Rajendra Kulkarni is a researcher at School of Public Policy. His research interests span multiple disciplines including complexity science, discrete nonlinear dynamical systems, blockchain, spatio-temporal systems, and network science with the focus on developing analytical models for research in public policy, regional science, and economics. His interdisciplinary approach seeks to bridge the gap between computational science and how it may be applied to policy design, particularly in understanding how localized disruptions propagate through global networks. Through this approach; his research addresses critical contemporary challenges in supply chain resilience, spatial economics, and institutional governance.
Select Publications
Schintler, Laurie; Kulkarni, Rajendra; Beware of What Lies Beyond the Power Law: Predicting “Dragon King” Failures in Complex Spatial Economic Networks; Networks & Spatial Economics 2026 Springer Nature
Correa-Cabrera, Guadalupe; Kulkarni, Rajendra G; Baxter, Patrick R; Koizumi, Naoru; Messengers of a Drug War in the Cyberspace: The Case of Tamaulipas Third Generation Gangs and Transnational Cartels: A Small Wars Journal–El Centro Anthology 2025 Xlibris Corporation
Inoue, Megumi; Li, Meng-Hao; Hashemi, Mahdi; Yu, Yang; Jonnalagadda, Jahnavi; Kulkarni, Rajendra; Kestenbaum, Matthew; Mohess, Denise; Koizumi, Naoru; Opinion and sentiment analysis of palliative care in the era of COVID-19 Healthcare 11 116 855 2023 MDPI
Li, Meng-Hao; Kulkarni, Rajendra; Koizumi, Naoru; Andalibi, Ali; N3C Consortium; The association of the levels of high-density lipoprotein and apolipoprotein A1 with SARS-CoV-2 infection and COVID-19 severity: an analysis of the N3C database Biology 12 6 852 2023 MDPI
Kulkarni, Rajendra; Schintler, Laurie; Koizumi, Naoru; Olds, Jim; Stough, Roger R; Cryptocurrency, Stablecoins and Blockchain: Exploring digital money solutions for remittances and inclusive economies 66th Annual North American Meetings of the Regional Science Association International (13–16 Nov, 2019) in Pittsburgh, PA, USA 2019
Kulkarni R, Stough R. Identifying Sleeping Beauties in the Lore of Regional Science. In: Jackson R., Schaeffer P. (eds) Regional Research Frontiers – Vol. 1. Advances in Spatial Science (The Regional Science Series). 2017.
Schintler L, Kulkarni R. Big Data for Policy Analysis: The Good, The Bad, and The Ugly. Review of Policy Research. 2014 July; 31(34):343-348.
Kulkarni R, Haynes K, Stough R, Riggle J. Light based growth indicator (LBGI): exploratory analysis of developing a proxy for local economic growth based on night lights. Regional Science Policy and Practice. 2011 May 16; 1(3):101-113.
Haynes K, Kulkarni R. Modeling region based regimes for COVID‐19 mitigation: An inverse Gompertz approach to coronavirus infections in the USA, New York, and New Jersey. Regional Science Policy & Practice. 2021 April 29.
Kulkarni R, Stough R, Haynes K. Algorithmic Complexity and Spatial Simplicity. In: Reggiani A., Nijkamp P. (eds) Complexity and Spatial Networks. Advances in Spatial Science (The Regional Science Series). Springer, Berlin, Heidelberg. 2009.
P. Auerswald and R. G. Kulkarni (2008). Placing Innovation: An Approach to Identifying emergent technological activity. Economics of Innovation and New Technology, 17, 7, 733-750.
Gorman S, Kulkarni R. Spatial small worlds: new geographic patterns for an information economy. Environment and Planning B: Planning and Design. 2004 April 01; 31(2):273-296.
Kulkarni R, Schintler L, Stough R, Button K. A Kohonen Self-Organizing Map Approach to Modeling Growth Pole Dynamics. Networks and Spatial Economics. 2002; 2(2):175-189. Available from:
Paelinck J, Kulkarni R. Location-allocation aspects of Tinbergen-Bos systems. The Annals of Regional Science. 1999 December 01; 33(4):573-580.
Kulkarni R, Stough R, Haynes K. Spin glass and the interactions of congestion and emissions: an exploratory step. Transportation Research Part C: Emerging Technologies. 1996 December 01; 4(6):407-424.
Patent Award: Recipient of the United States Patent 7765319 for System and method for analyzing the structure of logical networks. (Sean Gorman, Rajendra Kulkarni, Laurie Schintler, Roger Stough) 2010