Saturday, December 6th, 2025 | Upper Level Room 24ABC | San Diego, California
Our brains and bodies speak a rich and complex biological language of neural and physiological signals, a language that AI models are increasingly capable of deciphering as large-scale datasets become available. Recent advances in brain interfacing and wearable technologies, including EEG, intracortical electrophysiology, EMG, MEG, and ECG, have enabled the broad collection of these signals across real-world contexts and diverse populations. This growing wealth of data is driving a shift toward foundation models: large-scale, pretrained AI systems designed to learn from biosignals and generalize across diverse downstream applications, from brain-computer interfacing to health monitoring.
Realizing this potential, however, requires addressing the unique challenges that come with biosignal timeseries: they are noisy, heterogeneous, and collected under variable conditions across subjects, devices, and environments. To meet these challenges, this workshop brings together neuroscientists, biomedical engineers, wearable tech researchers, and machine learning experts advancing foundation model approaches. Through interdisciplinary dialogue, we aim to catalyze the next generation of AI models that can capture the complexity of the brain, body, and behavior at scale.
This is a NeurIPS 2025 workshop. Registration is required through the official NeurIPS conference website. Make sure to check the "Workshops & Competitions" session when registering.
Columbia, ARNI
Columbia University
Stanford University
MIT, Harvard
Sophont, Princeton
Mila
Donders Institute
Meta
Columbia University
Mila
3 contributed talks (5 mins each)
Contributed Works + Live Demos
3 contributed talks (5 mins each)
3 contributed talks (5 mins each)
Contributed Works + Live Demos
