Background

Chethan Pandarinath, PhD, is an Associate Professor in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University, where he directs the Systems Neural Engineering Lab (SNEL). Pandarinath is a computational neuroscientist and neuroengineer whose research focuses on understanding how populations of neurons represent information and intent, and applying this knowledge to develop high-performance brain-computer interfaces and neuromodulatory devices. He has also served as a research consultant at Meta Reality Labs.

Key Contributions

Pandarinath developed LFADS (Latent Factor Analysis via Dynamical Systems), a groundbreaking machine learning method for analyzing neural population dynamics from high-dimensional neural recording data. LFADS uses a variational autoencoder architecture to reduce complex patterns of neural spiking into low-dimensional temporal factors and dynamics that reveal the underlying computational structure of neural populations. This method has proven invaluable for BCIs, enabling researchers to identify the core dynamical patterns that drive behavior, improve neural decoding robustness, and understand how neural populations implement specific computations. LFADS can combine data from non-overlapping recording sessions spanning months to improve inference of underlying neural dynamics, making it exceptionally powerful for clinical BCI applications where recording sessions are intermittent. The method has become a standard tool in neuroscience and has been widely adopted by BCI researchers worldwide.

Current Work

Pandarinath continues to advance the theory and application of neural dynamics methods at his Systems Neural Engineering Lab. His research focuses on understanding how large populations of neurons represent motor intent and other cognitive variables, and on using dynamical systems approaches to develop high-performance, robust, and practical BCIs and neuromodulatory devices. His work bridges fundamental neuroscience, computational methods, and practical engineering to advance assistive technologies for people with neurological disabilities.