Hsinchun Chen

UA Regents' Professor of MIS
Thomas R. Brown Chair in Management and Technology
Director, Artificial Intelligence Laboratory
Director, AZSecure Cybersecurity Program
Hsinchun Chen

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

Documents

Areas of Expertise

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

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, AAAS, and AIS. He received the NCTU Distinguished Alumnus Award in 2005, the IEEE Computer Society Technical Achievement Award in 2006, the INFORMS Design Science Award in 2008 and 2023, the AIS Impact Award in 2020, and the IEEE Big Data Security Pioneer Award, the UA Extraordinary Faculty Award in 2022, and the INFORMS ISS Practical Impacts Award in 2023. He was also recognized in the INFORMS ISS Nunamaker-Chen Dissertation Award. Dr. Chen had graduated 36 Ph.D. students over the past 34+ years, most of them placed at peer Research I institutions. Three of his Ph.D. students won the prestigious ICIS ACM SIGMIS Doctoral Dissertation Award (Z. Huang 2005, S. Samtani 2019, R. Ebrahimi 2021). 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, 320+ SCI journal articles, and 220+ refereed conference articles covering artificial intelligence, digital library, data/text/web mining, business intelligence, technology mapping, security informatics, and health informatics. His overall h-index is 112 (58,000+ citations for 600+ papers according to Google Scholar), among the highest in MIS and top 50 in computer science. Dr. Chen is Director of the Artificial Intelligence Lab at The University of Arizona since 1989, which has received $60M+ 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 was the founding chair of ICADL (25+ years) and IEEE ISI (20+ years). He served on the INFORMS Publications Committee and ISR EIC Search Committee in 2021-2022. He is also a successful IT entrepreneur. His COPLINK/i2 system (with NSF and VC funding) for security analytics was commercialized in 2000 and acquired by IBM (for $500M) as its leading government analytics product in 2011. The COPLINK/i2 system is in use in 5,000+ law enforcement jurisdictions and intelligence agencies (100K+ users) 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 has been a visiting distinguished chair professor at several major universities in China (Tsinghua University, 2013-2016) and Taiwan (National Taiwan University, 2010-present). 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 since 2012 from NSF SFS, SaTC, and CICI programs and CAE-CD/CAE-R cybersecurity designations from NSA/DHS. Led by SFS CyberCorps graduate students (G. Greer and R. Reyes), the Arizona Pen Testing teams placed #5 in 2020 and #4 in 2021 in the highly competitive National Cyber League (NCL) competition (10,000+ students from 500+ universities). In addition, SFS Ph.D. graduate Dr. S. Samtani (supervised by Dr. Chen) was elected in 2022 as a member of the prestigious SFS CyberCorps Hall of Fame (only 7 elected out of 5,000+ SFS graduates). The UA SFS program has placed 30+ graduates (100% placement rate) at federal agencies (NSA, FBI, DHS) and national labs (Sandia, PNNL) as cyber warriors since 2015, helping to secure cyberspace. Dr. Chen’s most recent AI4BI project involves advancing AI for BI (business intelligence) in the domain of CHIPS Act for semiconductors and high-performance computing (HPC). Dr. Chen currently serves as Head of AI4BI at TSMC (June 2024-). 

Research Lab/Program

Research Summary

Courses

Publications

  • 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 Engineering, Volume 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 Engineering, Volume 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 Informatics, Volume 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 Informatics, Volume 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 Quarterly, Volume 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 Research, Volume 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 Systems, Volume 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.
  •  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, Volume 37, Number 2, Pages 457-483, 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 Quarterly, Volume 44, Number 2, Pages 933-955, 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 Frontiers, Volume 22, Number 3, Pages 697-718, 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 Frontiers, Volume 24, Number 4, Pages 911-925, 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, Volume 37, Number 3, Pages 694-722, 2020.
  • S. Samtani, H. Zhu, and H. Chen, “Proactively Identifying Emerging Threats from the Dark Web: A Diachronic Graph Embedding Framework (D-GEF),” ACM Transactions on Privacy and Security, Volume 23, Number 4, Pages 1-33, 2020.
  • S. Samtani, M. Kantarcioglu, and H. Chen. “Trailblazing the Artificial Intelligence for Cybersecurity Discipline: A Multi-Disciplinary Research Roadmap,” ACM Transactions on Management Information Systems, Volume 11, Number 4, Pages 1-19, 2020.
  • S. Samtani, M. Kantarcioglu, and H. Chen, “A Multi-Disciplinary Perspective for Conducting Artificial Intelligence-enabled Privacy Analytics: Connecting Data, Algorithms, and Systems,” ACM Transactions on Management Information Systems, Volume 12, Number 1, Pages 1-18, 2021. 
  • 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 Quarterly, Volume 46, Number 2, June 2021.
  • 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 Engineering, Volume 33, Number 10, Pages 3323-3337, 2021.
  • S. Yu, Y. Chai, H. Chen, R. A. Brown, S. J. Sherman, and J. F. Nunamker, “Fall Detection with Wearable Sensors: A Hierarchical Attention-based Convolutional Neural Network Approach,” Journal of Management Information Systems, Volume 38, Number 4, Pages 1095-1121, 2021.
  • B. Wen, P. Hu, M. Ebrahimi, and H. Chen, “Key Factors Affecting User Adoption of Open-Access Data Repositories in Intelligence and Security Informatics,” ACM Transactions on Management Information Systems (TMIS), Volume 13, Number 1, Pages 10:1-10:24, 2022.
  • N. Zhang, M. Ebrahimi, W. Li, H. Chen, "Counteracting Dark Web Text-Based CAPTCHA with Generative Adversarial Learning for Proactive Cyber Threat Intelligence," ACM Transactions on Management Information Systems (TMIS), Volume 13, Number 2, Pages 21:1-21:21, 2022.
  • S. Samtani, Y. Chai, and H. Chen, "Linking Exploits from the Dark Web to Known Vulnerabilities for Proactive Cyber Threat Intelligence: An Attention-based Deep Structured Semantic Model," MIS Quarterly, Volume 46, Number 2, Pages 909-944, June 2022.
  • M. Ebrahimi, Y. Chai, S. Samtani, and H. Chen, “Cross-Lingual Cybersecurity Analytics in the International Dark Web with Adversarial Deep Representation Learning,” MIS Quarterly, Volume 46, Number 2, Number 1209-1226, June 2022.
  • S. Yu, Y. Chai, H. Chen, S. J. Sherman, and R. A. Brown, "Wearable Sensor-based Chronic Condition Severity Assessment: An Adversarial Attention-based Deep Multisource Multitask Learning Approach,” MIS Quarterly, Volume 46, Number 3, Pages 1355-1394, September 2022.
  • Y. Dang, Y. Zhang, and H. Chen, “Leveraging the IS Success Model to Examine a Large-scale Social Media Search System,” Pacific Asia Journal of the Association for Information Systems, forthcoming, 2022.
  • S. Samtani, H. Zhu, B. Padmanabhan, Y. Chai, H. Chen, and J. F. Nunamaker, “Deep Learning for Information Systems Research,” Journal of Management Information Systems, forthcoming, 2022.
  • W. Li and H. Chen, “Discovering Emerging Threats in the Hacker Community: A Non-parametric Emerging Topic Detection Framework,” MIS Quarterly, forthcoming, 2022.
  • M. Ebrahimi, Y. Chai, H. Zhang, and H. Chen, "Heterogeneous Domain Adaptation with Adversarial Neural Representation Learning: Experiments on E-Commerce and Cybersecurity," IEEE Transactions on Pattern Recognition and Machine Intelligence (TPAMI), forthcoming, 2022.

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
  • IEEE Big Data Security Pioneer Award, 2022
  • AIS Impact Award, 2020
  • 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

Degree(s)

  • PhD, Information Systems, New York University, 1989