About

Hi! I am a Computer Science Ph.D. student at Yale University, fortunate to work with Manolis Zampetakis and Andre Wibisono. Prior to starting my Ph.D. studies, I worked at Twitter in the Ads Targeting and Modeling team as a machine learning engineer. Before that, I completed my master’s and bachelor’s degrees together at the University of Pennsylvania, where I was advised by Shivani Agarwal for my master’s thesis.

I received a GFSD (formerly NPSC) fellowship in 2022, sponsored by the U.S. National Security Agency (NSA).

Research

I am interested in machine learning theory and optimization, particularly when theoretical insights can improve the design and practical use of machine learning algorithms.

Publications

J. H. Lee*, A. Mehrotra*, M. Zampetakis*, “Efficient Statistics With Unknown Truncation: Polynomial Time Algorithms Beyond Gaussians”, in IEEE Symposium on Foundations of Computer Science (FOCS), 2024. pdf
J. H. Lee, A. Wibisono, M. Zampetakis, “Learning Exponential Families from Truncated Samples”, in Advances in Neural Information Processing Systems (NeurIPS), 2023. pdf
J. H. Lee*, S. Haghighatshoar*, A. Karbasi, “Exact Gradient Computation for Spiking Neural Networks Through Forward Propagation”, in International Conference on Artificial Intelligence and Statistics, (AISTATS), 2023. pdf
M. Zhang, J. Lee, and S. Agarwal, “Learning from noisy labels with no change to the training process”, in International Conference on Machine Learning (ICML), Jul. 2021. pdf
K. Jaidka, S. C. Guntuku, J. H. Lee, Z. Luo, A. Buffone, and L. H. Ungar, “The rural–urban stress divide: Obtaining geographical insights through twitter”, Computers in Human Behavior, vol. 114, p. 106 544, Jan. 2021, issn: 0747-5632. pdf
S. Chen, E. Dobriban, and J. H. Lee, “A group-theoretic framework for data augmentation”, Journal of Machine Learning Research (JMLR), vol. 21, no. 245, pp. 1–71, 2020. pdf
S. Chen, E. Dobriban, and J. H. Lee, “A group-theoretic framework for data augmentation”, in Advances in Neural Information Processing Systems (NeurIPS), Oral Presentation, 2020. pdf

Workshop Papers and Preprints

J. H. Lee, K. Nikolakakis, D. Kalogerias, A. Karbasi, “Reward-Based Reinforcement Learning with Risk Constraints”
- Preliminary version presented at Duality Principles for Modern Machine Learning Workshop @ ICML 2023

Teaching

Yale University:

I received the Yale CS Department Distinguished Teaching Award for 2022-2023.

Probabilistic Machine Learning (CPSC 586), Teaching Fellow (Spring 2023) evaluation
Introduction to Database Systems (CPSC 537), Teaching Fellow (Fall 2022) evaluation

University of Pennsylvania:

Machine Learning (CIS 520), Teaching Assistant (Spring 2018, Spring 2019)
Algorithms (CIS 320), Teaching Assistant (Spring 2019)
Agent-Based Modeling and Simulation (ESE 520), Teaching Assistant (Fall 2018)
Internet and Web Systems (CIS 555), Teaching Assistant (Spring 2018)
Software Engineering (CIS 573), Head Teaching Assistant (Fall 2017)
Software Engineering (CIS 350), Teaching Assistant (Spring 2017)
Data Structures and Algorithms (CIS 121), Head Teaching Assistant (Fall 2017), Teaching Assistant (Fall 2016, Spring 2017)

Service and Outreach

I believe that being able to give back to others is a privilege. I have received much help to get to where I am today, and I am glad to be able to help others now. I enjoy volunteering with organizations that help students with meeting their educational needs because I feel that education is one way to empower young people to take control of their futures.

(External) Volunteering:

Microsoft TEALS Program, Volunteer Teaching Assistant (2021-2024)
The SMART Program, Volunteer Tutor (2019-2021)

(For those who are interested in getting involved, I highly recommend volunteering with the above organizations. I’ve had a great time working with the staff who are very organized and the students who are eager to learn. The SMART program is local to the the San Francisco Bay Area, but the TEALS program works with high schools throughout the country.)

Service:

Yale Graduate Student Assembly (GSA)
- Serivce Committee Chair (2022-2023, 2023-2024)
- Computer Science Department Representative (2022-2023, 2023-2024, 2024-2025)
Yale Computer Science Graduate Student Advisory Committee (GSAC)
- Provisional (Founding) Member (2022-2023)
- Elected Member (2023-2024)
Yale Graduate Society of Women Engineers (SWE) Mentorship Program, Graduate Student Mentor (2023-Current)
Women in Science at Yale (WISAY), Graduate Student Mentor (2021-Current)
STEM Mentors at Yale, Graduate Student Mentor (2021-2023)
University of Pennsylvania Women in Computer Science (WiCS) Alumni Mentorship Program, Mentor (Spring 2020)

Miscellaneous

My sister is also a (really accomplished!) PhD student, in astronomy. Check out her page!
I have been playing Puzzle and Dragons (on and off) since high school. I also like to play Pokemon Go and Don’t Starve Together and lately Yu-Gi-Oh! Master Duel and Hearthstone, so if you are at Yale let me know if you’d like to be friends on any of these games.
I also enjoy cooking, painting, and fashion.