About Me

I am a Tenure-Track Assistant Professor in the Department of Computer Science at Boston College. Previously, I was a Postdoctoral Research Associate at Computer Science & Artificial Intelligence Lab of Massachusetts Institute of Technology, working with Prof. Dina Katabi. Before MIT, I received my Ph.D. degree in Department of Electronic & Computer Engineering, Hong Kong University of Science and Technology. I was very fortunate to have Prof. Dit-Yan Yeung as my advisor. I was a visiting research scholar in The Robotics Institute of Carnegie Mellon University, working with Prof. Abhinav Gupta.

I am a WISDM speaker in MIT Office of Innovation. I am passionate about fostering STEM community diversity, equity, and inclusion through speaking, mentoring, teaching, academic collaborations, and outreach.

🔥🔥🔥 Recruiting:

Prospective students: I am currently seeking multiple highly motivated students to join my lab as postdocs, PhDs (Fall 2027, please submit your application through the official portal), undergraduates, and visiting students/scholars (in-person or remote). If interested, please complete this Google form and contact miayuanmit@gmail.com (cc yuanyua@bc.edu).

Research Interests:

• Multisensory AI & Generative AI: the development of bleeding-edge AI techniques aims to comprehend and make meaningful use of various data modalities, such as vision, Artificial Intelligence of Things (AIoT), language (including LLMs), and medical data, etc.
• AI for medicine, health, science: new digital biomarker discovery, contactless health monitoring, etc., to advance personalized medicine.
• Trustworthy & Safe AI: e.g., interpretability, robustness, alignment, etc.

News

• [11/2024] We are thrilled to have Zhutian Yang from MIT CSAIL give a talk titled "Generalizable Algorithms for Long-Horizon Manipulation in Complex Environments by Integrating Deep Learning and Planning-Based Approaches".
• [11/2024] We are thrilled to have Hao He from MIT CSAIL give a talk titled "Respiratory Intelligence: What Can AI Learn About Your Health from Your Breathing".
• [11/2024] We are thrilled to have Yifei Wang from MIT CSAIL give a talk titled "Towards Test-time Self-supervised Learning".
• [11/2024] We are thrilled to have Paul Liang from MIT Media Lab & EECS give a talk titled "Multimodal AI".
• [07/2024] One paper has been accepted by Nature Nanotechnology.
• [04/2024] We are thrilled to have Hao He from MIT EECS give a talk titled "Respiration Intelligence: Know Your Health from Your Breathing with an AI Assistant".
• [04/2024] We are thrilled to have Hanzi Mao from Nvidia Deep Imagination Research give a talk titled "Segment Anything".
• [04/2024] We are thrilled to have Guohao Li from University of Oxford give a talk titled "CAMEL: Communicative Agents for “Mind” Exploration of Large Language Model Society".
• [04/2024] We are thrilled to have Zifan Shi from Stanford / HKUST give a talk titled "Towards Efficient and High-Quality 3D Generation".
• [04/2024] We are thrilled to have Ge Yang from MIT CSAIL give a talk titled "Foundation Priors for Robot Perception: From Neural Radiance Fields to OpenAI Sora".
• [04/2024] We are thrilled to have Tianhong Li from MIT CSAIL give a talk titled "Learning to and from Predict in Computer Vision".
• [04/2024] We are thrilled to have Chunyuan Li from Microsoft Research give a talk titled "LLaVA: A Vision-and-Language Approach to Computer Vision in the Wild".
• [01/2024] Our paper "Continuous Invariance Learning" has been accepted to ICLR 2024.
• [01/2024] I join the Dept. of Computer Science as a Tenure-Track Assistant Professor at Boston College.
• [12/2023] I attend the NeurIPS conference in New Orleans, USA.
• [11/2023] I was invited to give a guest lecture for the COMP5511 Artificial Intelligence Concepts course at Hong Kong Polytechnic University in the Fall of 2023.
• [10/2023] I attend the ICCV conference in Paris, France.
• [07/2023] Our paper "TokenCut: Segmenting Objects in Images and Videos with Self-supervised Transformer and Normalized Cut" has been accepted to TPAMI.
• [05/2023] I was honored to be invited to give a guest lecture for the ROB-UY 3203 Robot Vision course at New York University in the Spring of 2023.
• [01/2023] AI-based biomarker for Parkinson's disease has been selected to Notable Advances 2022 by Nature Medicine, as one of the ten global breakthroughs and critical developments that moved medicine forward in 2022. Notable Advances 2022 are selected from all the papers of Nature, Science, Lancet, New England Journal of Medicine and their subsidiary journals, and all the reports of the World Health Organization (WHO).
• [01/2023] I co-organized workshop @ ICLR 2023 -- Machine Learning for IoT: Datasets, Perception, and Understanding.
• [10/2022] Attended the Nature Conference on Medicine in a Virtual Age.
• [08/2022] Our paper on AI-based biomarker for Parkinson's disease is published at Nature Medicine.
• [04/2022] Our poster has been accepted at AI Cures 2022.
• [03/2022] TokenCut and TSC have been accepted at CVPR 2022.
• [02/2022] Our paper "Self-Supervised Transformers for Unsupervised Object Discovery using Normalized Cut" is on arXiv.
• [11/2021] Our paper "Targeted Supervised Contrastive Learning for Long-Tailed Recognition" is on arXiv.
• [10/2021] Attended Microsoft Research Summit 2021, virtually.
• [10/2021] Our paper "Unsupervised Learning for Human Sensing Using Radio Signals" has been accepted at WACV 2022.
• [12/2020] Our paper "Addressing Feature Suppression in Unsupervised Visual Representations" is on arXiv.
• [11/2020] Attended Path of Professorship workshop, MIT, virtually.
• [09/2020] Our paper "Subgroup-based Rank-1 Lattice Quasi-Monte Carlo" has been accepted at NeurIPS 2020.
• [08/2020] RF-Diary was covered by: TechCrunch, Engadget, VentureBeat, DailyMail, Hot Hardware, BBC News, MIT CSAIL News, and other media outlets.
• [07/2020] RF-Diary has been accepted at ECCV 2020 as an oral presentation.
• [06/2020] RF-ReID was covered by: TechCrunch, Yahoo News, Healthcare IT News, MIT CSAIL News, and other media outlets.
• [02/2020] RF-ReID has been accepted at CVPR 2020.
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Selected Publications [Full List]

Continous Invariance Learning
Yong Lin*, Fan Zhou*, Lu Tan, Lintao Ma, Jiameng Liu, Yansu He, Yuan Yuan, Yu Liu, James Zhang, Yujiu Yang, and Hao Wang
(* indicates equal contribution)
International Conference on Learning Representations (ICLR), 2024
[PDF] [BibTeX]

Contactless Oxygen Monitoring with Radio Waves and Gated Transformer
Hao He*, Yuan Yuan*, Ying-Cong Chen*, Peng Cao and Dina Katabi
(* indicates equal contribution, order determined via a random coin flip)
Machine Learning for Healthcare (MLHC), 2023
[MLHC Version] [NeurIPSw Version] [BibTeX]

Artificial Intelligence-Enabled Detection and Assessment of Parkinson's Disease using Nocturnal Breathing Signals
Yuzhe Yang, Yuan Yuan, Guo Zhang, Hao Wang, Ying-Cong Chen, Yingcheng Liu, Christopher Tarolli, Daniel Crepeau, Jan Bukartyk, Mithri Junna, Aleksandar Videnovic, Terry Ellis, Melissa Lipford, Ray Dorsey, Dina Katabi ( indicates corresponding authors: yuzhe@mit.edu; miayuan@mit.edu)
Nature Medicine (2022)     2-year Impact Factor: 87.241     5-year Impact Factor: 68.310
[Paper] [Project Page] [Poster] [BibTeX]

🏆 2022 Top Ten Notable Advances in Medicine [Year In Review]

Covered by: MIT News, MIT CSAIL News, Forbes, Fierce Biotech, University of Rochester, STAT News, New Atlas, The Boston Globe, NVIDIA Technical Blog, Yahoo, FDA News, WBUR, American Council on Science and Health, NIH News, Health IT Analytics, Boston.com, Parkinson's News Today, The Washington Post, Futurity, BioSpace, Times of India, aerzteblatt.de, MedSpace, AzoRobotics, healthcare-in-europe, The Daily Beast, Indian Express, and more media outlets can be found at here.

TokenCut: Segmenting Objects in Images and Videos with Self-supervised Transformer and Normalized Cut
Yangtao Wang, Xi Shen, Yuan Yuan, Yuming Du, Maomao Li, Xu Hu, James Crowley, Dominique Vaufreydaz
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023
[Project Page] [PDF] [Arxiv] [BibTeX] [Code] Star

Addressing Feature Suppression in Unsupervised Visual Representations
Tianhong Li*, Lijie Fan*, Yuan Yuan, Hao He, Yonglong Tian, Rogerio Feris, Piotr Indyk and Dina Katabi
Winter Conference on Applications of Computer Vision (WACV), 2023
[PDF] [Talk (by Dina)] [BibTeX]

Self-Supervised Transformers for Unsupervised Object Discovery using Normalized Cut
Yangtao Wang, Xi Shen, Xu Hu, Yuan Yuan, James Crowley, Dominique Vaufreydaz
Computer Vision and Pattern Recognition (CVPR), 2022
[Project Page] [PDF] [BibTeX] [Code (GitHub)] [Code (GitLab)] Star

Targeted Supervised Contrastive Learning for Long-Tailed Recognition
Tianhong Li*, Peng Cao*, Yuan Yuan, Lijie Fan, Yuzhe Yang, Rogerio Feris, Piotr Indyk and Dina Katabi
Computer Vision and Pattern Recognition (CVPR), 2022
[PDF] [BibTeX] [Code] Star

Unsupervised Learning for Human Sensing Using Radio Signals
Tianhong Li*, Lijie Fan*, Yuan Yuan* and Dina Katabi
(* indicates equal contribution)
Winter Conference on Applications of Computer Vision (WACV), 2022
[PDF] [Poster] [BibTeX]

Subgroup-based Rank-1 Lattice Quasi-Monte Carlo
Yueming Lyu, Yuan Yuan and Ivor W. Tsang
Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS), 2020
[Paper] [Supplemental] [arXiv] [Poster] [BibTeX]

In-home Daily-Life Captioning Using Radio Signals
Lijie Fan*, Tianhong Li*, Yuan Yuan and Dina Katabi
European Conference on Computer Vision (ECCV), 2020
[Project Page] [PDF] [arXiv] [Slides] [MIT CSAIL Video] [Video] [Talk] [BibTeX]
Covered by: MIT CSAIL News, BBC, TechCrunch, Engadget, VentureBeat, Daily Mail, Hot Hardware, Xataka (Mexico)
Oral Presentation (2%)

Learning Longterm Representations for Person Re-Identification Using Radio Signals
Lijie Fan*, Tianhong Li*, Rongyao Fang*, Rumen Hristov, Yuan Yuan and Dina Katabi
Computer Vision and Pattern Recognition (CVPR), 2020
[Project Page] [PDF] [arXiv] [Video] [BibTeX]
Covered by: MIT CSAIL News, TechCrunch, Yahoo News, Healthcare IT News, Medical Device and Diagnostic Industry

Marginalized Average Attentional Network For Weakly-Supervised Learning
Yuan Yuan, Yueming Lyu, Xi Shen, Ivor W. Tsang and Dit-Yan Yeung
International Conference on Learning Representations (ICLR), 2019
[PDF] [Code] [BibTeX] Star

Efficient Batch Black-box Optimization with Deterministic Regret Bounds
Yueming Lyu, Yuan Yuan and Ivor W. Tsang
Under Review (JMLR), 2019
[arXiv] [BibTeX]

Temporal Dynamic Graph LSTM for Action-driven Video Object Detection
Yuan Yuan, Xiaodan Liang, Xiaolong Wang, Dit-Yan Yeung and Abhinav Gupta
International Conference on Computer Vision (ICCV), 2017
[PDF] [Dataset] [BibTeX]

Adaptive Block Coding Order for Intra Prediction in HEVC
Amin Zheng, Yuan Yuan, Jiantao Zhou, Yuanfang Guo, Haitao Yang and Oscar C. Au
IEEE Transaction on Circuits and Systems for Video Technology, vol.26, no.11, pp.2152-2158, Nov. (TCSVT), 2016
[PDF] [BibTeX]

Image Compression Via Dense Descriptors Assisted Synthesis
Yuan Yuan, Amin Zheng, Haitao Yang and Oscar C. Au
International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015
[PDF] [BibTeX]
Oral Presentation

Motion Vector Fields Based Video Coding
Amin Zheng, Yuan Yuan, Hong Zhang, Haitao Yang, Pengfei Wan and Oscar C. Au
International Conference on Image Processing (ICIP), 2015
[PDF] [BibTeX]

Motion Estimation Via Hierarchical Block Matching and Graph Cut
Amin Zheng, Yuan Yuan, Sunil Prasad Jaiswal and Oscar C. Au
International Conference on Image Processing (ICIP), 2015
[PDF] [BibTeX]

Image Colorization Via Color Propagation and Rank Minimization
Yonggen Ling, Oscar C. Au, Jiahao Pang, Jin Zeng, Yuan Yuan and Amin Zheng
International Conference on Image Processing (ICIP), 2015
[PDF] [BibTeX]

Image Compression Via Sparse Reconstruction
Yuan Yuan, Oscar C. Au, Amin Zheng and Haitao Yang
International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2014
[PDF] [Poster] [BibTeX]

Natural Image Matting via Adaptive Local and Nonlocal Sample Clustering
Haiyan Yang, Oscar C. Au, Yuan Yuan and Wenxiu Sun
International Conference on Image Processing (ICIP), 2014
[PDF] [BibTeX]
Top 10% Paper Award

Posters & Technical Reports

Radiofrequency-based Wireless and Contactless Sensors for Detection of Seizures and Risk Factors of SUDEP
Hernan Nicolas Lemus, Hao He, Yuan Yuan, Steven Tobochnik, Emily Lapinskas, Dina Katabi and Jong Woo Lee
American Epilepsy Society (AES) Annual Meeting, Nashville, USA, 2022
[Poster]

Patents and Patent Applications

• Voice interaction system, related method, device and equipment
Yuan Yuan, Yuxiang Hu, Feijun Jiang.
Chinese Patent CN113160854 | 202010085433.7 | priority date: Jan 22, 2020


• Voice processing method, model training method, interface display method and equipment
Yuan Yuan, Yuxiang Hu, Feijun Jiang.
Chinese Patent CN112825248 | 201911134195.8 | priority date: Nov 19, 2019


• Method and device for processing action behaviors in video
Yuan Yuan, Lin Ma, Zequn Jie, Wei Liu.
Chinese Patent CN110096938 | 201810098321.8 | priority date: Jan 31, 2018


• Encoding and decoding methods and apparatuses
Haitao Yang, Amin Zheng, Yuan Yuan, Oscar Au.
Chinese Patent CN104853196 | 201410054130.3 | priority date: Feb 18, 2014 | publication date: Oct 19, 2018.
Korean Patent KR101960825 | KR1020167023765 | priority date: Feb 02, 2015 | publication date: Mar 21, 2019.
Japanese Patent JP6389264 | 2016-552562 | priority date: Feb 02, 2015｜publication date: Sep 12, 2018.
European Patent EP3094091A4 | EP15752321.8 | priority date: Feb 02, 2015
WIPO (PCT) WO2015124058 | PCT/CN2015/072089 | priority date: Feb 02, 2015
US Patent US20160373767 | US15/240,436 | priority date: Feb 02, 2015

Press Coverage

• AI-based Biomarker for Parkinson's Disease using Nocturnal Breathing was covered by: MIT News, MIT CSAIL News, Forbes, Fierce Biotech, University of Rochester, STAT News, New Atlas, The Boston Globe, NVIDIA Technical Blog, Yahoo, FDA News, WBUR, American Council on Science and Health, NIH News, Health IT Analytics, Boston.com, Parkinson's News Today, The Washington Post, Futurity, BioSpace, Times of India, aerzteblatt.de, MedSpace, AzoRobotics, healthcare-in-europe, The Daily Beast, Indian Express, and and other media outlets.
• In-Home Daily-Life Captioning Using Radio Signals was covered by: MIT CSAIL News, BBC, TechCrunch, Engadget, VentureBeat, Daily Mail, Hot Hardware, Xataka (Mexico), and other media outlets.
  
• Learning Longterm Representations for Person Re-Identification Using Radio Signals was covered by: MIT CSAIL News, TechCrunch, Yahoo News, Healthcare IT News, Medical Device and Diagnostic Industry, and other media outlets.

Teaching

Courses

• CSCI 3345: Machine Learning, Boston College, Fall 2026 [Course Website]
• CSCI 1101: Computer Science I, Boston College, Spring 2026
• CSCI 3370: Deep Learning, Boston College, Fall 2025 [Course Website]
• CSCI 3345: Machine Learning, Boston College, Spring 2025 [Course Website]
• CSCI 3370: Deep Learning, Boston College, Fall 2024 [Course Website]
• CSCI 3399: Vision and Learning, Boston College, Spring 2024 [Course Website]

Lectures

• COMP 5511: Artificial Intelligence Concepts, Hong Kong Polytechnic University, Guest Lecture, Fall 2023
• Deep Generative Modeling, Nanyang Technological University, Teaching Seminar, May 2023
• ROB-UY 3203: Robot Vision, New York University, Guest Lecture, Spring 2023

Teaching Assistant

• EESM 5547: Multimedia Signal Processing, HKUST, Fall 2014
• ELEC 1200: A System View of Communications: from Signals to Packets, HKUST, Fall 2013
• ELEC 1200: A System View of Communications: from Signals to Packets, HKUST, Spring 2012

Mentorship

I am fortunate to have worked with a group of talented students and collaborators.

Student Awards and Honors

• Lejun R. Liao: CRA Outstanding Undergraduate Researcher Award, Honorable Mention, 2026

Alumni

• Lejun R. Liao: BC Undergraduate → UCSD M.S.
• Shuang Liang: Wuhan University B.S. → HKU Ph.D.
• Xianghong Fang: HKUST M.Phil. → University of Toronto Ph.D.
• Shiyuan (Sean) Zhang: UIUC M.S. → University of Virginia Ph.D.
• Ruolong Mao: BC Undergraduate → UIUC M.S.
• Yunhan Liu: BC Undergraduate → University of Michigan M.S.
• Riteng Zhang: BC Undergraduate → Purdue Ph.D.
• Bo Jiang: BC Undergraduate → CMU Robotics M.S.
• Zhi Xu: BC Undergraduate → UPenn M.S.
• Junye Pan: BC Undergraduate → UIUC M.S.
• Matthew Eichelman: BC Undergraduate → University of Minnesota, Twin Cities Ph.D.
• Sean (Seunghwan) Cha: HKUST CSE Undergraduate → CMU Robotics M.S.
• Shuhao Fu: HKUST CSE Undergraduate → UCLA Ph.D.
• Yangtao Wang: Ph.D. Student at Université Grenoble Alpes, France

Academic Services

• Workshop Service
  GenAI for Health: Agentic Systems, Clinical Trust, and Future Potential — PC Member, NeurIPS 2026

  First Workshop on Agent Skills — PC Member, ACM CAIS 2026

  GenAI for Health: Potential, Trust, and Policy Compliance — PC Member, NeurIPS 2025

  Machine Learning for IoT: Datasets, Perception, and Understanding — Organizer, ICLR 2023 [Website]

  Learning with Limited Labelled Data for Image and Video Understanding — PC Member, CVPR 2022

  PAIR²Struct: Privacy, Accountability, Interpretability, Robustness, Reasoning on Structured Data — PC Member, ICLR 2022

  First Workshop on Statistic Deep Learning in Computer Vision — PC Member, ICCV 2019
• Conference Program Committee Member/Reviewer:
IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
IEEE International Conference on Computer Vision (ICCV)
International Conference on Machine Learning (ICML)
Neural Information Processing Systems (NeurIPS)
International Conference on Learning Representations (ICLR)
European Conference on Computer Vision (ECCV)
International Conference on Artificial Intelligence and Statistics (AISTATS)
Annual Meeting of the Association for Computational Linguistics (ACL)
AAAI Conference on Artificial Intelligence (AAAI)
Winter Conference on Applications of Computer Vision (WACV)
International Joint Conferences on Artificial Intelligence (IJCAI)

• Journal Reviewer
IEEE Transactions on Image Processing (TIP)
IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
IEEE Transactions on Multimedia (TMM)
IEEE Transactions on Neural Networks and Learning Systems (TNNLS)

Selected Honors and Awards

• Rising Stars in AI Symposium 2023 at KAUST, 2023. (Being selected to give a talk, but unable to attend in person due to visa issues)
• 2022 Top Ten Notable Advances in Medicine, Nature Medicine, 2022. [Details]
• Ali Star, Alibaba Group, 2019.
• Research Travel Grant, CMU, ICCV 2017.
• Overseas Research Award for conducting research at Carnegie Mellon University, HKUST, 2016.
• Research Travel Grant, HKUST, 2014, 2015, 2017.
• Meritorious Winner, Mathematical Contest in Modeling of America (MCM), 2011.
• Microsoft Young Fellowship, Microsoft Research Asia, 2011.
• National Scholarship (top 0.2%, highest honor), Ministry of Education of P.R.China, 2009, 2010, 2011.
• Merit Scholarship (top 0.05%, highest honor), HUST, 2011
• First-Class Scholarship (top 5%), HUST, 2009, 2010, 2011