Eric Lei

Amy Gutmann Hall 508

Philadelphia, PA 19104

I am a final-year Ph.D. student at University of Pennsylvania in the Electrical and Systems Engineering department, advised by Prof. Shirin Saeedi Bidokhti and Prof. Hamed Hassani, and supported by a NSF Graduate Research Fellowship. My current research interests are at the intersection of machine learning and information theory, particularly neural compression and generative models. Previously, I obtained my B.S. from Cornell University.

During summer 2024, I interned at JPMorganChase, working on trustworthy machine learning. Prior to that, I interned at InterDigital, working on 3D generative models.

In summer 2025, I will be joining JPMorganChase (Global Technology Applied Research) as a research scientist in NYC.

Feel free to reach me at elei [at] seas.upenn.edu

Education

University of Pennsylvania
Ph.D. in Electrical and Systems Engineering, 2025

University of Pennsylvania
M.S.E. in Electrical Engineering, 2023

Cornell University
B.S. in Electrical and Computer Engineering, 2020

selected publications

  1. ICLR
    Approaching Rate-Distortion Limits in Neural Compression with Lattice Transform Coding
    Eric Lei, Hamed Hassani, and Shirin Saeedi Bidokhti
    International Conference on Learning Representations 2025
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  2. ICLR
    PaLD: Detection of Text Partially Written by Large Language Models
    Eric Lei, Hsiang Hsu, and Chun-Fu Chen
    International Conference on Learning Representations 2025
  3. ICIP
    WrappingNet: Mesh Autoencoder via Deep Sphere Deformation
    Eric Lei, Muhammad Asad Lodhi, Jiahao Pang, Junghyun Ahn, and Dong Tian
    IEEE International Conference on Image Processing (ICIP), Best Student Paper Award 2024
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  4. ICML NCW
    Text + Sketch: Image Compression at Ultra Low Rates
    Eric Lei, Yiğit Berkay Uslu, Hamed Hassani, and Shirin Saeedi Bidokhti
    ICML Workshop on Neural Compression 2023
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  5. ICLR
    On a Relation Between Rate-Distortion Theory and Optimal Transport
    Eric Lei, Hamed Hassani, and Shirin Saeedi Bidokhti
    International Conference on Learning Representations (Tiny Papers Track) 2023
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  6. JSAIT
    Neural Estimation of the Rate-Distortion Function With Applications to Operational Source Coding
    Eric Lei, Hamed Hassani, and Shirin Saeedi Bidokhti
    IEEE Journal on Selected Areas in Information Theory 2023
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  7. L4DC
    Robust Graph Neural Networks via Probabilistic Lipschitz Constraints
    Raghu Arghal, Eric Lei, and Shirin Saeedi Bidokhti
    In Proceedings of The 4th Annual Learning for Dynamics and Control Conference 2022
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  8. ICML
    Out-of-Distribution Robustness in Deep Learning Compression
    Eric Lei, Hamed Hassani, and Shirin Saeedi Bidokhti
    ICML Workshop on Information-Theoretic Methods for Rigorous, Responsible, and Reliable Machine Learning 2021
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