SCALE@NTU Invited Talk: HINCare: Intelligent volunteering and timebanking (Teams)

This research seminar is organized by Singtel-NTU Corporate Lab (SCALE@NTU). 

Invited Talk: HINCare: Intelligent volunteering and timebanking

Speaker:

Prof. Reynold C. K. Cheng
Associate Dean of Engineering (Student Enrichment), HKU
Associate Director, Musketeers Foundation Institute of Data Science, HKU
Programme Director, Data Science and Engineering, HKU
Department of Computer Science
The University of Hong Kong
 

Abstract: 

In Hong Kong, the number of elderly citizens is estimated to rise to one third of the population, or 2.37 million, in year 2037. As they age and become more frail, the demand for formal support services (e.g., providing domestic or escort services) will increase significantly in the coming years. However, there is a severe lack of manpower to meet these needs. Some elderly-care homes reported a 70% shortage of employees. There is thus a strong need of voluntary or part-time helpers for taking care of elders.
 
In this talk, I will introduce HINCare, a software platform that encourages mutual-help and volunteering culture in the community. HINCare uses the HIN (Heterogeneous Information Network) to recommend helpers to elders or other service recipients. The algorithms that use HINs and AI technologies for matching elders and helpers are based on our recent research results. This is the first time that HIN is used to support elderly care.
 
HINCare is now downloadable in Apple and Google Play Store, and has been serving more than a thousand of elders and helpers in NGOs (e.g., SKH and CSFC). The app is originally designed for elderly users, but has now expanded its services to support the Community Investment and Inclusion Fund (CIIF) and 10 NGOs engaged in teenage and family services. The system won the HKICT Award 2021, two Asia Smart App Awards (2021 and 2020), and the HKU Faculty Knowledge Exchange Awards 2021 HKU.

Biography:

Professor Reynold Cheng is a Professor of the Department of Computer Science in the University of Hong Kong (HKU). His research interests are in data science, big graph analytics and uncertain data management. He was the Assistant Professor in the Department of Computing of the Hong Kong Polytechnic University (HKPU) from 2005 to 2008. He received his BEng (Computer Engineering) in 1998, and MPhil (Computer Science and Information Systems) in 2000 from HKU. He then obtained his MSc and PhD degrees from Department of Computer Science of Purdue University in 2003 and 2005.
 
Professor Cheng is listed as the World’s Top 2% Scientists by Stanford University in 2022, and is named the 2023 AI 2000 Most Influential Scholar Honorable Mention in Database. He 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 KAIS, IS and DAPD, and was a former editorial board member of TKDE.