
Jennifer Tang
Massachusetts Institute of Technology
About Me
I am a Postdoctoral Associate in IDSS (Institute for Data, Systems, and Society) at MIT working with Ali Jadbabaie. I received my Ph.D. in the Department of Electrical Engineering and Computer Science at MIT advised by Yury Polyanskiy. Previous to that, I received my B.S.E in Electrical Engineering at Princeton University. At Princeton, I did my junior and senior independent work with Paul Cuff.
My research interests include information theory, prediction with logarithmic loss, quantization and data compression, high-dimensional statistics, data analytics, and models for social dynamics and inference.
Publications and Preprints
Conference
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Capacity of Noisy Permutation Channels
Jennifer Tang, Yury Polyanskiy
ISIT 2022 (Best Student Paper Award Winner) -
Efficient Representation of Large-Alphabet Probability Distributions via Arcsinh-Compander
Aviv Adler*, Jennifer Tang*, Yury Polyanskiy
ISIT 2022 - Minimax Regret on Patterns Using Kullback-Leibler Divergence Covering
Jennifer Tang
COLT 2022 - Exploiting Temporal Structures of Cyclostationary Signals For Data-Driven Single-Channel Source Separation
Gary C.F. Lee, Amir Weiss, Alejandro Lancho, Jennifer Tang, Yuheng Bu, Yury Polyanskiy, Gregory W. Wornell
MLSP 2022 (Best Student Paper Award Winner) -
Data-Driven Blind Synchronization and Interference Rejection for Digital Communication Signals
Alejandro Lancho, Amir Weiss, Gary C.F. Lee, Jennifer Tang, Yuheng Bu, Yury Polyanskiy, Gregory W. Wornell
GlobeCom 2022 -
Quantization of Random Distributions under KL Divergence
Aviv Adler*, Jennifer Tang*, Yury Polyanskiy
ISIT 2021 -
Tracking to Improve Detection Quality in Lidar for Autonomous Driving
Jennifer Tang, Atulya Yellepeddi, Sefa Demirtas, Christopher Barber
ICASSP 2020 -
Defect Tolerance: Fundamental Limits and Examples
Jennifer Tang, Da Wang, Yury Polyanskiy, Gregory W. Wornell
ISIT 2016
Shannon Centennial Celebration (Student Competition Winner)
Journal
-
Capacity of Noisy Permutation Channels
Jennifer Tang and Yury Polyanskiy
(under review) - Efficient Representation of Large-Alphabet Probability Distributions
Aviv Adler*, Jennifer Tang*, Yury Polyanskiy
(Accepted to IEEE JSAIT Issue on Modern Compression) -
Defect Tolerance: Fundamental Limits and Examples
Jennifer Tang, Da Wang, Yury Polyanskiy, Gregory W. Wornelli
IEEE Transactions on Information Theory 2018
* indicates equal contribution
Contact Me
You are encouraged to email me if:
- You want a copy of my CV or Ph.D. thesis
- Interested in having me give a talk in your group!
You can email me at: jstang AT mit.edu