I am a Ph.D. student at MIT CSAIL. My advisor is Prof. Dina Katabi. My research focuses on Wireless Sensing Systems with AI, as well as their applications for human and planet health. My research draws on tools from wireless systems, computer vision and machine learning.

I have also worked with Dr. Ranveer Chandra at Microsoft, and Prof. Tai Sing Lee at CMU. Before coming to MIT, I recieved my Bachelor degree in 2015 from Peking University working with Prof. Yizhou Wang and Prof. Fan Ye.



Recent News:

  • I spent a great summer at Microsoft working on a seeing-through-clouds technology for Earth observation (stay tuned).
  • Two papers on through-wall human mesh recovery and human activity recognition accepted at ICCV 2019.
  • We present a real-time demo of Through-Wall 3D Human Pose Estimation at SIGCOMM 2018.
  • Our work on learning 3D Human Pose with wireless and vision systems is accepted at SIGCOMM 2018.
  • Through-Wall Human Pose Estimation is accepted at CVPR 2018 as a spotlight presentation.
  • EQ-Radio is featured in CACM Research Highlights.
  • EQ-Radio received ACM SIGMOBILE Research Highlights of 2017.
  • Our emotion detection technology is the topic of an entire episode in The Big Bang Theory.
  • Publications:



    RF-Based 3D Skeletons
    M. Zhao, Y. Tian, H. Zhao, M. Alsheikh, T. Li, R. Hristov, Z. Kabelac, D. Katabi and A. Torralba
    ACM SIGCOMM, 2018
    [PDF] [Website] [Video] [Slides]


    Enabling Identification and Behavioral Sensing in Homes using Radio Reflections
    C. Hsu, R. Hristov, Guang-He Lee, M. Zhao, and D. Katabi
    ACM Conference on Human Factors in Computing Systems (ACM CHI), 2019
    [PDF] [Website] [Video]

    Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profiling
    H. Wang, C. Mao, H. He, M. Zhao, D. Katabi and T. Jaakkola
    AAAI Conference on Artificial Intelligence (AAAI), 2019
    [PDF] [Supp] [MIT News]


    Emotion Recognition using Wireless Signals
    M. Zhao, F. Adib and D. Katabi
    ACM International Conference on Mobile Computing and Networking (MobiCom), 2016
    [PDF] [Website] [Video] [Slides] [MIT News] [The Big Bang Theory episode]
    ACM SIGMOBILE Research Highlights
    CACM Research Highlights

    VeTrack: Real Time Vehicle Tracking in Uninstrumented Indoor Environments
    M. Zhao, R. Gao, T. Ye, F. Ye, Y. Wang and G. Luo
    ACM Conference on Embedded Networked Sensor Systems (SenSys), 2015
    [PDF]

    Predictive Encoding of Contextual Relationships for Perceptual Inference, Interpolation and Prediction
    M. Zhao, C. Zhuang, Y. Wang and T.S. Lee
    International Conference on Learning Representations (ICLR), 2015
    [PDF]

    Jigsaw: Indoor Floor Plan Reconstruction via Mobile Crowdsensing
    R.Gao, M. Zhao, T. Ye, F. Ye, Y. Wang, K. Bian, T. Wang and X. Li
    ACM International Conference on Mobile Computing and Networking (MobiCom), 2014
    [PDF]

    Smartphone-based Real Time Vehicle Tracking in Indoor Parking Structures
    R. Gao, M. Zhao, T. Ye, F. Ye, Y. Wang and G. Luo
    IEEE Transactions on Mobile Computing, 2017
    [PDF]

    Multi-story Indoor Floor Plan Reconstruction via Mobile Crowdsensing
    R.Gao, M. Zhao, T. Ye, F. Ye, Y. Wang, K. Bian, T. Wang and X. Li
    IEEE Transactions on Mobile Computing, 2016
    [PDF]

    Poster Abstract: VeLoc: Finding Your Car in the Parking Lot
    M. Zhao, R. Gao, J. Zhu, T. Ye, F. Ye, Y. Wang, K. Bian, M. Zhang and G. Luo
    ACM Conference on Embedded Networked Sensor Systems (SenSys), 2014
    [PDF]

    Text Detection and Localization from Complex Background
    M. Zhao, and Y. Chen
    International Joint Workshop on Machine Perception and Robotics (MPR), 2013

    Press:


    Through-Wall Human Pose Estimation was covered by: MIT News, Technology Review, BBC, Forbes, Fox, Wired, Science Daily, iMore, CSO, Electronics 360, Economic Times, Live Mint, Geek, ZDNet, Engadget, Inverse, Gizmodo, Extreme Tech, GearBrain, Alphr and other media outlets.

    Learning Sleep Stages from Radio Signals was covered by: MIT News, Science, TechCrunch, Digital Trends, Gizmodo, IEEE Spectrum, PCMag, Science Daily, Engadget, DailyMail, TrendinTech, New Atlas, Boston Globe, Medgadget, Electronics360, TNW, Boston Bussiness Journal and other media outlets.

    Emotion Recognition using Wireless Signals was covered by: MIT News, The Wall Street Journal‎, Forbes, IEEE Spectrum, CBC, CCTV, CNN, CBS, Popular Science, Scientific American, Gizmodo, Business Insider, Fast Company, Engadget, Futurism, TechRepublic, TechCrunch, Consumerist, and other media outlets.


    Contact:

    MIT Computer Science & Artificial Intelligence Lab
    32 Vassar Street, 32-G918
    Cambridge, MA 02139
    mingmin@mit.edu
    [Google Scholar]