Organizers.

Arnault Caillet Core · operations

Yneuro and Imperial College Bioengineering. PhD work on EMG biomechanics modelling. Core team for the EEG/EMG Foundation Challenge: runs day-to-day platform operations and connects the Yneuro engineering side with the academic track teams.

Hubert Banville Track 01 · EEG-to-IMG

Research Scientist in the Brain & AI group at Meta FAIR. PhD at Inria Parietal on self-supervised learning for EEG; previously a researcher at Muse. Designs the SSL pretraining for the EEG-to-IMG encoder.

Pierre Guetschel Core · decoding methods

PhD candidate at the Donders Institute. Deep learning for EEG decoding with a focus on transfer learning, self-supervised learning, and foundation models. Core developer of Braindecode and MOABB.

Jean-Rémi King Track 01 · EEG-to-IMG

CNRS researcher (ENS, detached) leading the Brain & AI team at Meta AI. Studies the brain and computational bases of human intelligence; develops models that decode brain activity from MEG, EEG, electrophysiology, and fMRI.

Vinay Jayaram Track 01 · EEG-to-IMG

At Alljoined, assembles large-scale, image-aligned EEG corpora. Owns the dataset side of Track 1: stimulus protocols, alignment, and the public release used as the warm-up split.

Ugo Nunes Track 01 · EEG-to-IMG

Alljoined. Builds the data pipelines and evaluation harness for Track 1, keeping the EEG-to-image retrieval scoring reproducible across labs and submission environments.

Simon Kojima Track 02 · BCI track

Postdoctoral researcher at Inria Bordeaux on the NEARBY project, working on noise- and variability-robust BCIs for out-of-the-lab use. Motor-imagery BCIs, EEG variability, and ML for neural decoding.

Pauline Dreyer Track 02 · BCI track

PhD candidate at Inria Bordeaux on the PROTEUS project. Active brain-computer interfaces with a focus on understanding and addressing within-user variability, the same question Track 2 evaluates.

Raphaëlle N. Roy Track 02 · BCI track

Professor of neuroergonomics & physiological computing at ISAE-SUPAERO. Co-founder & vice-president of the French BCI association; organised the first passive-BCI competition. Adds the operator-state perspective to BCI evaluation.

Fabien Lotte Track 02 · BCI track

Research Director at Inria Bordeaux & LaBRI, leading project-team Potioc on Brain-Computer Interfaces. PI of ANR REBEL/PROTEUS and ERC BrainConquest/SPEARS. USERN Prize 2022; Lovelace-Babbage prize 2023.

Jiansheng Niu Track 03 · Sleep onset

Muse. Owns the consumer-wearable side of Track 3: recording protocols, signal-quality monitoring, and the comparison of Muse-grade EEG against clinical sleep-staging baselines.

Maurice Abou Jaoude Track 03 · Sleep onset

Senior Research Scientist at Muse, makers of the wearable EEG and fNIRS headband. Builds algorithms that turn raw EEG into clinical signals, including automated sleep staging at expert agreement and non-invasive detection of neurological abnormalities.

Christopher Aimone Track 03 · Sleep onset

Chief Innovation Officer and co-founder of Muse. Leads R&D advancing wearable neurotech with sleep science and AI; background spans VR/AR, humanistic intelligence, computer vision, and robotics.

Pranav Mamidanna Track 04 · EMG-to-Pose

Research Fellow at Imperial College London. Works at the boundary of AI and neuroscience, combining mathematical models of physical and biological systems with modern AI representations. Targets clinical translation.

Alex Gramfort Track 04 · EMG-to-Pose

Senior Research Scientist Manager at Meta Reality Labs, Paris. Works on machine learning for surface-EMG decoding. Previously Research Director at Inria leading the MIND/Parietal team. Statistical ML, signal processing, and biosignal computing.

Cédric Rommel Track 04 · EMG-to-Pose

Research scientist at Meta AI working in AI for neural interfaces. His work mostly revolves around the idea of learning and exploiting data symmetries (invariances and equivariances) to make neural networks more data efficient and robust.

Thorir Mar Ingolfsson Track 02 · BCI track

Postdoctoral researcher at the Integrated Systems Laboratory (IIS), ETH Zürich, in Luca Benini's group. His ETH Zürich PhD focused on robust seizure detection with wearable EEG. He develops biosignal foundation models including LUNA, LuMamba, FEMBA, CeREBrO, and PanLUNA, and deploys them on ultra-low-power edge hardware so AI can run on microwatts. Personal site →

Marie-Constance Corsi Track 02 · BCI track

Inria Research Scientist at Paris Brain Institute (NERV Lab). Identifies neurophysiological markers of BCI training and develops interpretable AI tools for neurological-disease diagnosis. Reviews Track 2 submissions for clinical and interpretability quality, not just leaderboard score.

Thomas Moreau Core · evaluator

Research scientist at Inria, MIND Team. Statistical ML, optimization, and signal processing for M/EEG decoding; maintainer of benchopt; contributor to braindecode, MNE-Python, MOABB.

Joséphine Raugel Track 01 · EEG-to-IMG

PhD candidate at ENS and Meta FAIR. Aligns deep-network and neural-data representations; co-author of NeuralSet (Python neuro-AI package) and TRIBEv2 (foundation brain encoder).

Lionel Kusch Core · AWS infra

Machine-learning infrastructure engineer at Yneuro. Cloud deployment, software engineering, and computational-neuroscience research projects. Owns the AWS submission and ranking pipeline.

Thomas Semah Host org · Yneuro CEO

Founder & CEO of Yneuro, the host organisation for the EEG/EMG Foundation Challenge. CentraleSupélec / ESPCI Paris-PSL alum, Stanford School of Medicine master's. Yneuro provides infrastructure and operational support for the challenge.

Seyed Yahya Shirazi Core · data & standards

Assistant Project Scientist at UC San Diego. Led HBN-EEG curation and annotation. Lead Scientist for BIDS extension proposals to EMG and Stimulus. Core member of the HED working group and the EEGLAB development team.

Scott Makeig Senior advisor · ICA pioneer

Founding director of the Swartz Center at UCSD. Pioneer in EEG analysis and the development of Independent Component Analysis (ICA) for brain-signal decomposition; leader in mobile brain/body imaging (MoBI).

Isabelle Guyon Senior advisor · ChaLearn

Director, Research Scientist at Google DeepMind, in detachment from her professorship at Université Paris-Saclay. President of ChaLearn, community lead of Codalab, JMLR action editor, NIPS 2016 program co-chair, NIPS 2017 general co-chair. 2020 BBVA Frontiers in Research Award (with Schölkopf and Vapnik) for SVMs.

Terrence Sejnowski Senior advisor · Salk

Co-developed the Boltzmann machine; foundational work in deep learning. Connects neuroscience and machine learning. Carries forty years of context on what the field has and hasn't already tried.

Sylvain Chevallier Core · Codabench

Full Professor at Université Paris-Saclay, board member of DATAIA/ClusterIA, co-leader of the TAU team. Leads the Codalab/Codabench framework, the platform the competition runs on.

Arnaud Delorme Core · EEGLAB

Leads the EEGLAB project. Research Director at CNRS, Research Scientist at UCSD. Owns the reproducibility audit at test-freeze, which is what lets any top entry be replayed byte-for-byte from another team's pipeline.