Please go to my new page: http://people.csail.mit.edu/winstonchen/

Bio:

Wenqiang (Winston) Chen is a Ph.D. candidate at the University of Virginia working with Professor John Stankovic. (Joining MIT EECS as a Postdoctoral Associate this fall, working with Wojciech Matusik and Dina Katabi.) His research lies at the intersection of Cyber-Physical Systems (CPS), ubiquitous and mobile sensing, and human-computer interaction (HCI). In particular, his research specializes in developing Vibration Interaction (VibInt) systems to perceive and infer information from human bodies, robots, and environments through vibrations. VibInt has been proposed to advance a wide variety of research areas, such as wearable interactions, robotics, smart health, smart homes, privacy and security. He has published his research in various top conferences and journals (e.g., Mobicom, Ubicomp, and Transactions on Mobile Computing), obtained five patents, and won the IEEE SECON 2018 Best Paper Award and the ACM SenSys 2020 Best Demo Award. Winston is also a co-founder of VibInt AI, a startup working on wearable devices using VibInt technologies, and his research IPs have been used in thousands of commodity devices.


Research Vision: Uniting People, Bits, and Atoms through Vibrational Interaction

All physical phenomena, even heartbeats, cause vibrations, spreading through media from human bodies, to machines, infrastructures, and even oceans. Rich information from these vibrations can be recognized by different sensors, including cameras, lasers, and accelerometers. Exploiting ubiquitous sensors and Artificial Intelligence, VibInt systems sense, understand, and interact with people and the physical world through universal vibrations. For example, VibInt captures subtle on-body vibrations to control smartwatches, smart glasses, and ubiquitous computers via typing on the skin and writing in the air. Also, VibInt can distinguish keystroke vibrations to authenticate users and enable password recovery in security research. Furthermore, VibInt detects passive building vibrations to localize pedestrians and monitor human activities in smart homes. Additionally, VibInt assists robotic fish in exploring various habitats by analyzing and recognizing water flow vibrations. The mission of my research is to integrate human, cyber, and physical experiences into an intelligent world of vibrational interactions.


Current Work: Harnessing Vibrations for Fine-grained Finger Interactions with a Commodity IMU Sensor

This research has created technology for next-generation smart devices, like watches and glasses. Specifically, I harness subtle finger induced vibrations for intelligent interactions and have designed a novel adversarial neural network to mitigate human body variations. This new technology is called ViWatch, and it is able to recognize finger typing and writing induced vibrations with accuracy, even when users are in different states of motion or in noisy environments. It won IEEE SECON Best Paper Award, ACM SenSys Best Demo Award, and the Link Lab Student Seminar Award (single awardee), which is the highest award in recognition of excellence in CPS research at a 200+ person lab. “Winston's work on using vibrations detected by smart watches is broad and deep and is first rate," said by the the director of UVA Engineering's Link Lab, “The work enables the use of very low amplitude vibrations even in the presence of non-target vibrations, for example picking up target finger tapping vibrations on the knuckles of a hand even while walking."

    

News:


Entrepreneurship:

I co-founded a startup company in 2019, VibInt AI, which leverages the IP from my research. VibInt AI was selected to join HKAI Lab Accelerator Program, which is fully funded by Alibaba and SenseTime. VibInt AI received first round funding and sold 10,000 + devices. Cooperating with MAD Gaze, VibInt launched smartwatches with the IP from my research on the crowdfunding platform Indiegogo, which exceeded the crowdfunding target amount by 27 times. I also attended CES 2019 to demonstrate our products.

Honors and Awards:


Representative Papers:

ViFin: Harness Passive Vibration to Continuous Micro Finger Writing with a Commodity Smartwatch.
Wenqiang Chen, Lin Chen, Meiyi Ma, Farshid Salemi Parizi, Shwetak Patel, John Stankovic.
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2021. (acceptance rate 23%, CORE Rank: A*)


SenseCollect: We Need Efficient Ways to Collect On-body Sensor-based Human Activity Data!
Wenqiang Chen, Shupei Lin, Elizabeth Thompson, John Stankovic.
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2021. (acceptance rate 23%, CORE Rank: A*)

Taprint: Secure Text Input for Commodity Smart Wearables.
Wenqiang Chen, Lin Chen, Yandao Huang, Xinyu Zhang, Lu Wang, Rukhsana Ruby, Kaishun Wu.
The Annual ACM International Conference on Mobile Computing and Networking, 2019. (acceptance rate 18.9%, CORE Rank: A*)


ViType: A Cost Efficient On-body Typing System through Vibration.
Wenqiang Chen, Maoning Guan, Yandao Huang, Lu Wang, Rukhsana Ruby, Wen Hu, Kaishun Wu.
The Annual IEEE International Conference on Sensing, Communication and Networking, 2018. (Best Paper Award, 1/211) (acceptance rate 23.2%)

Other Publications:

ViObject: A Smartwatch-based Object Recognition System via Vibrations. (Demo)
Wenqiang Chen, Daniel Bevan, John Stankovic.
In The Adjunct Publication of the 34th Annual ACM Symposium on User Interface Softwareand Technology, 2021.
Machine Learning Introduction for Newbies (invited workshop)
Wenqiang Chen, John Stankovic.
IEEE Systems and Information Engineering Design Symposium (SIEDS), 2021.
Vibration Intelligence: Bringing Machine Perception Beyond the Human-Like. (poster abstract)
Wenqiang Chen, John Stankovic.
ACM SIGBED Student Research Competition at CPS-IoT Week, 2021.
Tuna Robotics: Using Machine Learning and Interial Measurement Sensors for Sensory Feedback During Swimming. (abstract)
Wenqiang Chen, Joseph Zhu, John Stankovic, George V. Lauder, Hilary Bart-Smith
The Society for integrative and comparative biology, 2021.
(Best Demo Award) Demo Abstract: A Smartwatch Product Provides On-body Tapping Gestures Recognition.
Wenqiang Chen, Lin Chen, Kenneth Wan, and John Stankovic.
In The 18th ACM Conference on Embedded Networked Sensor Systems, November 16–19, 2020, Virtual Event, Japan.


Demo Abstract: Continuous Micro Finger Writing Recognition with a Commodity Smartwatch.
Wenqiang Chen, Lin Chen, Meiyi Ma, Farshid Salemi Parizi, Patel Shwetak, and John Stankovic.
In The 18th ACM Conference on Embedded Networked Sensor Systems, November 16–19, 2020, Virtual Event, Japan.


Power Saving and Secure Text Input for Commodity Smart Watches.
Kaishun Wu, Yandao Huang, Wenqiang Chen, Lin Chen, Xinyu Zhang, Lu Wang, Rukhsana Ruby.
IEEE Transactions on Mobile Computing, 2020.
A Low Latency On-body Typing System through Single Vibration Sensor.
Wenqiang Chen, Maoning Guan, Yandao Huang, Lu Wang, Rukhsana Ruby, Wen Hu, Kaishun Wu.
IEEE Transactions on Mobile Computing, 2019.
G-Fall: Location-assisted Training-free Fall Detection with Geophones.
Yandao Huang*, Wenqiang Chen*, Hongjie Chen, Lu Wang, and Kaishun Wu.(*Joint first authors)
The Annual IEEE International Conference on Sensing, Communication and Networking, 2019.
FaceInput: A Hand-Free and Secure Text Entry System through Facial Vibration.
Maoning Guan, Wenqiang Chen, Yandao Huang, Rukhsana Ruby, Kaishun Wu.
The Annual IEEE International Conference on Sensing, Communication and Networking, 2019.
Demo: Virtual Keyboard for Wearable Wristbands.
Wenqiang Chen, Yanming Lian, Lu Wang, Rukhsana Ruby, Wen Hu, Kaishun Wu.
The ACM Conference on Embedded Networked Sensor Systems, 2017.
FLoc: Device free Passive Indoor Localization in Complex Environments.
Wenqiang Chen, Maoning Guan, Lu Wang, Rukhsana Ruby, Wen Hu, Kaishun Wu.
The IEEE International Conference on Communications, 2017.