Anil Vullikanti

Anil Vullikanti is a Professor in the Department of Computer Science and a core faculty member of the Biocomplexity Institute at the University of Virginia. He holds affiliations within the School of Engineering and Applied Science. His research bridges theoretical computer science and applied domains like epidemiology, critical infrastructure, and public health. Previously, he held roles at Virginia Tech (2005–2018) and Los Alamos National Lab (2003–2005), and completed postdoctoral work at the Max Planck Institute for Computer Science.

Education: B. Tech from Indian Institute of Technology, Kanpur (1993); PhD from Indian Institute of Science, Bangalore (1999).

Research Interests: Randomized Algorithms, Combinatorial Optimization, Distributed Computing, Network Science, Machine Learning, and AI applied to epidemiological modeling, infrastructure protection, and healthcare systems. His work emphasizes scalable algorithms for real-world systems like pandemic forecasting, evacuation planning, and infection control.

Key Awards:

• College of Engineering Faculty Fellow Award (Virginia Tech, 2017)
• Excellence in Research Award (Biocomplexity Institute, 2017)
• DOE Early Career Award (2010)
• NSF CAREER Award (2009)

Grants & Projects: Focus on large-scale computational epidemiology, disaster management systems, and AI-driven public health interventions. His lab develops frameworks for epidemic scenario modeling, agent-based simulations, and privacy-preserving analytics.

Labs & Teams: Leads research groups at the Biocomplexity Institute, collaborating on interdisciplinary projects with engineers, epidemiologists, and policymakers to address societal challenges like pandemic response and infrastructure resilience.