main work
  • Website 1 change (10+ months ago)
  • Pipeline signals: LinkedIn update added 'Generative' to headline, no job search signal
  • Qualifying per instructions with a LOW hireability flag — the time series / wearable sensor work is peripherally relevant under the broadened criteria but there is no dedicated brain/EEG research focus
  • Hireability: LOW — stable at USC in wireless/sensing research, EEG is a secondary data modality rather than a core focus
MV

Mithilesh Vaidya

low hireability

Research Engineer@Descript

  • BrainML MS alumnus (GaTech, May 2024) who worked under Anqi Wu on neural latent variable models and VAE disentanglement for computational neuroscience — qualifying as 'brain-related' under broadened criteria (modeling of neural systems)
  • Prior IIT Bombay work on children's speech prosody and ICASSP 2022 publication on deep learning for speech prominence detection shows depth in neural signal modeling applied to speech
  • Now Research Engineer at Descript (audio AI), joined June 2024
  • No pipeline signals (no slug in DB)
  • Under the broadened criteria (any brain/neural signal work counts), the BrainML neural latent variable work satisfies the bar
  • Hireability: LOW — stably employed at Descript in audio AI with no apparent job search signal; the neuroscience work is from his MS, not his current role. Qualifying on technical merit but flagging LOW mobility
OJ

Oiwi Parker Jones

low hireability

Principal Researcher@University of Oxford

Previously: Lecturer @ University of Oxford

Oxford, GB

  • PI of the Parker Jones Neural Processing Lab at Oxford (Oxford Robotics Institute + Department of Engineering Science + Jesus College Fellow), specializing in non-invasive BCI for inner speech decoding via EEG/MEG — the most direct speech BCI + deep learning profile in this batch. h=24, active publication record including Oct 2025 bioRxiv on decoding inner speech from EEG/MEG
  • Website has 22 tracked changes with most recent 27 days ago (RECENT), and an active blog
  • While PI-level hireability is typically LOW (entrenched in academia), this profile warrants a flag for senior technical leader roles
  • Hireability: LOW — established PI at Oxford, unlikely to relocate; worth noting for advisory/collaboration relationships rather than hiring
ZL

Zhangqi Luo

low hireability

Engineer/Researcher@CTRL-labs (Meta)

  • BrainML MS alumnus (GaTech, Fall 2022) who worked on 3D animal behavior reconstruction with Anqi Wu, now at Meta CTRL-labs — Meta's neural interface / sEMG BCI arm
  • This makes him the second BrainML→CTRL-labs placement (alongside Chengrui Li), confirming the lab-to-BCI-industry pipeline is real
  • No slug in DB (not scraped), but the trajectory is highly relevant: BrainML neuro methods → neural interface industry
  • No pipeline signals available since no slug
  • Hireability: LOW — recently placed at Meta CTRL-labs, unlikely to move. Qualifying for network mapping and future tracking

Runs

#1completed24 qualified / 24 foundMar 12, 8:35 PM