Welcome!
I'm Peter, a graduate student at Northeastern University. I'm broadly interested in theoretical & applied machine learning, decision making, and optimization.
My research aims to understand the processes of representation learning, generalization, and sample-compression in machine learning models.
Education
- 2024-2026: M.S. in Computer Science, Northeastern University
- 2020-2024: B.S. in Computer Science, Northeastern University
Teaching
- Spring 2026: TA for CS 4530 (Fundamentals of Software Engineering)
- Fall 2025: TA for CS 4530 (Fundamentals of Software Engineering)
- Fall 2022: TA for CS 3500 (Object-Oriented Design)
Bio
I'm currently a M.S. in Computer Science candidate at Northeastern University, where I'm exploring theoretical machine learning.
Previously, I spent about 2 years building at various venture-backed startups in the high-performance blockchain infrastructure, cryptography, and browser agent space.
In the past, I've:
- Mapped relationships between post-quantum cryptographic-hardness assumptions with Prof. Ariel Hamlin
- Co-founded a web development company
- Researched meta-heuristic optimization algorithms for a DARPA project at Scientific Systems
Email: li.pet [at] northeastern [dot] edu