Welcome

The DSAIG seminar series aim to bring together faculty members and students across different disciplines within the University to discuss research topics that are related to Data Science and its applications. It serves as a forum to foster interdisciplinary research and to uncover new possibilities for research collaboration in the Data Science field.

Monthly seminars will be organized with focuses on specific research topics related to Data Science and its applications, and given by renowned experts of the field with a broad range of academic backgrounds including Business, Engineering, Science, and Social Science.

For enquiries, please contact us at cb-dsaig@cityu.edu.hk.


Next Seminar

Prof. Frank CHEN
Dr. Eman LEUNG

A Data-driven Approach to the Integrated Elderly Care

By Prof. Frank CHEN & Dr. Eman LEUNG

Date
14 December 2017 (Thursday)
Time
12:30pm-2:00pm
Venue
Room 14-221, 14/F, Lau Ming Wai Academic Building (AC3), City University of Hong Kong
Language
English
Registration
Register Here

(A light sandwich lunch will be provided starting from 12:00noon. Please confirm your attendance.)

 

Abstract
The global trend today is to shift the care burden away from the acute care and long-term care, which are costly and afford a poor quality of life, to community care and primary care, which are more conducive to active aging, more cost-effective and afford a higher quality of life. Clinical studies and health economics research have repeatedly demonstrated that appropriate and coordinated care in the community can reduce both the rate of hospitalisation and the need for institutionalized long-term care.

However, the prevailing practice in HK is such that acute care and long-term care institutions receive most of the financial and human resources, even though it is well researched that investment in community-based care is more cost-effective for the active aging of the population. Healthcare in HK have been governed by two government departments through two systems, i.e., Social Welfare Department and Health and Food Bureau. As a result, elderly care systems in HK are fragmented and lacking effective coordination.

In this talk, we will present several projects towards developing a data-and-service analytics approach to integrated elderly care. Specifically, our studies are intended to address the following two thrust areas: First, prioritise elderly care delivery: use data science tools to develop an integrated registry of at-risk elderly in selected areas and their case history and care needs. Second, optimise resource allocation: use analytics such as simulation and optimisation tools to balance supply-demand dynamics and to ensure that resources are most effectively distributed and coordinated between inpatient and outbound (medical and social) services in the community.

Biography
Prof. Frank Chen is the Head and Chair Professor of Department of Management Sciences at CityU. His current research interests include healthcare management, supply-chain modeling, analysis of inventory systems, and sustainable supply chains. Prior to joining City University of Hong Kong in 2012, Prof. Chen was on the faculty of NUS Business School at National University of Singapore (1997-2001) and the Department of Systems Engineering and Engineering Management at the Chinese University of Hong Kong (2001-2012). He holds a bachelor degree in Engineering, master degree in Economics, and doctoral degree in Management from Tsinghua University (Beijing), the University of Waterloo, and the University of Toronto, respectively.

Dr. Eman Leung joined the Department of Management Sciences, College of Business, CityU in December 2014. He received his PhD and undergraduate degrees from the University of Toronto, Canada. His research interests include biostatistics, public health, healthcare management sciences and implementation sciences. His area of research bridges between public health research in clinical risk analytics and operations research on data-driven resource allocation. Before joining CityU, Dr. Leung was responsible for managing the quality and risk portfolio of a teaching hospital in Toronto. He has also served as a data scientist, first in the University of California San Francisco and then the University of Toronto.


Forthcoming

A Data-driven Approach to the Integrated Elderly Care
By Prof. Frank CHEN & Dr. Eman LEUNG
The global trend today is to shift the care burden away from the acute care and long-term care, which are costly and afford a poor quality of life, to community care and primary care, which are more conducive to active aging, more cost-effective and afford a higher quality of life... [ more ]
 
Neurodynamics-based Parallel Data Selection in the Era of Big Data
By Jun WANG
In the present information era, huge amount of data to be processed daily. In contrast of conventional sequential data processing techniques, parallel data processing approaches can expedite the processes and more efficiently deal with big data. In... [ more ]
 
A Lightening Introduction to Parallel Computing: Using Apache Spark as an Example
By Zhenzhen WANG
Traditionally, many problems are so large and/or complex that it is impossible to solve them on a single computer, especially given limited computer ... [ more ]
 
Development of two consumer satisfaction and confidence indexes
By Geoffrey TSO
We shall cover the development of two consumer indexes with local impacts in Hong Kong. The Hong Kong Consumer Satisfaction Index (HKCSI) is a leading performance indicator for HK businesses, measuring ... [ more ]
 
 

Previous

Status Leaders, Hubs and their Social Influence
By Huazhong ZHAO
The prevalence of internet technology and social media has provided marketers new opportunities to identify influencers and utilize their social influence to affect consumer decisions. We introduce status leaders ... [ more ]
 
Mining Triage Notes to Predict Emergency Department Admissions
By Dr. Kevin SUN
Emergency department (ED) overcrowding is a worldwide problem that undermines hospitals’ ability to provide timely care to patients who need it urgently. One of the ... [ more ]
 
Prediction of chronic disease occurrence using EHR data: A pilot study in Hong Kong
By Dr. Qingpeng ZHANG
Chronic diseases are major causes of morbidity and mortality worldwide. Many chronic diseases are preventable through effective disease management and prevention programs. In addition, some... [ more ]
 
Mining Time Information in Digital Data
By Prof. Jonathan ZHU
Time is the single common denominator across all types of digital data from the internet, mobile networks, and IoT (internet of things). However, the rich information embedded in timestamps of digital data has often been taken for granted. As such, this gold... [ more ]
 
Understanding Demand Uncertainty
By Prof. Jeff HONG
Poisson processes are often used to model arrival (demand) processes in many business and engineering fields. In this talk, I will show you the results from a sequence of studies that we have done trying to understand the uncertainty behaviors in demand processes. The examples include phone calls... [ more ]
 
Blockchain as Trust Platform for Cross-boundary Dataflow
By Prof. Leon ZHAO
In the era of big data, more and more companies have become digitized. Further, under globalization initiatives such as the One-Belt One Road effort, business processes are being automated nowadays cross companies, leading to cross-boundary data flow. However, conventional information... [ more ]
 
 

Privacy Policy · Copyright · Disclaimer · Accessibility · Contact Us
© 2017 City University of Hong Kong. All Rights Reserved.