Jennifer Tang
About Me
Beginning in Fall 2026, I will be an Assistant Professor of Electrical Engineering at Polytechnique Montréal. I am currently an Assistant Professor of Mathematics and Computer Science at the College of the Holy Cross in Worcester, Massachusetts. Previously, I was a Postdoctoral Associate in IDSS (Institute for Data, Systems, and Society) and LIDS (Laboratory for Information and Decision Systems) at MIT working with Ali Jadbabaie. I received my Ph.D. in Electrical Engineering and Computer Science at MIT, advised by Yury Polyanskiy. Prior to that, I received my B.S.E in Electrical Engineering at Princeton University, where I did my junior and senior independent work with Paul Cuff.
My research interests include information theory, prediction and estimation, quantization and data compression, high-dimensional statistics, data analytics, multi-agent networks, and models for social dynamics and inference.
I am recruiting students to my group at Polytechnique Montréal! In particular, I am looking for students interested in working on the intersection of machine learning and information theory. If you are interested, please send me an email with the subject line "Prospective Student", introducing yourself and describing why you are interested in working with me. Attach also a resume or CV. I may not be able to respond to everyone's email. Note that admission to Polytechnique Montréal is decentralized. I first accept you as a student and then you apply to the university.
Publications and Preprints
Conference
-
A Model-Driven Lossless Compression Algorithm Resistant to Mismatch
Cordelia Hu, Jennifer Tang
(accepted to ISIT 2026) -
Synchronizing Probabilities in Model-Driven Lossless Compression
Aviv Adler, Jennifer Tang
(accepted to ICLR 2026) -
Bounding the Capacity of the Multinomial Channel using KL Divergence Covering and Packing
Jennifer Tang
ISIT 2025 -
Estimating True Beliefs from Declared Opinions
Jennifer Tang, Aviv Adler, Amir Ajorlou, and Ali Jadbabaie
ACC 2024 -
Evolution of Opinions under Social Pressure on Random Graphs
Jennifer Tang, Amir Ajorlou, and Ali Jadbabaie
ACC 2024 -
Stochastic Opinion Dynamics under Social Pressure in Arbitrary Networks
Jennifer Tang, Aviv Adler, Amir Ajorlou, and Ali Jadbabaie
CDC 2023 -
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
-
Stochastic Opinion Dynamics under Social Pressure in Arbitrary Networks
Jennifer Tang, Aviv Adler, Amir Ajorlou, and Ali Jadbabaie
IEEE Transaction on Automatic Control 2025 -
Estimating True Beliefs from Declared Opinions
Jennifer Tang, Aviv Adler, Amir Ajorlou, and Ali Jadbabaie
IEEE Transaction on Automatic Control 2025 -
Capacity of Noisy Permutation Channels
Jennifer Tang and Yury Polyanskiy
IEEE Transactions on Information Theory 2023 - Efficient Representation of Large-Alphabet Probability Distributions
Aviv Adler*, Jennifer Tang*, Yury Polyanskiy
IEEE Journal on Selected Areas in Information Theory (Issue on Modern Compression) 2022 -
Defect Tolerance: Fundamental Limits and Examples
Jennifer Tang, Da Wang, Yury Polyanskiy, Gregory W. Wornell
IEEE Transactions on Information Theory 2018
Teaching
College of the Holy Cross
- CSCI 399: Network Science (Spring 2026)
- CSCI 235: Analysis of Algorithms (Spring 2026)
- CSCI 132: Data Structures (Fall 2025)
MIT
- Instructor for 1.022: Introduction to Network Models (Spring 2025)
- TA for 6.008: Introduction to Inference (Fall 2020)
- Graduate Instructor for 6.041/6.431: Probabilistic Systems Analysis (Spring 2020)
- TA for 6.008: Introduction to Inference (Fall 2019)
- TA for 6.437: Inference and Information (Spring 2019)
- TA for 6.439: Statistics, Computation and Applications (Fall 2018)
- Mathematics Instructor for MIT Women's Technology Program (WTP) (Summer 2017)
Contact Me
You can email me at: jstang AT mit.edu or jtang AT holycross.edu