Graduate student at UCLA
I work on computational methods for scientific discovery, with interests in generative and physics-informed models, hybrid quantum-classical algorithms, and practical AI systems.
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.
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.
Explored weakly supervised methods for activity detection in videos when annotations are limited or incomplete.
Researched asynchronous randomized methods for solving large linear systems.
Minor coursework in Algorithms and Machine Learning.
