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Rohit Kannan

Assistant Professor
Rohit Kannan
233 Durham Hall
(MC 0118)
1145 Perry Street
Blacksburg, VA 24061
rohitkannan@vt.edu
google scholar
Curriculum Vitae
PERSONAL WEBSITE

For Prospective PhD Students: I am looking for highly motivated Ph.D. students with a strong background in mathematics or operations research and a keen interest in machine learning. Please feel free to reach out to me, and attach your resume and unofficial transcripts.

  • Ph.D., Chemical Engineering, Massachusetts Institute of Technology, 2018
  • M.S., Chemical Engineering Practice, Massachusetts Institute of Technology, 2014
  • B.Tech., Chemical Engineering, Indian Institute of Technology Madras, 2012
  • Assistant Professor, Industrial and Systems Engineering, Virginia Tech, 2023 - present
  • Postdoctoral Associate, Center for Nonlinear Studies and Applied Mathematics & Plasma Physics, Los Alamos National Laboratory, 2021 - 2023
  • Postdoctoral Associate, Wisconsin Institute for Discovery, University of Wisconsin-Madison, 2018 - 2020
  • Learning + Optimization
  • Optimization Under Uncertainty
  • Global Optimization 
  • Computational Optimization 
  • Energy & Process Systems
  • E. M. Turan, J. Jäschke, and R. Kannan (2023). "Optimality-Based Discretization Methods for the Global Optimization of Nonconvex Semi-Infinite Programs," pp. 1-22, under review.
  • R. Kannan, H. Nagarajan, and D. Deka (2023). "Learning to Accelerate the Global Optimization of Quadratically-Constrained Quadratic Programs," pp. 1-27, under review.
  • R. Kannan, G. Bayraksan, and J. R. Luedtke (2023). "Data-driven sample average approximation with covariate information," pp. 1-57, under revision.
  • R. Kannan, G. Bayraksan, and J. R. Luedtke (2023). "Residuals-based distributionally robust optimization with covariate information," Forthcoming in Mathematical Programming. 
  • R. Kannan and J. R. Luedtke (2021). "A stochastic approximation method for approximating the efficient frontier of chance-constrained nonlinear programs," Mathematical Programming Computation, 13, pp. 705–751. 
  • R. Kannan, J. R. Luedtke, and L. A. Roald (2020). "Stochastic DC optimal power flow with reserve saturation," Electric Power Systems Research (special issue for the XXI Power Systems Computation Conference), pp. 1-9. 
  • R. Kannan and P. I. Barton (2018). "Convergence-order analysis of branch-and-bound algorithms for constrained problems," Journal of Global Optimization, 71(4), pp. 753-813. 
  • R. Kannan and P. I. Barton (2017). "The cluster problem in constrained global optimization," Journal of Global Optimization, 69(3), pp. 629-676.