Scholar
Xiaohui Liang
Google Scholar ID: fzX2e3sAAAAJ
University of Massachusetts Boston
Citations & Impact
Citations
5,624
H-index
36
i10-index
74
Publications
20
Co-authors
18
list available
Publications
Resume (English only)
Academic Achievements
- Published over 100 refereed journal and conference papers. Awards include: Early Career Research Excellence Award from UMass Boston College of Science and Mathematics (2020), Early Career Award for Excellence in Scalable Computing from IEEE Technical Committee on Scalable Computing (2017), Best Land Transportation Paper Award from IEEE Vehicular Technology Society (2017), Internet of Things Technology Research Award from Google (2016), Best Paper Award in BodyNets 2010. Google Scholar H-Index is 55 and total citation is 13,684 as of Oct. 2025. Single PI of an NIH R01 Project (2019-2023) and Lead PI of an NSF Project (2016-2020).
Research Experience
- Currently, an Associate Professor and Associate Chair with the Department of Computer Science at UMass Boston, leading the Mobile Computing and Privacy (MobCP) Lab. Previously, a Postdoctoral Researcher at Dartmouth College (2014-2015), working on the NSF frontier project THaW.
Education
- PhD in Electrical and Computer Engineering from the University of Waterloo, Canada (2013), supervised by Prof. Sherman Shen (FIEEE) and Prof. Xiaodong Lin (FIEEE). MSc in Computer Science from Shanghai Jiao Tong University, China (2009). BSc in Computer Science from Shanghai Jiao Tong University, China (2006). Postdoctoral Researcher at Dartmouth College (2014-2015), supervised by Prof. David Kotz (FIEEE).
Background
- Research Interests: Mobile Healthcare, Internet of Things, Wearable Computing, Security and Privacy for Communication and Networking Systems. Professional Field: Computer Science. Brief Introduction: Xiaohui Liang is an Associate Professor and Associate Chair with the Department of Computer Science at University of Massachusetts, Boston (UMB), where he leads the Mobile Computing and Privacy (MobCP) Lab.
Miscellany
- Personal Interests: Looking for self-motivated PhD students interested in or with previous research experiences in voice analysis, data mining, deep learning, and mobile computing.
