Keynote Speakers

Douglas R. Vogel


Douglas R. Vogel is Professor of Information Systems (IS) and Association for Information Systems (AIS) Fellow as well as AIS Past President and, currently, Director of the eHealth Research Institute as a State Specially Recruited Expert in the School of Management at the Harbin Institute of Technology in China. He was Professor (Chair) of Information Systems at City University of Hong Kong. He has been involved with computers and computer systems in various capacities for over 35 years. He received his M.S. in Computer Science from U.C.L.A. in 1972 and his Ph.D in Business from University of Minnesota in 1986. Professor Vogel’s research interests bridge the business and academic communities in addressing questions of the impact of management information systems on aspects of interpersonal communication, group problem solving, cooperative learning and multi-cultural team productivity. He has published widely and directed extensive research on group support systems and technology support for education. He has been ranked 3rd in a journal report of top researchers in Group Support Systems and ranked 10th in a worldwide list of top researchers in MIS as well as 4th in the list of most collaborative information systems researchers. His research interests reflect a concern for encouraging efficient and effective utilization of computer systems in an atmosphere conducive to enhancing the quality of life with particular attention to healthcare and wellness.

Ahmed Abbasi


Ahmed Abbasi is Associate Dean and Murray Research Chaired Professor of Information Technology in the McIntire School of Commerce at the University of Virginia. He is Director of the Center for Business Analytics, co-director for the MS in Business Analytics, and coordinator for McIntire’s executives-on-grounds program. Ahmed is also a member of the Predictive Analytics Lab. Ahmed received his Ph.D. in Information Systems from the University of Arizona, where he worked as a project-lead on multi-million dollar “big data” initiatives in the Artificial Intelligence (AI) Lab. He attained an M.B.A. and B.S. in Information Technology from Virginia Tech.

Ahmed has over fifteen years of experience pertaining to AI and predictive analytics, with applications in health analytics, online fraud and security, text mining, and social media. Ahmed’s research has been funded through nearly a dozen grants from funding agencies such as the National Science Foundation. He has also received the IBM Faculty Award, AWS Research Grant, and Microsoft Research Azure Award for his work at the intersection of health and Big Data. Moreover, his center has received over 20 grants from industry.

Ahmed’s health research spans many topics, including detection of adverse drug events through user-generated content, development of machine learning methods to overcome health disparities, deep learning approaches for health psychometric analysis, and design and development of novel patient-centric health platforms that leverage mobile and IoT devices coupled with advanced AI methods.

Ahmed has published over 70 peer-reviewed articles in journals and conferences, including top-tier outlets such as MISQ, JMIS, ACM TOIS, IEEE TKDE, IEEE Intelligent Systems, and ICDM. One of his articles was considered a top publication by the Association for Information Systems. He also won best paper awards at MISQ and WITS. Ahmed’s work has been featured in various media outlets, including the Wall Street Journal, the Associated Press, WIRED, CBS, and Fox News.

Ahmed serves as Senior Editor for Information Systems Research (ISR) and Associate Editor (AE) for ACM TMIS and IEEE Intelligent Systems. He also previously served as AE at ISR and Decision Sciences Journal, and as special AE at MISQ. Ahmed is a senior member of the IEEE, a member of the American Heart Association, and has been on program committees for various conferences related to computational linguistics, text analytics, and data mining. He is also served as co-founder or advisory board member for multiple predictive analytics-related companies.

Long Lu


Long Lu is Professor at the School of Information Management in Wuhan University. Professor Lu’s research areas are biomedical informatics and big-data analysis and application. His laboratory focuses on bringing quantitative approaches from disciplines such as computer science and applied mathematics to study human and crop diseases, analysis on biological & medical big data, and making forecast & prediction with machine learning algorithms.

In 2003, Professor Lu designed a multimeric threading algorithm which successfully predicts the interaction between proteins. The application of the algorithm in yeast constructed the first protein structure based interaction map on the genomic scale. In 2006, he elucidated the evolutionary mechanism of protein interaction networks by combining protein structure with interactome map. In 2011, he effectively predicted the network of rare diseases. More recently, his laboratory made significant progresses in the networks of high density lipoprotein (HDL), as well as in brain structural and functional networks. These technologies and algorithms have been successfully applied to human diseases including infectious diseases, cardiovascular diseases and childhood developmental disorders, becoming effective tools for auxiliary diagnosis and treatment. Professor Lu has led several multi-million-dollar research projects supported by U.S. National Institutes of Health (NIH), National Science Foundation (NSF), and Chinese Talent Programs. He owns several patents in the United States and China. He has published more than fifty high-quality scientific papers which have been cited more than 2,000 times in total.

Professor Lu serves as the grant panel reviewer of U.S. NIH, U.S. NSF, Natural Sciences and Engineering Research Council of Canada (NSERC), Poland National Science Centre (NCN), and French National Research Agency (ANR). Domestically, Professor Lu also served in the reviewer panel for Ministry of Science and Technology and State Science and Technology Awards. Professor Lu’s research has been reported by numerous scientific magazines, such as The Scientist, Genomics, Proteomics & Bioinformatics, and social media, such as National Public Radio News and Yahoo News.

The major research topics of Prof. Lu include: high throughput genomic sequences, proteome, metabolic group analysis, microbial essential genes, network of diseases diagnosis development, medical image data analysis, and data mining in healthcare.

Chunxiao Xing


Chunxiao Xing is Professor and Associate Dean of Research Institute of Information Technology (RIIT), Tsinghua University, and Director of Web and Software R&D Center.

His research primarily focuses on the database and data warehouse, data and knowledge engineering, large-scale digital media management, software engineering, digital library technology, and key technologies for e-government.

He is the Director of Big Data Research Center for Smart Cities, Tsinghua University. He is also the Deputy Director of the Office Automation Technical Committee of China Computer Federation, a member of China Computer Federation Technical Committee on databases, big data and software engineering. He is also the member of IEEE and ACM.

He published more than 180 papers, including 40 SCI and 80 EI journal and conference articles. He has received 23 software copyrights, 40 patents of invention, and a technological achievement of Ministry of Education of China. His research has been supported by a number of national programs of China, such as National Basic Research Program (973), Natural Science Foundation of China, National High-Tech R&D Program (863), national high-tech industrialization project of CNGI, National Science and Technology Support Program.