About
About Me
I’m a Computer Science M.S. candidate at the University of Minnesota. Prior to this, I earned dual B.S. degrees in Applied Mathematics and Economics from UCLA. My professional background spans machine learning engineering and generative AI. As a Generative AI Engineer at Reality AI, I architected scalable, low-latency LLM generation pipelines, implemented semantic search using vector embeddings, and deployed robust MLOps infrastructure. Previously, I developed real-time recommendation systems leveraging spatial and semantic search during my time with the UCLA Office of Advanced Research Computing. I enjoy blending my mathematical foundation with practical software engineering to build efficient, robust AI solutions.
Education
M.S., Computer Science
University of Minnesota | 2028 (expected)
B.S., Applied Mathematics and B.S., Economics (Double Major)
UCLA | 2024
Technical Skills
Programming Languages
Frameworks & Tools
Technologies
Research Interests
My research focuses on building autonomous agents capable of exploring complex, high-dimensional design spaces to advance scientific discovery. I leverage representation learning frameworks to distill raw data into structured latent spaces reflecting underlying state dynamics. By embedding probabilistic models and Bayesian optimization within these manifolds, my work enables agents to rigorously quantify epistemic uncertainty and execute highly sample-efficient exploration.
Projects
For a complete list of my projects, please visit my projects page. You can also find my code on GitHub.
Contact
I’m always interested in discussing research collaborations, internship opportunities, or interesting technical challenges. Feel free to reach out via email or connect on LinkedIn.
About This Site
This site is built with Jekyll and hosted on GitHub Pages. You can find my source code on GitHub.