Hsinchun Chen

UA Regents' Professor of MIS

Thomas R. Brown Chair in Management and Technology

Director, Artificial Intelligence Laboratory

Director, AZSecure Cybersecurity Fellowship Program

Hsinchun Chen

McClelland Hall 430X
1130 E. Helen St. 
P.O. Box 210108 
Tucson, Arizona 85721-0108

Areas of Expertise

  • Cybersecurity and cyber threat intelligence
  • Health analytics and mobile health
  • Knowledge management and business intelligence
  • Data mining, text mining and web mining
  • Health informatics and security informatics
  • Digital library and search engines


PhD, Information Systems, New York University, 1989

Dr. Hsinchun Chen graduated with a BS degree from the National Chiao-Tong University (Taiwan), MBA from SUNY Buffalo, and an MS and Ph.D. from New York University. He is a University of Arizona Regents' Professor and the Thomas R. Brown Chair Professor in Management and Technology. He is also a Fellow of ACM, IEEE and AAAS. He received the IEEE Computer Society Technical Achievement Award in 2006, the INFORMS Design Science Award in 2008, the AIS Impact Award in 2020, and the IEEE Big Data Security Pioneer Award in 2022. He was also recognized in the INFORMS Information Systems Society (ISS) Nunamaker-Chen Dissertation Award (NCDA). The NCDA is named in honor of two University of Arizona professorsJay Nunamaker and Hsinchun Chen, who have made significant contributions to the field of Information Systems over the past several decades. Dr. Chen served as the lead Program Director of the Smart and Connected Health (SCH) Program at the NSF for 2014-2015, a multi-year multi-agency health IT research program of in the U.S. He is author/editor of 20+ books, 300+ SCI journal articles, and 200+ refereed conference articles covering artificial intelligence, digital library, data/text/web mining, business analytics, security informatics, and health informatics. His overall h-index is 104 (40,000+ citations for 900+ papers according to Google Scholar), among the highest in MIS and top 50 in computer science. Dr. Chen founded the Artificial Intelligence Lab at The University of Arizona in 1989, which has received $50M+ research funding from NSF, NIH, NLM, DOD, DOJ, CIA, DHS, and other agencies (100+ grants, 50+ from NSF, as PI). He has served as Editor-in-Chief, Senior Editor or AE of major ACM/IEEE (ACM TMIS, ACM TOIS, IEEE IS, IEEE SMC), MIS (MISQ, DSS) and Springer (JASIST) journals and conference/program chair of major ACM/IEEE/MIS conferences in digital library (ACM/IEEE JCDL, ICADL), information systems (ICIS), security informatics (IEEE ISI), and health informatics (ICSH). He is also a successful IT entrepreneur. His COPLINK/i2 system for security analytics was commercialized in 2000 and acquired by IBM as its leading government analytics product in 2011. The COPLINK/i2 system is in use in 5,000+ law enforcement jurisdictions and intelligence agencies in the U.S. and Europe, making significant contribution to public safety worldwide. Dr. Chen has served as an advisor to major federal research programs and was a Scientific Counselor of the National Library of Medicine (USA), National Library of China, and Academia Sinica (Taiwan). He is a visiting chair professor at several major universities in China (Tsinghua University) and Taiwan (National Taiwan University). He is internationally renowned for leading research and development in the health analytics (data and text mining; health big data; DiabeticLink and SilverLink) and security informatics (counter terrorism and cyber security analytics; security big data; COPLINK, Dark Web, Hacker Web, and AZSecure) communities. His recent research includes SilverLink for mobile health and AZSecure for advanced cyber threat intelligence. Dr. Chen is director of the UA AZSecure Cybersecurity Program, with $15M+ funding from NSF SFS, SaTC, and CICI programs and CAE-CD/CAE-R cybersecurity designations from NSA/DHS.

Research Lab/Program

Research Summary



  • Y. Lin, H. Chen, R. Brown, and S. Li, “Healthcare Predictive Analytics for Risk Profiling in Chronic Care: A Bayesian Multi-Task Learning Approach,” MIS Quarterly, Volume 41, Number 2, Pages 473-495, June 2017.
  • S. Samtani, R. Chinn, H. Chen, and, J. F. Nunamaker, “Exploring Emerging Hacker Assets and Key Hackers for Proactive Threat Intelligence,” Journal of Management Information Systems, Volume 34, Number 4, Pages 1-31, 2017.
  • Q. Li, Y. Chen, J. Wang, Y. Chan, and H. Chen, “Web Media and Stock Markets: A Survey and Future Directions from a Big Data Perspective,” IEEE Transactions on Knowledge and Data EngineeringVolume 30, Number 2, Pages 381-399, 2018.
  • W. Li, J. Yun, and H. Chen, “Supervised Topic Modeling using Hierarchical Dirichlet Process-based Inverse Regression: Experiments on E-Commerce Applications,” IEEE Transactions on Knowledge and Data EngineeringVolume 30, Number 6, Pages 1192-1205, 2018.
  • D. Zimbra, A. Abbasi, D. Zeng, and H. Chen, “The State-of-the-Art in Twitter Sentiment Analysis: A Review and Benchmark Evaluation,” ACM Transactions on Management Information Systems, Volume 9, Number 2, Pages 5:1-5:29, August 2018.
  •   H. Zhu, H. Chen, and R. A. Brown, “A Sequence-to-Sequence Model-Based Deep Learning Approach for Recognizing Activity of Daily Living for Senior Care,” Journal of Biomedical InformaticsVolume 84, Pages-148-158, 2018.
  • S. Yu, H. Chen, and R. A. Brown, “Hidden Markov Model Based Fall Detection with Motion Sensor Orientation Calibration: A Case for Real-Life Home Monitoring,” IEEE Journal of Biomedical and Health InformaticsVolume 22, Number 6, Pages 1847-1853, 2018.
  •  S. Samtani, S. Yu, H. Zhu, M. Patton, J. Matherly, and H. Chen, “Identifying SCADA Systems and Their Vulnerabilities on the Internet of Things (IoT):  A Text Mining Approach,” IEEE Intelligent Systems, Volume 33, Number 2, Pages 63-73, 2018.
  • V. Benjamin, J. Valacich, and H. Chen, “DICE-E: A Framework for Conducting Darknet Identification, Collection, Evaluation, with Ethics,” MIS QuarterlyVolume 43, Number 1, 2019.
  • S. Yu, H. Zhu, and H. Chen, “Emoticon Analysis for Chinese Social Media and E-Commerce: The AZEmo System,” ACM Transactions on Management Information Systems, Volume 9, Number 4, 16:1-16:22, 2019.
  • Y. Lin, M. Lin, and H. Chen, “Do Electronic Health Records Affect Quality of Care? Evidence from the HITECH Act,” Information Systems ResearchVolume 30, Number 1, Pages 306-318, 2019.
  • L. Wu, H. Zhu, H. Chen, and M. C. Roco, “Comparing Nanotechnology Landscapes in the US and China: A Patent Analysis Perspective,” Journal of Nanoparticle Research, Volume 21, August, 2019.
  • F. Ahmad, A. Abbasi, J. Li, D. G. Dobolyi, R. G. Netemeyer, G. D. Clifford, and H. Chen, “A  Deep Learning Architecture for Psychometric Natural Language Processing,” ACM Transactions on Information SystemsVolume 33, Number 1, Pages 6:1-6:29, 2020.
  • I. Bardhan, H. Chen, and E. Karahanna, “Connecting Systems, Data, and People: A Multidisciplinary Research Roadmap for Chronic Disease Management,” MIS Quarterly, Volume 44, Number 1, March 2020.
  • Y. Dang, Y. Zhang, Sue Brown, and H. Chen, “Examining the Impacts of Mental Workload and Task-Technology Fit on User Acceptance of the Social Media Search System,” Information Systems Frontiersforthcoming, 2020.
  • Y. Dang, Y. Zhang, and H. Chen, “An Exploratory Study on the Virtual World: Investigating the Avatar Gender and Avatar Age Differences in Their Social Interactions for Help-Seeking,” Information Systems Frontiersforthcoming, 2020.
  • M. Chau, T. Li, P. Wong, J. Xu, P. Yip, and H. Chen, “Finding People with Emotional Distress in Online Social Media: A Design Combining Machine Learning and Rule-based Classification,” MIS Quarterlyforthcoming, 2020.
  • Q. Li, J. Tan, J. Wang, and H. Chen, “A Multimodal Event-driven LSTM Model for Stock Prediction Using Online News,” IEEE Transactions on Knowledge and Data Engineeringforthcoming, 2020.
  •  H. Zhu, S. Samtani, H. Chen, and J. F. Nunamaker, “Human Identification for Activities of Daily Living: A Deep Transfer Approach,” Journal of Management Information Systems, forthcoming, 2020.
  • H. Zhu, S. Samtani, R. Brown, and H. Chen, “A Deep Learning Approach for Recognizing Activity of Daily Living (ADL) for Senior Care: Exploiting Interaction Dependency and Temporal Patterns,” MIS Quarterlyforthcoming, 2020.
  • M. Ebrahimi, J. F. Nunamaker, and H. Chen, “Semi-Supervised Cyber Threat identification in Dark Net Market: A Transductive and Deep Learning Approach,” Journal of Management Information Systems, forthcoming, 2020.

Research Funding

Dr. Hsinchun Chen has received over 40 million dollars in research funding from the National Science Foundation, National Library of Medicine, National Institutes of Health, Department of Justice, Department of Defense, Department of Homeland Security, SAP, New Mexico Tech and Library of Congress, among others.

Journal Associate Boards

Dr. Hsinchun Chen is founding Editor-in-Chief of ACM Transactions Management Information Systems, Editor-in-Chief of Springer Security Informatics journal, and Senior Editor of MIS Quarterly. He has served on the following editorial boards: ACM Transactions on Information Systems; IEEE Transactions on Systems, Man, and Cybernetics; Decision Support Systems; Journal of the American Society for Information Science and Technology; International Journal of Digital Libraries; International Journal of Electronic Business; Journal of Information Technology and Politics; Encyclopedia of Library and Information Sciences.

Professional Associations

  • Fellow, Association of Computing Machinery (ACM)
  • Fellow, Institute of Electrical and Electronic Engineers (IEEE)
  • Fellow, American Association for the Advancement of Sciences (AAAS)

Awards and Honors

  • Fellow: IEEE, AAAS, and ACM
  • Lead Program Director, NSF, Smart and Connected Health, 2014-2015
  • Thomas R. Brown Chair Professor of Technology and Management, University of Arizona, February 2013-present
  • University of Arizona Innovator of the Year, 2013
  • Arizona Centennial Top 100 Scientists, 2012
  • IEEE Research Achievement and Leadership Award in Intelligence and Security Informatics, 2011
  • Finalist, AZ Tech Council’s Governor’s Innovation of the Year Award, 2011
  • MIS Quarterly Best Paper, 2010