I am a postdoc at Harvard University in Kanaka Rajan's lab. I am interested in theoretical neuroscience and NeuroAI research. I completed my PhD at Columbia University's Center for Theoretical Neuroscience, co-advised by Larry Abbott and Dmitriy Aronov.
I am interested in understanding representation learning in artificial systems tested on real-world tasks and using these findings to gain insight into brain function. I also want to understand how episodic memory supports fast, efficient learning, with particular interest in key-value memory systems.
In the Abbott and Aronov labs, I worked on mechanistic models of memory formation and retrieval, taking inspiration from advances in machine learning. I previously did my undergrad at UC Berkeley, where I studied computer science and molecular & cell biology. There, I worked in the lab of Jose Carmena to understand how neural circuits drive neuroprosthetic learning. I also worked in the labs of Daniel Feldman and Anne Collins.
Updates
- March 2025: Presented at the Yale Neuro-AI journal club
- Jan 2025: Our paper "Barcode activity in a recurrent network model of the hippocampus enables efficient memory binding" is now out in eLife
- Dec 2024: Presented my internship work with Apple at NeuRIPS Medical Foundation Models Workshop: "Promoting cross-modal representations to improve multimodal foundation models for physiological signals"
- Oct 2024: Started my postdoc with Kanaka Rajan
- Sep 2024: Defended my thesis and finished my PhD
- Sep 2024: Finished my ML research internship at Apple
- May 2024: Presented ICLR Oral on our paper "Predictive auxiliary objectives in deep RL mimic learning in the brain"
- Apr 2024: Started ML research internship at Apple's Body-Sensing Intelligence Group
- Mar 2024: Gave a Cosyne workshop talk on our barcode-memory model
- Mar 2024: Gave a Cosyne talk on our work in relating Deep RL models + auxiliary objectives to neuroscience
- Feb 2024: Gave a talk at the DeepMind NeuroLab workshop