World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
53
Citations
14452
World Ranking
4735
National Ranking
2203

Electronics and Electrical Engineering

D-Index
46
Citations
11829
World Ranking
3321
National Ranking
1232

Research.com Recognitions

  • 2014 - IEEE Fellow For contributions to modeling of wireless ad-hoc and sensor networks

Overview

Mingyan Liu is affiliated with the University of Michigan-Ann Arbor in the United States. Their research primarily lies within the field of Computer Science, with a strong focus on several subfields including Artificial Intelligence, Management Science and Operations Research, Sociology and Political Science, Information Systems, and Cognitive Neuroscience.

Their scholarly output spans a variety of topics, reflecting a multidisciplinary approach. Key topics of their work include:

  • Game Theory and Applications
  • Privacy-Preserving Technologies in Data
  • Privacy, Security, and Data Protection
  • Auction Theory and Applications
  • Information and Cyber Security
  • Adversarial Robustness in Machine Learning
  • Experimental Behavioral Economics Studies

Mingyan Liu has published extensively, with notable recent papers such as:

  • "Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations," 2020, arXiv (Cornell University)
  • "RAP1-RAC1 Signaling Has an Important Role in Adhesion and Migration in HNSCC," 2020, Journal of Dental Research
  • "Essential Technics of Cybersecurity for Intelligent Connected Vehicles: Comprehensive Review and Perspective," 2023, IEEE Internet of Things Journal
  • "A novel method of prediction for capacity and remaining useful life of lithium-ion battery based on multi-time scale Weibull accelerated failure time regression," 2023, Journal of Energy Storage

Their frequent co-authors include Kun Jin, Jon Crowcroft, Ranjan Pal, Swades De, and Yixuan Wang. These collaborations have resulted in multiple publications, contributing to diverse aspects of their research areas.

Mingyan Liu's work appears frequently in several publication venues, including:

  • arXiv (Cornell University)
  • IEEE Access
  • International Journal of Radiation Oncology*Biology*Physics
  • IEEE Internet of Things Journal
  • Alzheimer's & Dementia

Among the recognitions received, Mingyan Liu was named an IEEE Fellow in 2014 for contributions to modeling of wireless ad-hoc and sensor networks.

Best Publications

  • Random waypoint considered harmful

    J. Yoon;M. Liu;B. Noble

  • Generating Adversarial Examples with Adversarial Networks

    Chaowei Xiao;Bo Li;Jun-yan Zhu;Jun-yan Zhu;Warren He

  • AMRoute: ad hoc multicast routing protocol

    Jason Xie;Rajesh R. Talpade;Anthony Mcauley;Mingyan Liu

  • Analysis of energy consumption and lifetime of heterogeneous wireless sensor networks

    E.J. Duarte-Melo;Mingyan Liu

  • Mining Spectrum Usage Data: A Large-Scale Spectrum Measurement Study

    Sixing Yin;Dawei Chen;Qian Zhang;Mingyan Liu

  • Optimality of Myopic Sensing in Multichannel Opportunistic Access

    S. Ahmad;Mingyan Liu;T. Javidi;Qing Zhao

  • Network coverage using low duty-cycled sensors: random & coordinated sleep algorithms

    Chih-fan Hsin;Mingyan Liu

  • Revenue generation for truthful spectrum auction in dynamic spectrum access

    Juncheng Jia;Qian Zhang;Qin Zhang;Mingyan Liu

  • Optimal channel probing and transmission scheduling for opportunistic spectrum access

    Nicholas B. Chang;Mingyan Liu

  • Sound mobility models

    Jungkeun Yoon;Mingyan Liu;Brian Noble

  • Surface street traffic estimation

    Jungkeun Yoon;Brian Noble;Mingyan Liu

  • Spatially transformed adversarial examples

    Chaowei Xiao;Jun Yan Zhu;Bo Li;Warren He

  • On the many-to-one transport capacity of a dense wireless sensor network and the compressibility of its data

    Daniel Marco;Enrique J. Duarte-Melo;Mingyan Liu;David L. Neuhoff

  • Data-gathering wireless sensor networks: organization and capacity

    Enrique J. Duarte-Melo;Mingyan Liu

  • Mining spectrum usage data: a large-scale spectrum measurement study

    Dawei Chen;Sixing Yin;Qian Zhang;Mingyan Liu

  • AMRoute: Adhoc Multicast Routing Protocol

    Mingyan D. Liu;Rajesh R. Talpade;Anthony J. McAuley;Ethendranath Bommaiah

  • Building realistic mobility models from coarse-grained traces

    Jungkeun Yoon;Brian D. Noble;Mingyan Liu;Minkyong Kim

  • PhaseU: Real-time LOS identification with WiFi

    Chenshu Wu;Zheng Yang;Zimu Zhou;Kun Qian

  • Cloudy with a chance of breach: forecasting cyber security incidents

    Yang Liu;Armin Sarabi;Jing Zhang;Parinaz Naghizadeh

  • Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks

    Yulong Cao;Ningfei Wang;Chaowei Xiao;Dawei Yang

  • Optimality of Myopic Sensing in Multi-Channel Opportunistic Access

    T. Javidi;B. Krishnamachari;Qing Zhao;Mingyan Liu

Frequent Co-Authors

Mahta Moghaddam
Mahta Moghaddam University of Southern California
Jerome P. Lynch
Jerome P. Lynch University of Michigan–Ann Arbor
Demosthenis Teneketzis
Demosthenis Teneketzis University of Michigan–Ann Arbor
Dawn Song
Dawn Song University of California, Berkeley
John S. Baras
John S. Baras University of Maryland, College Park
Bhaskar Krishnamachari
Bhaskar Krishnamachari University of Southern California
Yunhao Liu
Yunhao Liu Tsinghua University
Brian D. Noble
Brian D. Noble University of Michigan–Ann Arbor
Jianwei Huang
Jianwei Huang Chinese University of Hong Kong, Shenzhen
Michael Bailey
Michael Bailey Georgia Institute of Technology

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