About me
Hello! My name is Jennifer Sun, and I am a third-year graduate student at the Department of Operations Research and Financial Engineering at Princeton University, advised by Prof. Elad Hazan from the Department of Computer Science. I am generously awarded with the Gordon Wu Fellowship. I am broadly interested in machine learning theory, and my recent work particularly focuses on online learning and its intersection with optimization and nonstochastic control theory.
During my time at Princeton, I also worked as a student researcher for the algorithmic efficiency team at Google DeepMind, working on memory efficient optimization algorithms. Before coming to Princeton, I graduated Summa Cum Laude from The University of Chicago with a Bachelor of Science degree in Mathematics with honors. During my undergraduate studies, I was fortunate to be inducted into the Phi Beta Kappa society and advised by insipiring and supportive mentors. To highlight, I was fortunate to work on bioinformatics research with Prof. Xinan Yang and pariticipate in algebraic topology reading courses and the 2020 REU program led by Prof. Peter May.
Click here for my updated resume (Jan.2024).
Preprints
[1] Arun Suggala*, Y Jennifer Sun*, Praneeth Netrapalli, Elad Hazan. Second Order Methods for Bandit Optimization and Control. Link to paper.
Publications
[4] Y Jennifer Sun, Stephen Newman, Elad Hazan. Optimal Rates for Bandit Nonstochastic Control. NeurIPS 2023. Link to paper.
[3] Vladimir Feinberg, Xinyi Chen, Y Jennifer Sun, Rohan Anil, Elad Hazan. Sketchy: Memory-efficient Adaptive Regularization with Frequent Directions. NeurIPS 2023. Link to paper. Link to code.
[2] (Alphabetical) Elad Hazan, Adam Tauman Kalai, Varun Kanade, Clara Mohri, Y Jennifer Sun. Partial Matrix Completion. NeurIPS 2023. Link to paper.
[1] Xinan H Yang, Andrew Goldstein, Yuxi Sun, Zhezhen Wang, Megan Wei, Ivan P Moskowitz, John M Cunningham. Detecting critical transition signals from single-cell transcriptomes to infer lineage-determining transcription factors. Nucleic acids research. Link to paper. Link to package.
Services
Reviewer: NeurIPS 2023, STOC 2024, ICML 2024
Program committee: COLT 2023, 2024
Teaching
ORF 531: Computational Finance in C++, Fall 2022
ORF 335: Introduction to Financial Mathematics, Spring 2023
COS 597Q: AI Alignment and Safety, Fall 2023
COS 324: Introduction to Machine Learning, Spring 2024