Welcome to Yuzhe Yang's Homepage!

Hi there! I am a Ph.D. student at Computer Science & Artificial Intelligence Laboratory (CSAIL) at MIT, advised by Prof. Dina Katabi. Before coming to MIT, I received my B.S. degree with honors from Peking University.

My research interests lie in machine learning, deep learning, and their applications to advance digital health. I work on improving the robustness and generalization of machine learning models across underrepresented and out-of-distribution data to enable real-world capabilities at scale. I also develop novel learning algorithms and models to sense and understand human health with multimodal data.

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News

[03/2022] I have been selected as a Highlighted Reviewer (Top 8%) for ICLR 2022.

[06/2021] I received the 2021 MathWorks Ph.D. Fellowship.
[05/2021] Paper on imbalanced regression is accepted to ICML 2021 as a Long Talk (3%).

[09/2020] BodyCompass is covered by MIT News and featured on MIT front page.

[04/2020] My research on contactless human sleep sensing with AI has been used to let doctors monitor COVID-19 patients from a distance.
[12/2019] Paper on structured reinforcement learning is accepted to ICLR 2020 as an Oral Presentation (1.8%).

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Publications [Full List]

(* indicates equal contribution)

On Multi-Domain Long-Tailed Recognition, Generalization and Beyond
Yuzhe Yang, Hao Wang, Dina Katabi
arXiv Preprint, 2022
[Paper] • [Code] • [BibTeX]

Delving into Deep Imbalanced Regression
Yuzhe Yang, Kaiwen Zha, Ying-Cong Chen, Hao Wang, Dina Katabi
38^th International Conference on Machine Learning (ICML 2021)
Long Talk (top 3%)
[Paper] • [Project Page] • [Blog Post] • [Code] • [Slides] • [Talk] • [BibTeX]

Rethinking the Value of Labels for Improving Class-Imbalanced Learning
Yuzhe Yang, Zhi Xu
34^th Conference on Neural Information Processing Systems (NeurIPS 2020)
[Paper] • [Project Page] • [Blog Post] • [Code] • [Slides] • [Talk] • [BibTeX]

Sample Efficient Reinforcement Learning via Low-Rank Matrix Estimation
Devavrat Shah*, Dogyoon Song*, Zhi Xu*, Yuzhe Yang* (α-β order)
34^th Conference on Neural Information Processing Systems (NeurIPS 2020)
[Paper] • [arXiv] • [Talk (by Devavrat)] • [BibTeX]

Harnessing Structures for Value-Based Planning and Reinforcement Learning
Yuzhe Yang, Guo Zhang, Zhi Xu, Dina Katabi
8^th International Conference on Learning Representations (ICLR 2020)
Oral Presentation (top 1.8%)
[Paper] • [OpenReview] • [Project Page] • [Code] • [Slides] • [Talk] • [BibTeX]

When NAS Meets Robustness: In Search of Robust Architectures against Adversarial Attacks
Minghao Guo*, Yuzhe Yang*, Rui Xu, Ziwei Liu, Dahua Lin
IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2020)
[Paper] • [Project Page] • [Code] • [Slides] • [Poster] • [Talk] • [BibTeX]

BodyCompass: Monitoring Sleep Posture with Wireless Signals
Shichao Yue, Yuzhe Yang, Hao Wang, Hariharan Rahul, Dina Katabi
ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2020)
[Paper] • [Project Page] • [Slides] • [Talk] • [BibTeX] • [MIT News]

ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation
Yuzhe Yang, Guo Zhang, Dina Katabi, Zhi Xu
36^th International Conference on Machine Learning (ICML 2019)
[Paper] • [Project Page] • [Code] • [Slides] • [Poster] • [Talk] • [BibTeX]

ImgSensingNet: UAV Vision Guided Aerial-Ground Air Quality Sensing System
Yuzhe Yang, Zhiwen Hu, Kaigui Bian, Lingyang Song
IEEE International Conference on Computer Communications (INFOCOM 2019)
[Paper] • [Project Page] • [arXiv] • [Code] • [Video] • [BibTeX]

Real-Time Profiling of Fine-Grained Air Quality Index Distribution using UAV Sensing
Yuzhe Yang, Zijie Zheng, Kaigui Bian, Lingyang Song, Zhu Han
IEEE Internet of Things Journal (IoT-J), Feb. 2018
[Paper] • [arXiv] • [Video] • [BibTeX]
IEEE ComSoc Student Competition'17 Best Project (No.1)

Talks (Selected)

2022 @ Citadel Securities, PhD Summit: Delving into Deep Imbalanced Regression
2021 @ Tsinghua, AI TIME: Delving into Deep Imbalanced Regression
2021 @ NTU, MMLab: Rethinking Learning from Imbalanced Data
2021 @ TechBeat: Imbalanced Learning: From Semi-supervision, Self-supervision, to Deep Imbalanced Regression
2020 @ Johns Hopkins University, Artificial Intelligence Society: Algorithms & Applications for AI-driven Healthcare
2020 @ UC Berkeley, JiaoLab Group: Rethinking the Value of Labels for Improving Class-Imbalanced Learning

Honors and Awards (Selected)

MathWorks Ph.D. Fellowship, 2021-2022
Highlighted Reviewer (Top 8%), ICLR 2022
Best Undergraduate Dissertation Award, EECS Dept., Peking Univ., 2018
First Prize (No.1 out of 23 finalists), IEEE ComSoc Student Competition: Communication Technology Changing the World, 2017
National Scholarship (highest honor), The Chinese Government, 2017
HuaWei Scholarship, 2017
Samsung Scholarship, 2016

Professional Service

Conference Reviewer: NeurIPS, ICML, ICLR (Highlighted Reviewer), CVPR, ICCV, ECCV, IJCAI, AAAI, UAI
Program Committee Member: AAAI, IJCAI, UAI
Journal Reviewer: TMLR, IEEE TKDE, IEEE TVT, IEEE IoT-J

Press

BodyCompass was covered by: MIT News, Engadget, Yahoo, Technology Networks, Sleep Review, TechTimes, SlashGear, TechSpot, Hackster, New Atlas, BGR, and other media outlets.
COVID-19 Health Monitoring was covered by: CSAIL News, Tech Crunch, Engadget, VentureBeat, and other media outlets.

Contact

MIT Computer Science & Artificial Intelligence Lab
32-G928, 32 Vassar St., Cambridge, MA 02139
yuzhe [at] mit (dot) edu