Graduate student at UCLA
I am pursuing a Master of Quantum Science and Technology at UCLA. My current interests are in computational tools for scientific discovery, especially where machine learning, inverse problems, and quantum methods overlap.
Before UCLA, I led development of Reggi, a legal AI assistant at Regology. Earlier, I worked on communication-efficient distributed learning at KAUST and on optimization problems in research internships.
Developing a prior-aware extension of COPRA for ultrafast pulse retrieval by integrating analytic, physics-informed, and learned denoising priors into the iterative retrieval loop.
Engineered a scalable ClickHouse data warehouse with dbt for analytics and built optimized ranking systems with secure multi-tenant social feed architecture in Go.
Led Reggi, a RAG-based legal AI assistant built on in-house semantic search and LLM workflows, and applied state-of-the-art NLP methods across legal corpora.
Developed communication-efficient methods for large-scale distributed machine learning and co-authored work on compressed communication, sparse collectives, and federated learning.
INRIA
·
2020
Explored weakly supervised methods for activity detection in videos when annotations are limited or incomplete.
Minor coursework in Algorithms and Machine Learning.
KAUST
·
2017
Researched asynchronous randomized methods for solving large linear systems.
