I’m a PhD student at UCLA advised by Prof. Vwani Roychowdhury. I’m broadly interested in language modeling and information retrieval. My current focus is on building better information representation systems for LLMs (memory systems) to enable more dynamic, adaptable representations. I’m also interested in applying advances in language modeling to problems in the sciences and in health. I’ve also spent consecutive summers (and a bit more!) at NVIDIA building on-device agents for gamers. At NVIDIA, I worked across the entire stack from curating proprietary tool-use/reasoning data, parameter-efficient fine tuning of Small Language Models, Retrieval mechanisms for system info QA, and a host of optimizations to keep everything working in a tiny form factor!
We introduce GSW, which equips LLMs with human-like episodic memory through structured semantic representations that track actors, roles, and states across space and time, outperforming standard RAG frameworks on episodic memory tasks.
Bioinformatics 2025
We introduce DNARDE, a DNA language model trained with a contrastive objective for sequence alignment, pairing it with vector-store retrieval over nucleotide sequences. DNARDE outperforms prior transformer baselines on alignment and transfers across chromosomes and species.
NeurIPS 2025 — GenAI for Health Workshop
We develop a framework using open-source LLMs to standardize opioid use disorder prescriptions from diverse EHRs, enabling consistent analysis across different EHR sources and formats.
arXiv
Initial explorations on what an evolving memory system could look like from the perspective of how an ideal AI would observe and build a semantic map of an ongoing situation.
* denotes equal contribution.