Time

10:00-11:00 AM, May. 17, 2022

Location

ZOOM online

Abstract
In this talk, I will discuss the recent results done by the HKU STAR Lab (Social Technology and Research Laboratory) established in 2021. The lab has been working on fundamental data science research, as well as novel  data-driven technologies for serving the society.  I will first describe how we tackle the challenge of the huge volume and complexity of graph data, based on developing novel graph algorithms (e.g., densest subgraph discovery and higher-order graph analysis). I will also discuss how heterogeneous information networks can be used to support the matching of elders’ needs and helpers’ expertise in HINCare – our multiple-NGO volunteering support platform.

     Lecturer
Prof. Reynold Cheng is a Professor of the Department of Computer Science in the University of Hong Kong (HKU). He is Associate Director of the HKU Musketeers Foundation Institute of Data Science, Director of HKU STAR Lab, Associate Dean of Engineering (Student Enrichment), and program director of data science and engineering program.  His research interests are in data science, big graph analytics and uncertain data management. He received his PhD degree from Department of Computer Science of Purdue University in 2005.

Prof. Cheng received the SIGMOD Research Highlights Reward 2020, HKICT Awards 2021, and HKU Knowledge Exchange Award (Engineering) 2021. He was granted an Outstanding Young Researcher Award 2011-12 by HKU. He received the Universitas 21 Fellowship in 2011, and two Performance Awards from HKPU Computing in 2006 and 2007.  He is an academic advisor to the College of Professional and Continuing Education of HKPU. He is a member of IEEE, ACM, ACM SIGMOD, and UPE. He was a PC co-chair of IEEE ICDE 2021, and has been serving on the program committees and review panels for leading database conferences and journals like SIGMOD, VLDB, ICDE, KDD, IJCAI, AAAI, and TODS. He is on the editorial board of IS and DAPD, and was a former editorial board member of TKDE.