September 2019 – Current
- Pursuing an M.S. in Computer Science with a B.A. in Computer Science and Mathematics.
- TF for CS 124 (Data Structures and Algorithms), Spring 2020 - Commendation for Extraordinary Teaching
- TF for CS 182 (Artificial Intelligence), Fall 2020
- TF for CS 161 (Operating Systems), Spring 2021 - Certificate of Distinction in Teaching
- TA for Summer Geometry Institute (SGI), Summer 2021
- TF for CS 153 (Compilers), Fall 2021
- Selected coursework († graduate-level):
- Computational Complexity† (CS 221)
- Randomized Algorithms† (CS 223)
- Computational Learning Theory† (CS 228)
- PL/AI Graduate Seminar† (CS 252r)
- Systems Security† (CS 263)
- Distributed Systems Engineering† (MIT 6.824)
- Shape Analysis† (MIT 6.838)
- Robotic Manipulation† (MIT 6.843)
- Graduate Probability† (Stat 210)
- Graduate Statistical Inference† (Stat 211)
- Compilers (CS 153)
- Operating Systems (CS 161)
- Computer Graphics (MIT 6.837)
- Differential Topology (Math 132)
- Honors Abstract Algebra (Math 55a)
- Honors Real and Complex Analysis (Math 55b)
Software Engineer at Convex
June 2021 – October 2021
- First hired engineer at a seed-stage startup. Worked with three highly experienced technical cofounders (ex-Dropbox) to build a next-generation platform for dynamic serverless applications using Rust and TypeScript.
- Contributed to the MVP and advised on web developer experience. Described by the CEO as an "early core team member" who "played a real architectural hand in the design of the product."
Quantitative Research Intern at Jump Trading
June 2021 – August 2021
- Won the intern trading strategies competition and rotated on a trading team to research algorithmic signals in US equities.
- Developed decentralized apps on the Ethereum blockchain for the cryptocurrency team, including new trading algorithms on DEXs. Contributed to the open source Ethereum ecosystem in Rust, Go, and Python.
Software Engineering Intern at Scale AI
December 2020 – January 2021
- Worked on machine learning infrastructure for a fast-growing startup using Terraform, Kubernetes, and AWS.
- Developed an in-house system to unify the ML training workflow, allowing the team to quickly iterate on models, share results on a tracking server, and launch Kubernetes distributed training jobs, saving “hours” of time on each experiment.
Architecture Intern at Nvidia
June 2020 – August 2020
- Worked with the Applied Deep Learning Research (ADLR) group on deep learning models for street image segmentation.
- Individually developed and released FastSeg, an open-source library containing state-of-the-art PyTorch implementations of MobileNetV3 LR-ASPP for real-time semantic segmentation, significantly more accurate than existing public implementations.
Research Assistant at Harvard Programming Languages Group
June 2020 – August 2020
- Worked on a C++ compiler for Formulog, a variant of Datalog that supports ML-like syntax extension and SMT queries.
- Generated highly parallel templatized C++17 code, used caching in B-Tree comparisons to speed up Datalog evaluation by 16x, and optimized existing OpenMP code using lockless data structures for an additional 4x speedup.
- Wrote a handwritten parser that was 30x faster than the ANTLR-generated LL(*) parser and used 20x less memory (80 GB to 4 GB).
Undergraduate Researcher at Predictive Medicine Group
December 2019 – June 2020
- Conducted research in statistics & medical informatics advised by Ben Reis (Harvard Medical School), developing temporal models to identify patients at high risk of suicide based on medical histories obtained from Massachusetts General Hospital.
Coauthor at American Association of Physics Teachers
April 2018 – October 2020
- Co-wrote a physics book with Branislav Kisačanin, F=ma Contests: 2011-2019 Solutions Manual.
- Provided detailed solutions for nine years of past F=ma contests to encourage physics interest among high school students.
- Published with the American Association of Physics Teachers (AAPT) and AIP Publishing, preprint available online.
Computer Science Instructor at AlphaStar Academy
December 2017 – April 2020
- Taught advanced algorithms and data structures (USACO Platinum) and AIME-level (national math competition) mathematics to talented high school students across the nation.
- Developed detailed lesson plans and recorded lectures for future summer programs and online courses.
Mathematics Researcher at PRIMES-USA
January 2018 – December 2018
- Conducted research on quasirandom permutations, using flag algebras and semidefinite programming.
- Published a paper in the Electronic Journal of Combinatorics 28(1), and won the Regeneron STS competition.
- International Olympiad in Informatics (IOI): Gold Medalist (2018, 2019), 7th place globally
- Google Hash Code: World Finalist (2020, 2021), 7th place team out of over 100,000 students and professionals
- Google Code Jam: Round 3 Finalist (2020), placed 34th globally
- Facebook Hacker Cup: Round 3 Finalist (2020)
- PicoCTF: Winner (2018), ranked 6th
- Mathematical Olympiad Program (MOP): Participant (2017), IMO team selection group (2017, 2018)
- USA Math Olympiad (USAMO): Honorable Mention (2017), top 24 in nation
- U.S. Physics Team: Invitee (2017, 2018, 2019)
- USA Physics Olympiad (USAPhO): Gold Medalist (2017, 2018, 2019)
- National YoungArts Foundation: Winner in Classical Music (2018, 2019)
- JDR Viola Competition: Grand prize winner, performed with a professional orchestra (2019)
- Texas All-State Symphony Orchestra: Principal Violist (2017), Co-Principal (2016, 2018)