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, and Institute for Environment. She is the director of the INSITE: Center for Business Intelligence and Analytics at the University of Arizona. Her research is in the areas of Big Data Analytics, Business Intelligence, and Large Scale Network Science. She is internationally acclaimed for her research that develops and uses different methods such as machine learning, statistical approaches, ontologies and conceptual modeling. 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, Intel Corporation, 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 AIS Fellow as well as an INFORMS ISS Distinguished Fellow and recipient of several IBM Faculty Development Awards and the Peter Chen Award. Her research has been highlighted in several media outlets including NPR news, and New York Times. She was a speaker for a TEDx talk on “Creating a Smarter World with Big Data”. She received a Woman of Impact of Award from the University of Arizona in October 2023.

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)

• Zhang, Wenli, and Sudha Ram. “A Comprehensive Analysis of Risk Factors for Asthma: Based on Machine Learning and Large Heterogenous Data Sources”, forthcoming,   MIS Quarterly,  Special Issue on Health Care Analytics, 2019.
• Devi Bhattacharya, Faiz Currim and Sudha Ram, “Evaluating Distributed Digital Infrastructures: An Empirical Study Comparing On-Demand Cloud with Local Systems”, forthcoming,  IEEE Transactions on Cloud Computing, 2019.
• Srikar Velichety, Sudha Ram and Jesse Bockstedt, “Quality Assessment of Peer-Produced Content in Knowledge Repositories using Development and Coordination Activities”, forthcoming, Journal of MIS, June 2019, pp. 478-512.
• Dursun Delen and Sudha Ram, “Research Challenges and Opportunities in Business Analytics”, Journal of Business Analytics, Vol. 1, No. 1, August 2018, pp. 2-12.
• 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.
• 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.
• 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.
• 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.