Eric Lei

3401 Walnut Street

Philadelphia, PA 19104

I am a Ph.D. student at University of Pennsylvania in the Electrical and Systems Engineering department, supported by an NSF Graduate Research Fellowship. I am fortunate to be advised by Shirin Saeedi Bidokhti and Hamed Hassani. My current research interests are in data compression, information theory, machine learning, and networks. Previously, I received my B.S. at Cornell University where my focus was on signal processing and communications.

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

Education

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

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

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

selected publications

  1. Preprint
    Approaching Rate-Distortion Limits in Neural Compression with Lattice Transform Coding
    Eric Lei, Hamed Hassani, and Shirin Saeedi Bidokhti
    arXiv preprint arXiv:2403:07320 2024
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  2. 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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  3. 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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  4. 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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  5. 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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  6. 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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  7. 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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