ms — computer science
relevant coursework: training foundation models, algorithms for big data, high performance computing, distributed systems. cross-registered at mit for graduate deep learning coursework and research.
[cs 181 teaching fellow] machine learning (spring 2024) — sections and office hours covering supervised learning, neural networks, and optimization for 100+ students.
[cs 182 teaching fellow] artificial intelligence (fall 2024) — sections and office hours covering search algorithms, game theory, and machine learning applications for 120+ students.
[stat 110 teaching fellow] probability (fall 2023, fall 2024, fall 2025) — sections and office hours covering probability theory, distributions, and statistical inference for 200+ students.
ba — computer science & statistics
relevant coursework: machine learning, artificial intelligence, probability theory, statistical inference, linear models, stochastic processes, systems programming, multivariable calculus, linear algebra.
[co-president] startups @ harvard (2024 – 2025) — collaborated with a16z, greylock, and gc to scale organization from 20 to 150+ students interested in startups.
[managing director] harvard undergraduate capital partners (2021 – 2022) — managed 30+ analysts and led diligence teams for ai/saas/consumer services for partners totaling $27b aum.
[case team lead] harvard data analytics group (2021 – 2022) — consulted for $50b real estate developer greystar to analyze housing data and rental pricing models.