BCI Research with the Ganguly Lab at UCSF

Starting from the beginning of 2026, I have been working at the Ganguly Lab on a object grasp task that consists of 3 grasp modes, physical execution, imagined execution, and visual observation. We are investigating the understand the effects of imagining our complex physical grasps along with the effects of performing complex grasps vs smaller micro actions.

More information about my analysis can be found in the slide below:

This summer, I worked as a student researcher at the Ganguly Lab (UCSF Weill Institute of Neuroscience). The lab develops brain-computer interfaces (BCI) that enable individuals with paralysis to control neuroprosthetic devices using brain signals (see this Cell publication from the lab). The slides below an overview of the lab's work  on BCI.

A major challenge in BCI systems is signal drift: the neural signals recorded from brain implants degrade and change over time. This instability means that gesture decoding algorithms, limiting the long-term reliability of neuroprosthetic control.

Currently, I am working on anomaly detection for long-term gesture decoding stability for the control of a neuroprosthesis. The following slides provide some details on my work presented at the Lab in August 2025.