Jiaxing SHEN

Jiaxing SHEN

Assistant Professor

I am an Assistant Professor with the Department of Computing and Decision Sciences at Lingnan University. Previously, I was with the Department of Computing at the Hong Kong Polytechnic University as a Research Assistant Professor from 2020 to 2022. I obtained the B.E. degree in Software Engineering from Jilin University in 2014, and the Ph.D. degree in Computing from the Hong Kong Polytechnic University in 2019. In 2017, I was a visiting scholar with the Media Lab at Massachusetts Institute of Technology.

The theme of my research is Human Dynamics which aims to understand human behavior and provide actionable insights via cross-disciplinary approaches. Under the theme, my research interests include Context Sensing, IoT Systems, Mobile Computing, and Data Mining. I have published over NA papers including top-tier journals and conferences such as IEEE TMC, IEEE TKDE, IEEE TPDS, ACM TOIS, ACM IMWUT, IEEE INFOCOM, and WWW (including NA CCF-A and NA CCF-B). I have also won two Best Paper awards including one from IEEE INFOCOM 2020.

News

  • đź“Ś Recruiting Postdoctoral Fellows in mobile computing or data mining.

  • đź“Ś Recruiting self-motivated research students who are interested in doing MPhil and Ph.D.

  • 2023.12: Our work entitled “Distributed Semi-Supervised Learning with Consensus Consistency on Edge Devices” has been accepted by IEEE Transactions on Parallel and Distributed Systems (TPDS).

  • 2023.12: Our work entitled “Effective Network-Wide Traffic Measurement: A Lightweight Distributed Sketch Deployment” has been accepted by IEEE Conference on Computer Communications (INFOCOM).

  • 2023.11: Our works entitled “NetCR: Knowledge Graph based Recommendation Framework for Manual Network Configuration” and “ConfigReco: Network Configuration Recommendation with Graph Neural Networks” have been accepted by IEEE Internet of Things Journal and IEEE Network Magazine, respectively.
  • 2023.10: Our work entitled “Resisting TUL Attack: Balancing Data Privacy and Utility on Trajectory via Collaborative Adversarial Learning” has been accepted by GeoInformatica.
  • 2023.09: Our work entitled “Human-Intent-Driven Cellular Configuration Generation Using Program Synthesis” has been accepted by IEEE Journal on Selected Areas in Communications (JSAC).
  • 2023.06: Our work entitled “RemoteGesture: Room-scale Acoustic Gesture Recognition for Multiple Users” has been accepted by IEEE International Conference on Sensing, Communication, and Networking (SECON).
  • 2023.05: Our work entitled “Density Estimation-based Method to Determine Sample Size for Random Sample Partition of Big Data” has been accepted by Frontiers of Computer Science.
  • 2023.04: Our work entitled “Effective Fault Scenario Identification for Communication Networks via Knowledge-Enhanced Graph Neural Networks” has been accepted by IEEE Transaction on Mobile Computing (TMC).

Data-Driven Analytics of Human Dynamics

Below shows a pyramid of Human Dynamics research. It covers both my previous research effort and future directions.

Economic Level Human Dynamics
Social Level Human Dynamics
Psychological Level Human Dynamics
Physical Level Human Dynamics

Unknown and dark levels to be explored and lighted by us...

Economic level studies high-level human behaviors (e.g., decision-making, human bias) and profound social issues in significant sections like health, education, safety.

Social level refers to interplay between individuals including social tie, social influence, and social recommendation. Although social level is also difficult to capture and quantify, it is still feasible by combining physical and psychological cues.

Psychological level refers to mental things like emotion, personality, and cognition. This level is usually hard to measure directly and thus rely on measurements from physical level.

Physical level refers to human dynamics that can be directly observed. This level largely cares about low-level physical status (e.g., individuals' locations), activities (e.g., shopping, eating, and gestures), properties (e.g., gender).

Publications

. , .
CCF-A CCF-B JCR-Q1 Best Paper


Refereed Journal

Conference Papers

Other Publications

*:corresponding author(s) or co-first authors

Projects

  • 2023.05 - 2025.04 Knowledge Graph-based Recommendation Framework for Manual Network Configuration, PI.
  • 2023.01 - 2024.12 Preserving Implicative Privacy via Context-Aware Generative Approaches in Mobile Crowdsensing, PI.
  • 2019.03 - 2022.09 Multi-Stage Learning: An Effective Learning Paradigm for Multistage Systems, PI.

Selected Honors and Awards

  • 2020, Best Paper Award of IEEE International Conference on Computer Communications (INFOCOM).
  • 2016, Best Paper Award of IEEE International Conferences on Ubiquitous Intelligence & Computing, Advanced and Trusted Computing, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People, and Smart World Congress.
  • 2013, National Scholarship of China

Education

  • 2017 - 2018, visiting Ph.D., Media Lab, Massachusetts Institute of Technology, US
  • 2014 - 2019, Ph.D., Computer Science, The Hong Kong Polytechnic University, Hong Kong
  • 2010 - 2014, B.E., Software Engineering, Jilin University, China

Talks

  • 2022.04: Technique sharing: Singular Value Decomposition (SVD) and Its Applications [Slides]
  • 2020.12: Data-Driven Analytics of Human Dynamics] [Slides]
  • 2018.12: ICDM: “GINA: Group Gender Identification Using Privacy-Sensitive Audio Data” [Slides]

Teaching

Service

Technical Program Committee

  • IEEE MASS 2022

Session Chair

  • IEEE ICDM 2023
  • IEEE MASS 2022

Journal Reviewer

  • IEEE Transactions on Mobile Computing
  • ACM Computing Surveys
  • INFORMS Journal on Computing
  • ACM Transactions on Intelligent Systems and Technology
  • ACM Transactions on Cyber-Physical Systems
  • IEEE Transactions on Big Data
  • IEEE Internet of Things Journal

Conference Reviewer

  • IJCAI
  • IEEE ICDCS
  • IEEE Percom
  • ACM MOBIQUITOUS