Eric Zhang

Education

Harvard University

September 2019 – Current

  • Pursuing an M.S. in Computer Science with a B.A. in Computer Science and Mathematics.
  • Teaching:
    • 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 — Certificate of Distinction in Teaching
  • Selected coursework († graduate-level):
    • Computational Complexity (CS 221)
    • Randomized Algorithms (CS 223)
    • Computational Learning Theory (CS 228)
    • PL/AI Graduate Seminar (CS 252r)
    • PL Design 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)

Work Experience

Software Engineer at Modal Labs

February 2022 – Current New York, NY

  • Founding engineer at a seed-stage startup.

Software Engineering Intern at Prosper Robotics

January 2022 London, UK

  • Early-stage startup developing VR-teleoperated household robots. Worked with electrical and mechanical engineers.
  • I wrote real-time (<10 μs) embedded microcontrollers in C++, developed new network services and robot control systems in Go. Refactored a lot of code, fixed many bugs, ported software to a new robot, introduced continuous integration, tests, static type checking for Python.

Software Engineer at Convex

June 2021 – October 2021 San Francisco, CA

  • First hired engineer at a seed-stage startup. Worked with three experienced technical cofounders (ex-Dropbox) to build a reactive, serverless database platform using Rust and TypeScript.
  • Wrote significant components of 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 Chicago, IL

  • 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 San Francisco, CA

  • 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 Santa Clara, CA

  • 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 Cambridge, MA

  • 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 Boston, MA

  • 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 College Park, MD

  • 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 Santa Clara, CA

  • 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 Cambridge, MA

  • 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.

Selected Awards

Computer Science

  • International Olympiad in Informatics (IOI): Gold Medalist (2018, 2019), 7th place globally
  • Google Hash Code: World Finalist (2020, 2021, 2022), 6th 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

Mathematics

  • Mathematical Olympiad Program (MOP): Participant (2017), IMO team selection group (2017, 2018)
  • USA Math Olympiad (USAMO): Honorable Mention (2017), top 24 in nation

Physics

  • U.S. Physics Team: Invitee (2017, 2018, 2019)
  • USA Physics Olympiad (USAPhO): Gold Medalist (2017, 2018, 2019)

Music Performance

  • 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)