Recent News

  • Nov. 2023, One paper is accepted by IMWUT 2023, issue 4. We proposed a drift-free approach for sensing motions. We will present this work at UbiComp 2024, stay tuned!
  • Oct. 2023, METRO is accepted by SenSys 2023. This is the first paper by my student Jike! METRO demonstrated how magnetic sensing can make our roads safer!
  • Sept. 2023, I will be serving in the TPC for MobiCom 2023.
  • Mar. 2023, VeFi received the Best Paper Award at the Inaugural ISOC Symposium on Vehicle Security and Privacy (VehicleSec 2023)!
  • Nov. 2022, I will be serving on the TPC of MobiSys 2023.
  • Sept. 2022, our work on Automatic Calibration of MEMS Magnetometer is accepted by MobiCom 2022, congrats to our leading authors Qing (also my first MS. student) and Mingke!
  • Aug. 2022, I will be serving in MobiCom 2023 PC. Please submit your works!
  • Mar. 2022, Enabling Software-defined PHY for Backscatter Networks is accepted by MobiSys 2022, congrats to the team!
  • Jul. 2021, I will be serving in the TPC for MobiCom 2022.
  • May 2021, Our magnetic tracking paper got accepted by MobiCom 2021! Congratulations to the team!
  • Jan. 2021, One paper on authenticating drivers using batteries is accepted by IMWUT/UbiComp.

Research works at CyPhy

At CyPhy, we build new technologies for solving real-world problems. Exemplary usage scenarios fall in smart transportation and healthcare.


(Underlined authors are my direct advisees, '*' denotes co-primary authors)

MagDot: Drift-free, Wearable Joint Angle Tracking at Low Cost
(To Appear) UbiComp 2024

Dongyao Chen, Qing Luo, Xiaomeng Chen, Xinbing Wang, Chenghu Zhou

Tracking the angular movement of body joints has been a critical enabler for various applications, such as virtual and augmented reality, sports monitoring, and medical rehabilitation. MagDot is the first wearable system that achieves drift-free joint tracking. Experiment results indicate MagDot can achieve tracking accuracy of 2.72◦, 4.14◦, and 4.61◦ for elbow, knee, and shoulder, respectively.

Paper | (Slides, Demo, and Code will be updated soon)

METRO: Magnetic Road Markings for All-weather, Smart Roads
SenSys 2023

Jike Wang, Shanmu Wang, Yasha Iravantchi, Mingke Wang, Alanson Sample, Kang G. Shin, Xinbing Wang, Chenghu Zhou, Dongyao Chen

Allowing cars to "see" road markings is crucial for traffic safety. However, road markings, e.g., lanes and pedestrian crossings, can be easily occluded by bad weather. METRO proposed a novel magnetic sensing approach to encode rich information with passive magnets. METRO is tested and verified on REAL-WORLD ROADS!

Paper | Code | Slides

Guess Which Car Type I Am Driving: Information Leak via Driving Apps
VehicleSec 2023 (Best Paper Award)

Dongyao Chen, Mert D. Pesé, and Kang G. Shin

We leveraged the widely available smartphone data to infer the vehicle type information.


Automatic Calibration of Magnetic Tracking
MobiCom 2022

Mingke Wang*, Qing Luo*, Yasha Iravantchi, Xiaomeng Chen, Alanson Sample, Kang G. Shin, Xiaohua Tian, Xinbing Wang, Dongyao Chen

We proposed MAGIC, a systematic framework to automatically calibrate both soft- and hard-iron disturbances for a MEMS magnetometer array.

Paper | Demo | Slides

Enabling Software-defined PHY for Backscatter Networks
MobiSys 2022

Fengyuan Zhu, Mingwei Ouyang, Luwei Feng, Yaoyu Liu, Xiaohua Tian, Meng Jin, Dongyao Chen, Xinbing Wang

In this work, we for the first time show how to enable softwaredefined PHY (SD-PHY) to achieve agile reprogrammability in wireless backscatter networks. This can facilitate innovations in this field by relieving researchers from unnecessary engineering work.


DETROIT: Data Collection, Translation and Sharing for Rapid Vehicular App Development
SECON 2022

Mert D. Pesé, Dongyao Chen, C. Andrés Campos, Alice Ying, Troy Stacer, Kang G. Shin

DETROIT is an open-source vehicle-agnostic end- to-end framework for vehicular data collection, translation and sharing that facilitates the rapid development of automotive apps.


MagX: Wearable, Untethered Hands Tracking with Passive Magnets
MobiCom 2021

Dongyao Chen, Mingke Wang, Chenxi He, Qing Luo, Yasha Iravantchi, Alanson Sample, Kang G. Shin, Xinbing Wang

We proposed MagX, the first untethered and mobile magnetic tracking platform for fine-grained hand tracking. Exemplary applications includes AR/VR interaction and face-touching detection.

Paper | Code | Slides | Website

Authenticating Drivers Using Automotive Batteries
UbiComp 2021

Liang He, Yuanchao Shu, Youngmoon Lee, Dongyao Chen, Kang G. Shin

This work presented B-Auth, a vehicle battery-based driver authentication platform. We discovered the connection between battery voltage with the driver's behavior, e.g., braking, acceleration, using wipers, etc.


LibreCAN: Automated CAN Message Translator
CCS 2019

Mert D. Pesé, Troy Stacer, C. Andrés Campos, Eric Newberry, Dongyao Chen, Kang G. Shin

LibreCAN can be used for automated translation of in-vehicle data, thus making the data flow in cars "transparent" to developers. In the future, we may be able to build apps on cars as easy as developing apps on smartphones!

Paper | Website

TurnsMap: Enhancing Traffic Safety with Crowdsensing and Deep Learning
UbiComp 2019

Dongyao Chen, Kang G. Shin

This work presents TurnsMap, an IoT + AI framework for automatically detecting if a left turn is safe, e.g., whether it has protection for left-turning cars. Democratizing this information can help assure traffic safety for various transportation applications, e.g., navigation and ride-sharing apps.

Paper | Website | Slides

Mobile IMUs Reveal Driver's Identity from Vehicle Turns
ArXiv Preprint, 2017

Dongyao Chen, Kyong-Tak Cho, Kang G. Shin

This work presents Dri-Fi, a solution that enables automotive apps to identify the person behind-the-wheel by only using mobile sensors. The capability of identifying driver is essential for personalized service/assistance for the driver and his/her designated parties, thus benefiting various automotive apps


Locating and Tracking BLE Beacons with Smartphones
CoNEXT, 2017

Dongyao Chen, Yurong Jiang, Kyu-Han Kim, Kang G. Shin

LocBLE is able to locate specific location of any surrounding Bluetooth low energy (BLE) beacons by justing using your smartphone. Comparing to existing coarse-grained BLE ranging applications, LocBLE is capable of enabling various use cases in Internet-of-Things. This is a collaborative work with Hewlett Packard Labs during my internship.

Paper | Demo | Slides

Invisible Sensing of Vehicle Steering with Smartphones
MobiSys, 2015

Dongyao Chen, Kyong-Tak Cho, Sihui Han, Zhizhuo Jin, Kang G. Shin

This work introduced a vehicle steering detection middleware called V-Sense which can run on commodity smartphones without additional sensors or infrastructure support.

Paper | Demo | Slides

Vulnerability and Protection of Channel State Information in Multiuser MIMO Networks
CCS, 2014

Yu-Chih Tung, Sihui Han, Dongyao Chen, Kang G. Shin

This work investigated vulnerability in MU-MIMO. Focusing on the plaintext feedback of estimated channel state information (CSI) from clients to the APs, we found that a malicious user could employ a sniff attack or a power attack by exploiting the vulnerability in the existing CSI feed scheme.


My Team

I am fortunate to work with these talented individuals at CyPhy Lab. Their motivation and curiosity in exploring the unknown are the eternal driving forces behind our team.

Ph.D. Student
M.S. Student
Ph.D. Student
Ph.D. Student
M.S. Student
M.S. Student
Undergraduate Student
Undergraduate Student
Undergraduate Student
Weikai Qin
Undergraduate Student


B.S. Thesis
M. S. Student at UCLA
B.S. Thesis
Ph.D. Student at UMich
Undergraduate research
M.S. at CMU
Tao Lu
Undergraduate research
M.S. student at Georgia Tech
Yuchao Ye
Undergraduate research
M.S. student at SJTU
Xueshen Liu
Undergraduate research
Ph.D. student at UMich
Tong Jin
Undergraduate research
M.S. student at CMU
Yifan Dong
Undergraduate research
M.S. student at UMich
Jingyan Wang
Undergraduate research
Hao Lin
Undergraduate research
Undergraduate research