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Mingmin Zhao

MIT Computer Science & Artificial Intelligence Lab
32 Vassar Street, 32-268
Cambridge, MA 02139
mingmin@mit.edu

Google Scholar / DBLP


About:

I am a Ph.D. student at MIT CSAIL. My advisor is Prof. Dina Katabi. I design and build wireless sensing systems with custom neural models to enable novel sensing capabilities and services. My approach draws on tools from diverse areas, including wireless systems, signal processing, computer vision, machine learning, and medicine. My research interprets radio reflections from the environment to sense human poses, actions, body shapes, emotions, vital signs, sleep physiology, etc. I also develop new digital biomarkers and health solutions that monitor people's health and well-being without physical contact. I have also worked with Dr. Ranveer Chandra at Microsoft Research, where I developed an Earth observation system that provides daily cloud-free satellite images for digital agriculture and environmental monitoring.

Before coming to MIT, I recieved my Bachelor degree in 2015 from Peking University, where I worked on mobile systems with Prof. Yizhou Wang and Prof. Fan Ye. I have also worked with Prof. Tai Sing Lee at CMU.

2020-2021: I am currently on the academic job market.


News:


Videos:

Through-Wall Human Pose Estimation

Contactless Sleep Monitoring

Wireless Emotion Recognition


Publications:

SpaceEye: Seeing Through Clouds in Satellite Images
M. Zhao, P. Olsen and R. Chandra
(in submission)


Assessment of Medication Self-Administration using Artificial Intelligence
M. Zhao*, K. Hoti*, H. Wang, A. Raghu and D. Katabi
Nature Medicine (2021) / Paper






Enabling Identification and Behavioral Sensing in Homes using Radio Reflections
C.Y. Hsu, R. Hristov, G.H. Lee, M. Zhao, and D. Katabi
ACM CHI 2019 / Paper / 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 2019 / Paper / Supp / MIT News


Emotion Recognition using Wireless Signals
M. Zhao, F. Adib and D. Katabi
ACM MobiCom 2016 / Paper / Website / Video / Slides / MIT News / The Big Bang Theory
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 SenSys 2015 / Paper

Predictive Encoding of Contextual Relationships for Perceptual Inference, Interpolation and Prediction
M. Zhao, C. Zhuang, Y. Wang and T.S. Lee
ICLR 2015 / Paper

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 MobiCom 2014 / Paper

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, 16(7), 2017 / Paper

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, 15(6), 2016 / Paper

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 SenSys 2014 / Poster


In the Press:

COVID-19 patient monitoring was covered by: CSAIL news, TechCrunch, Engadget, VentureBeat, etc.
Through-Wall Human Action Recognition was covered by: MIT Technology Review, TechCrunch, Communal News, Synced Review, etc.
In-Home Identification and Behavioral Sensing was covered by: MIT news, World Economic Forum, EurekAlert, India TV, and other media outlets.
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, etc.
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, etc.
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, etc.