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Pittsburgh Building
- kuruzj@rpi.edu
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5182762332
- 0000-0003-4091-9380
About
Jason Kuruzovich is Professor of Business Analytics and Information Technology at the Lally School of Management at Rensselaer Polytechnic Institute, where he also serves as Area Head for Information Technology and Web Science. His research examines how artificial intelligence, digital platforms, and analytics shape organizations, markets, and entrepreneurial activity, with particular interests in algorithmic fairness, AI in hiring, and technology-enabled innovation.
His work has appeared in leading journals, including Management Science, MIS Quarterly, Information Systems Research, Journal of Marketing, and Journal of Applied Psychology. His collaborative research on machine learning in personnel selection received the 2025 Personnel Psychology Best Paper Award and the Society for Industrial and Organizational Psychology’s Jeanneret Award.
Kuruzovich serves as principal investigator for RPI’s National Science Foundation I-Corps program and previously directed the Severino Center for Technological Entrepreneurship. His teaching spans machine learning, business analytics, information systems, and entrepreneurship, connecting technical skills with practical business applications. He holds a Ph.D. in Information Systems from the University of Maryland and a B.S. in Chemical Engineering, cum laude, from Lafayette College.
Ph.D., Information Systems, Robert H. Smith School of Business, University of Maryland, 2006.
B.S., Chemical Engineering, cum laude, Lafayette College, 1996.
Research
Jason Kuruzovich studies how digital technologies and artificial intelligence reshape organizations, markets, and entrepreneurship. His research spans online platform business models, applied AI, and innovation ecosystems, combining perspectives from information systems, economics, organizational behavior, and data science.
His work examines how digital platforms influence search, purchasing, and competition; how AI can improve decision-making while reducing bias in hiring and assessment; and how entrepreneurs use digital tools to adapt business models and acquire resources. Additional projects explore healthcare analytics, AI in online gaming, and the effects of generative AI on work. Through interdisciplinary teams and industry partnerships, he combines machine learning, causal inference, and field experiments to address practical challenges and advance understanding of technology-driven change.
Information Systems, Electronic Commerce, Database Management, Management Information Systems, Organizational Research Methodologies
Teaching
Jason Kuruzovich’s teaching connects information systems, business analytics, and artificial intelligence with practical business challenges. He has taught undergraduate, master’s, doctoral, and executive students across subjects including applied machine learning, entrepreneurship, quantitative methods, and digital business.
His approach emphasizes hands-on learning, critical thinking, and clear communication. In capstone and management practicum courses, students collaborate with companies and startups to define problems, analyze data, and develop actionable recommendations. These projects help students build professional experience and demonstrate their contributions to client organizations.
He also developed an applied machine learning course that guides students from Python fundamentals through advanced applications using real datasets and interactive notebooks. Across his courses, Kuruzovich aims to build students’ technical confidence and ability to translate analysis into business value, preparing them to navigate and lead technological change.
Professor Kuruzovich currently teaches Web Systems Development (ITWS 2110/CSCI 2960) and Advanced Web Systems Development (ITWS 4500). Both courses emphasize hands-on learning through collaborative projects in which students design, build, test, and deploy complete web applications.
Web Systems Development introduces full-stack development, connecting user interfaces, backend services, databases, and APIs with foundational practices in security, testing, and cloud deployment.
Advanced Web Systems Development builds on these foundations through deeper study of application architecture, scalability, reliability, and system integration. Students explore AI-assisted development and agentic AI workflows while learning to evaluate technical trade-offs and communicate design decisions. Across both courses, the goal is to prepare students to develop secure, maintainable web systems and adapt to rapidly evolving technologies.
Recognition
Jason Kuruzovich has received recognition for research on digital markets and artificial intelligence, as well as contributions to teaching and entrepreneurship. His collaborative research on machine learning in personnel selection received the 2025 Personnel Psychology Best Paper Award and the 2025 SIOP Jeanneret Award for Excellence in the Study of Individual or Group Assessment. Additional honors include the Information Systems Research Best Published Paper Award, the CIST Best Paper Award, and RPI’s Dean’s “Complete Educator” Award.
2025 — Personnel Psychology Best Paper Award.
2025 — SIOP Jeanneret Award for Excellence in the Study of Individual or Group Assessment.
2025 — Recognition among the top 10 most-cited papers published in Personnel Psychology in 2023.
2023 — Best Paper Award, Conference on Information Systems and Technology (CIST).
2018 — School of Management Best Paper Award, Rensselaer Polytechnic Institute.
2016 — Campus Connector Award, Upstate Venture Connect.
2014 — Albany’s 40 Under 40.
2014 — Technology Innovation Award, Center for Economic Growth, for startup work.
2010 — Best Paper Award, Hawaii International Conference on System Sciences, for “Competing through Services: Service Migration of Information Technology Product Vendors.”
2009 — Best Published Paper Award, Information Systems Society and Information Systems Research, for “Marketspace or Marketplace? Online Information Search and Channel Outcomes in Auto Retailing.”
Publications
Arhin, K., Hickman, L., & Kuruzovich, J. (2026). A layered needs-affordances-features approach to advancing artificial intelligence fairness in hiring systems. Journal of the Association for Information Systems, 27(4), 846–876.
Hickman, L., Huynh, C., Gass, J., Booth, B., Kuruzovich, J., & Tay, L. (2024). Whither bias goes, I will go: An integrative, systematic review of algorithmic bias mitigation. Journal of Applied Psychology.
Zhang, N., Wang, M., Xu, H., Koenig, N., Hickman, L., Kuruzovich, J., et al. (2023). Reducing subgroup differences in personnel selection through the application of machine learning. Personnel Psychology.
Jiang, L., Ravichandran, T., & Kuruzovich, J. (2023). Review moderation transparency and user-generated content: Evidence from a natural experiment. MIS Quarterly.
Kuruzovich, J., Paczkowski, W. F., Golden, T., Goodarzi, S., & Venkatesh, V. (2021). Telecommuting and job performance: Role of technology and social exchange. Information & Management, 58(3), 103431.
Shou, X., Mavroudeas, G., Magdon-Ismail, M., Figueroa, J., Kuruzovich, J., & Bennett, K. (2020). Supervised mixture of experts models for population health. Methods, 179, 101–110.
Kuruzovich, J., & Etzion, H. (2018). Online auctions and multichannel retailing. Management Science.
Han, S., Kuruzovich, J., & Ravichandran, T. (2013). Service expansion of product firms in the information technology industry: An empirical study. Journal of Management Information Systems, 29(4), 127–158.
Kuruzovich, J., Viswanathan, S., & Agarwal, R. (2010). Seller search and market outcomes in online auctions. Management Science, 56(10), 1702–1717.
Kuruzovich, J., Viswanathan, S., Agarwal, R., & Gosain, S. (2008). Marketspace or marketplace? Online information search and channel outcomes in auto retailing. Information Systems Research, 19(2), 182–201.
Brown, S., Venkatesh, V., Kuruzovich, J., & Massey, A. P. (2008). Expectation confirmation: An examination of three competing models. Organizational Behavior and Human Decision Processes, 105(1), 52–66.
Viswanathan, S., Kuruzovich, J., Gosain, S., & Agarwal, R. (2007). Online infomediaries and price discrimination: Evidence from the automotive retailing sector. Journal of Marketing, 71(3), 89–107.
The following is a selection of recent publications in Scopus. Jason Kuruzovich has 30 indexed publications in the subjects of Computer Science, Computer Science, Decision Sciences.