Education

Mines Logo
Colorado School of Mines
Ph.D. in Computer Science
Golden, USA
Aug. 2015 - Aug. 2020

Mines Logo
Colorado School of Mines
M.S. in Computer Science
Golden, USA
Jan. 2014 - May. 2015

PKU Logo
Peking University
B.S. in Geochemistry
Beijing, China
Sep. 2009 - Jul. 2013

Skills

Java, Python, C++, Bash, Matlab, C, R.

Digital Signal Processing, Android Programming, Machine Learning, Algorithm Design, Speech Recognition, Computer Vision, Object-Oriented Programming, ROS Robot Programming, Arduino Programming, Game Theory, Git Version Control, LaTeX Writing.

Interests

Security and Privacy in Mobile IoT Sensing, Digital Signal Processing, Machine Learning, Algorithmic Game Theory, Incentive Mechanism Design, Networks, Crowdsourcing.

Projects

TurtleBot
Using RTAB-Map and a TurtleBot to Create a Floor Map
UltraUnlock
Smartphone Authentication Using Gestures in the Air
MoVo
A Spoof-proof Voice Authentication System for Smartphones
PlaceRecognition
An Video-Based Place Recognition Android App
MaskCall
A Privacy-Preserving Calling App

Experience

Course Instructor
CSCI 358: Discrete Math(Undergraduate-Level Course)
Colorado School of Mines
Fall 2019
Attendee
Project Catalyst: How to Engineer Engineering Education
Bucknell University
July 2017
Course Instructor
CSCI 561: Theory of Computation(Graduate-Level Course)
Colorado School of Mines
Fall 2019

Publications

Trade-off Between Location Quality and Privacy in Crowdsensing: An Optimization Perspective
Yuhui Zhang, Ming Li, Dejun Yang, Jian Tang, Guoliang Xue, and Jia Xu.
IEEE Internet of Things Journal, 7(4):3535-3544, 2020.
A Budget Feasible Mechanism for k-Topic Influence Maximization in Social Networks.
Yuhui Zhang, Ming Li, Dejun Yang, and Guoliang Xue.
IEEE Global Communications Conference (GLOBECOM), 2019.
Optimizing Location Quality in Privacy Preserving Crowdsensing.
Yuhui Zhang, Ming Li, Dejun Yang, Jian Tang,and Guoliang Xue.
IEEE Global Communications Conference (GLOBECOM), 2019.
Frameworks for Privacy-Preserving Mobile Crowdsensing Incentive Mechanisms.
Jian Lin, Dejun Yang, Ming Li, Jia Xu, and Guoliang Xue.
IEEE Transactions on Mobile Computing (TMC), 17(8): 1851-1864, 2018.
With the rapid growth of smartphones, mobile crowdsensing emerges as a new paradigm which takes advantage of the pervasive sensor-embedded smartphones to collect data efficiently. Many auction-based incentive mechanisms have been proposed to stimulate smartphone users to participate in the mobile crowdsensing applications and systems. However, none of them has taken into consideration both the bid privacy of smartphone users and the social cost. In this paper, we design two frameworks for privacypreserving auction-based incentive mechanisms that also achieve approximate social cost minimization. In the former, each user submits a bid for a set of tasks it is willing to perform; in the latter, each user submits a bid for each task in its task set. Both frameworks select users based on platform-defined score functions. As examples, we propose two score functions, linear and log functions, to realize the two frameworks. We rigorously prove that both proposed frameworks achieve computational efficiency, individual rationality, truthfulness, differential privacy, and approximate social cost minimization. In addition, with log score function, the two frameworks are asymptotically optimal in terms of the social cost. Extensive simulations evaluate the performance of the two frameworks and demonstrate that our frameworks achieve bid-privacy preservation although sacrificing social cost.
SpecWatch: A Framework For Adversarial Spectrum Monitoring With Un- known Statistics.
Ming Li, Dejun Yang, Jian Lin, Ming Li, and Jian Tang.
Computer Networks (COMNET), 143: 176-190, 2018.
Sybil-Proof Online Incentive Mechanisms for Crowdsensing.
Jian Lin, Ming Li, Dejun Yang, and Guoliang Xue.
International Conference on Computer Communications (INFOCOM), 2438-2446, 2018.
QUAC: Quality-Aware Contract-Based Incentive Mechanisms for Crowdsensing.
Ming Li, Jian Lin, Dejun Yang, Guoliang Xue, and Jian Tang.
IEEE International Conference on Mobile Ad Hoc and Sensor System (MASS), 72-80, 2017.
Sybil-Proof Incentive Mechanisms for Crowdsensing.
Jian Lin, Ming Li, Dejun Yang, Guoliang Xue, and Jian Tang.
IEEE International Conference on Computer Communications (INFOCOM), 2017.
Maximizing Capacity in Cognitive Radio Networks Under Physical Interference Model.
Michael Brown, Colin Marshall, Dejun Yang, Ming Li, Jian Lin, Guoliang Xue.
IEEE/ACM Transactions on Networking (TON), 25(5): 3003-3015, 2017.
Spectrum Auctions Under Physical Interference Model.
Yuhui Zhang, Dejun Yang, Jian Lin, Ming Li, Guoliang Xue, Jian Tang, and Lei Xie.
IEEE Transactions on Cognitive Communications and Networking (TCCN), 3(4): 719-728, 2017.
SpecWatch: Adversarial Spectrum Usage Monitoring in CRNs with Unknown Statistics.
Ming Li, Dejun Yang, Jian Lin, Ming Li, and Jian Tang.
IEEE International Conference on Computer Communications (INFOCOM), 2016.
BidGuard: A Framework for Privacy-Preserving Crowdsensing Incentive Mechanisms.
Jian Lin, Dejun Yang, Ming Li, Jia Xu, and Guoliang Xue.
IEEE Conference on Communications and Network Security (CNS), 145-153, 2016.