Sudha Ram

Sudha Ram is Anheuser-Busch Endowed Professor of MIS, Entrepreneurship & Innovation in the Eller College of Management at the University of Arizona.  She has joint faculty appointments as Professor of Computer Science, member of BIO5 Institute, Applied Math, and Institute for Environment.  She is the director of  the INSITE: Center for Business Intelligence and Analytics at the University of Arizona.  Dr. Ram received a Ph.D.  from the University of Illinois at Urbana-Champaign in 1985 and a PGDM from IIM Calcutta in 1981.  Her research is in the areas of  Big Data Analytics, Machine Learning, and Large Scale Network Science. Dr. Ram has published more than 250 research  articles in refereed journals, conferences and book chapters. She has received more than $70 million in research funding from both corporate sources and government agencies including organizations such as, IBM, SAP, Ford, Raytheon Missile Systems, US ARMY, NIST, National Science Foundation, NASA, and Office of Research and Development of the CIA. Dr. Ram served as the senior editor for Information Systems Research, Journal of AIS and on the editorial board for many leading Information Systems journals. She was a co-editor in chief for the Journal on Data Semantics and is currently a founding co-editor for Journal of Business Analytics. In 1991, she started the Workshop on Information Technology and Systems (WITS). Dr. Ram has published articles in many top journals, including Information Systems Research, Management Science, MIS Quarterly, JAIS, Journal of MIS, and IEEE Transactions on Knowledge and Data Engineering. She is an  INFORMS ISS Fellow and an AIS Fellow and received  the Women of Impact Award from the University of Arizona in 2023,  the LEO award for Lifetime achievement from AIS in 2024,  and Extraordinary Faculty Award from the University of Arizona Foundation in 2025.

Courses

• MIS 531 Enterprise Data Management
• MIS 587 Business Intelligence
• MIS 586 Big Data Analytics
• MIS 615 Network Science: Theory and Applications

Publications (partial listing)

• Lee, Kyuhan and Ram, S.. “Intent-Driven Machine Learning for Fake News Detection: A Referential Domain Adaptation Approach”, accepted for publication, Production and Operations Management, January 2026.
• Zhang, W, Geng, S., Xie, J., Liang G., Niu, B., and Ram, S. “Predicting Consultation Success in Online Health Platforms Using Dynamic Knowledge Networks and Multimodal Data Fusion” , accepted for publication, MIS Quarterly, 2025.
• Lee, K., and Ram, S., “Leveraging Large Language Models for Hate Speech Detection: Multi-Agent, Information-Theoretic Prompt Learning for Enhancing Contextual Understanding”, Forthcoming, Journal of MIS, 2025. 
• Li, Y.,, Ernst, K., Pogreba Brown, K., Austhof, E., Heslin, K., Shilen, A., and Ram, S., “An analytical evaluation of contact tracing systems using real-world individual-level data.Int. J. Medical Informatics 203: 106020 (2025).
• Lee, K. & Ram, S. “Explainable Deep Learning for False Information Identification:  An Argumentation Theory Approach”, Information Systems Research (ISR Best Paper Nominee),   Vol. 35, No. (2), June 2024, pp.  890-907.
• Srinivasan K., Currim F., Ram S. “A Reduced Modeling Approach for Making Predictions With Incomplete Data Having Blockwise Missing Patterns”,  Informs Journal on Data Science, Vol 4, No. 1, 2025, pp. 85-99.
• Lee, M., Kankanahalli, A., Aanestadt, M., Ram, S and Maruping, L., “Digital Technologies and Advancement of Social Justice: A Framework and Agenda”, (Editorial)  Special issue of  MISQ,  Volume 48, No. 4, December 2024, pp. 1591-1610.
• Kim, B., Srinivasan, K., Kong, S., Kim, J., Shin, C., and Ram, S., “ROLEX: A Novel Method for Interpretable Machine Learning using Robust Local Explanations”. MIS Quarterly, 47(3), September 2023, pp, 1303-1332.
• Sudha Ram and Paulo Goes, “Focusing on High Impact Programmatic Research in Information Systems, Not Theory,  to Address Grand Challenges”, MIS Quarterly, Vol 45, No. 1, March 2021, pp. 478-483.
• Zhang, Wenli, and Sudha Ram. “A Comprehensive Analysis of Risk Factors for Asthma: Based on Machine Learning and Large Heterogenous Data Sources”, MIS Quarterly,  Special Issue on the Role of Information Systems in Chronic Disease Prevention and Management,  Vol 44, No. 1, pp 305-349, 2020.
• Karthik Srininivasan, Faiz Currim and Sudha Ram, Predicting High Cost Patients at Point of Admission using Network Science,  IEEE Journal on Biomedical and Health Informatics, Vol. 22, No. 6,  November 2018, pp. 1970-1977.
• Kunpeng Zhang, Sudha Ram, and Sid Bhattacharya, “Large Scale Network Analysis for Online Social Brand Advertising”, MIS Quarterly, Special Issue on Transformational Issues in Big Data and Analytics for Networked Business,  December 2016.
• Sudha Ram, Wenli Zhang, Max Williams and Yolande Pengetenze, “Predicting Asthma Related Emergency Department Visits Using Big Data”, Featured Article,  IEEE Journal of Biomedical and Health Informatics”, Special issue on Big Data Analytics in Health Care, July 2015.
• Yun Wang, and Sudha Ram, “Prediction of Location Based Sequential Purchasing Events Using Spatial, Temporal and Social Patterns”, in IEEE Intelligent Systems, Special Issue on Big Data and Predictive Analytics,  May/June 2015 pp. 2-9.
• F. Currim and S. Ram, “Modeling Spatial and Temporal Set-Based Constraints During Conceptual Database Design”, Information Systems Research, March 2012, Vol 23, pp. 109-128.
• A. Hevner, S. March, J. Park. S. Ram "Design Science in Information Systems Research", MIS Quarterly, Volume 28, No. 1, March 2004, pp. 75-105.  This paper has been cited more than 12,000 times.

Research Grants

• “eNEPA-Harnessing the Power of Big Data to Catalyze Scholarly Inquiry, Increase Efficiency, and Transform Public Engagement with the National Environmental Policy Co- PI with Laura Lopez Hoffman, Marc Miller, and Stephen Bethard,  funded by National Science Foundation,  $1,500,000, September 2018-2021.
• “A Data Synthesis and Knowledge Discovery System for Long Term Interdisciplinary Research on Southwest Social Change”, Funded by National Science Foundation, $1,685,090, August 2018-2020, Co-PI with Barbara Mills.
• “Big Data Analytics to Spur Health Care Innovations”, Accelerate for Success grant funded by Office of Research and Development, University of Arizona (with 1:1 matching funds from Eller/MIS department), $150,000, 2016.
• “Development of Smart Cities using Big Data”,  funded by I3FOR Institute, $224,995, June 2015-2016 Co-PI with Paulo Goes.
• “Impact of Green Building Design on Human Health and Wellbeing”,  funded, Co-PI with Esther Sternberg, Bijan Najafi and Matthias Mehl,   funded by General Services Administration, January 2013, $3,385,482, September 2014-2017.
• “Social Media Based  Analytics for  Disease propagation and Risk Prediction using Big Data”, PI, $50,000, funded by Parkland Center for Clinical Innovations, September 2013.

Professional Associations

• ACM (Association for Computing Machinery)
• IEEE (Institute of Electrical and Electronics Engineers)
• INFORMS (The Institute for Operations Research and the Management Sciences)
• AIS (Association for Information Systems)

Awards and Honors

• AIS (Association for Information Systems) Fellow, 2018
• Best paper award from IEEE International Conference on Smart Cities, September 2016
• Best Paper Award, ACM Digital Health Conference, April 2016.
• IBM Faculty Award, September 2012.