Hanchuan Li
Bio
I am a Principal Researcher at Microsoft Mixed Reality. I have broad research and engineering interest in the field of AR/VR, including machine learning, interaction techniques, computer vision and graphics, ubiquitous computing and streaming technologies. I specialize in prototyping, incubation as well as transforming state-of-the-art research into practical engineering solutions. I'm a fast learner who brings clarity to challenging problems through first principles. I enjoy building futuristic technologies collaborating with and learning from my wonderful colleagues. My work in the last decade has resulted in high impact products, platforms, and highly-cited research publications.
Skills: Machine Learning, Human-Computer Interaction, Computer Vision, Computer Graphics, Ubiquitous Computing,
Signal Processing, Python, C\#, C, Matlab, Unity.
Past Projects
I invented various sensing and interaction techniques to blur the line between physical and virtual experiences.
DeviceAR: Techniques for Device-oriented Augmented Reality Interactions
IDCam: Precise Item Identification for AR Enhanced Object Interactions
PaperID: A Technique for Drawing Functional Battery-Free Wireless Inter- faces on Paper.
MoveVR: Enabling Multiform Force Feedback in Virtual Reality using Household Cleaning Robot
IDSense: A Human-Object Interaction Detection System Based on Passive UHF RFID.
ID-Match: A hybrid computer vision and RFID system for recognizing individuals in groups.
FlexTouch: Enabling Large-Scale Interaction Sensing Beyond Touchscreens Using Flexible and Conductive Materials
ShopSight: A Retail Analytics Platform Tracking Consumer Behaviors in Physical Stores.
Professional Experience
JULY 2018 - PRESENT
Principal Researcher, Microsoft, Redmond, USA
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Tech lead on the Microsoft Meta partner project, delivering interaction and graphics techniques for streaming immersive experiences. | News
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Tech lead scaling deep learning hyper parameter tuning techniques (Microsoft NNI) for computer vision products with 100M+ revenue.
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Created statistical and machine learning techniques for detecting traffic anomalies at scale.
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Created techniques allowing HoloLens to interact with ambient devices using holographic interfaces | Demo | Paper
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Developed sensing solutions for intelligent retail stores. | News
SEPT 2013 - JUNE 2018
Graduate Researcher, The Ubicomp Lab, University of Washington, Seattle, USA
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Exploring novel sensing and interaction techniques for smart environments and IoT devices.
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Faculty Collaborators: Dr. Shwetak Patel, Dr. Alanson Sample.
MAY 2017 - MAY 2018
Co-Founder, ShopSight Technologies, Seattle, USA
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ShopSight is a data analytic platform that tracks fine‐granular in‐store consumer data, allowing brick and mortar to make data‐driven decisions.
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Winner of Jones Foster Accelerator Award, Best Retail Innovation UW Biz Plan Competition, 2nd Place Award GIX Innovation Competition.| Demo
JULY - OCTOBER, 2016
Research intern, Microsoft Research, Sensors and Devices Group, Cambridge, UK
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Mentors: Dr. Tobias Grosse-Puppendahl, Dr. James Scott
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Developed novel IR based solutions for user presence sensing and localization | Demo
JUNE - SEPTEMBER 2014-2015
Research Intern, Wireless Systems Group, Disney Research, Pittsburgh, USA
OCTOBER 2012 - MARCH 2013
Research Intern, HCI Group, Microsoft Research, Beijing, China
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Mentor: Dr. Koji Yatani
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Designed and implemented a novel insole sensing system recognizing body posture based on foot pressure distributions.
Key Publications
IDCam: Precise Item Identification for AR Enhanced Object Interactions
Hanchuan Li, Eric Whitmire, Alex Mariakakis, Victor Chan, Alanson Sample, Shwetak Patel.
In the Proceedings of the 2019 IEEE International Conference on RFID (IEEE RFID 2019)
IDAct: Towards Unobtrusive Recognition of User Presence and Daily Activities.
Hanchuan Li, Chieh-yih Wan, Rahul C. Shah, Alanson P. Sample, Shwetak Patel 2019. In the Proceedings
of the 2019 IEEE International Conference on RFID (IEEE RFID 2019)
PaperID: A Technique for Drawing Functional Battery-Free Wireless Inter- faces on Paper.
Hanchuan Li, Eric Brockmeyer, Elizabeth Carter, Josh Fromm, Scott Hudson, Shwetak Patel, Alanson Sample.
In The Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI16)
ID-Match: A hybrid computer vision and RFID system for recognizing individuals in groups.
Hanchuan Li, Peijin Zhang, Samer Al Moubayed, Alanson Sample, Shwetak Patel. 2016.
In the Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI16)
IDSense: A Human Object Interaction Detection System Based on Passive UHF RFID
Hanchuan Li, Can Ye, and Alanson Sample. 2015.
In the Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI15)
Enabling Sensing and Interaction with Everyday Objects
Hanchuan Li
In the Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology (UIST17 DS)
FlexTouch: Enabling Large-Scale Interaction Sensing beyond Touchscreens using Flexible and Conductive Materials
Yuntao Wang, Jianyu Zhou, Hanchuan Li, Tengxiang Zhang, Minxuan Gao, Zhuolin Cheng, Chun Yu, Shwetak Patel. In Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 3.3 (2019): 1-20.
MoveVR: Enabling Multiform Force Feedback in Virtual Reality using Household Cleaning Robot.
Wang, Yuntao, Zichao Chen, Hanchuan Li, Zhengyi Cao, Huiyi Luo, Tengxiang Zhang, Ke Ou et al. In Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 2020 (CHI 20).
Patents
Honors and Awards
SEPTEMBER, 2016
Qualcomm Innovation Fellowship
Qualcomm Inc.
SEPTEMBER, 2017
Second Place Award
GIX Innovation Competition
Global Innovation Exchange
OCTOMBER, 2017
People's Choice Award
UIST Doctoral Symposium Poster Session
SEPTEMBER, 2015
Disney Graduate Fellowship
Disney Research
SEPTEMBER, 2016
Third Place Award
GIX Innovation Competition
Global Innovation Exchange
April, 2018
Awardee
Jones Foster Accelerator
JUNE, 2010, 2011, 2012
Outstanding Student Scholarship
University of Science and
Technology of China
APRIL, 2019
Best Paper Nominee
2019 IEEE International Conference on RFID
Nov, 2017
Best Retail Innovation,
University of Washington Business Plan Competition
