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Manish Bansal

Associate Professor
  • Grado Faculty Fellow

Manish Bansal

Bansal
Manish Bansal
227 Durham Hall
(MC 0118)
1145 Perry Street
Blacksburg, VA 24061

For Prospective PhD Students: I have funded GRA positions for students who have strong background in Mathematics, Operations Research, Computer Science, or other related fields, and are interested in theory and algorithms for Stochastic/Robust/Integer Optimization, Machine Learning, Game Theory, and Computational Geometry, and their applications in cybersecurity and supply chain management. If you are interested in this position, please email me your resume and transcripts.

 

Research Areas

Main Area:  Operations Research, Game Theory, Machine Learning, Data-Driven Optimization, Decision Making under Uncertainty

  • Methodology: Stochastic and Distributionally Robust Integer Programming, Graph Neural Networks, Combinatorial Optimization, and Location Science.
  • Applications: Supply Chain, Logistics, Aerospace Structures, Network Designing, and Telerobotics

 

Other VT Affliliations

  • President, Engineering Faculty Organization, 2023-2024
  • Core Faculty, Sanghani Center for Artificial Intelligence and Data Analytics Webpage
  • Affiliate Faculty, National Security Institute, VT

 

  • Ph.D., Industrial and Systems Engineering, Texas A&M University
  • M.S. (Thesis), Industrial and Systems Engineering, Texas A&M University
  • B.Tech., Electrical Engineering, National Institute of Technology, India
  • Associate Professor, Department of Industrial and Systems Engineering, Virginia Tech, August 2022 - Present
  • Core Faculty Member, Sanghani Center for Artificial Intelligence and Data Analytics, Computer Science Department, Virginia Tech, Sept 2023 - Present
  • Affiliate Faculty Member, National Security Institute, Virginia Tech, Aug 2022 - Present
  • Assistant Professor, Department of Industrial and Systems Engineering, Virginia Tech, August 2016 - July 2022
  • Postdoctoral Fellow, Department of Industrial Engineering and Management Sciences, Northwestern University, October 2014 - August 2016
  • Research Assistant,  Department of Industrial and Systems Engineering, Texas A&M University, January 2011 - July 2014
  • ISE 2404: Deterministic Operations Research I
  • ISE 5405: Optimization I
  • ISE 5406: Optimization II
  • ISE 5984: Large-Scale Stochastic Optimization

For the latest list of publications, please refer to my CV or Google Scholar Page. Please click a title in orange to view the abstract. Students are indicated with *

[P28] S. Kang* and M. Bansal, “Distributionally ambiguous multistage stochastic integer and disjunctive programs: Applications to sequential two-player interdiction games,” under review, 2023

[P27] S. Park*, M. Bansal, “Algorithms for cameras view-frame placement problems in the presence of an adversary with distributional ambiguity,” IEEE Transactions on Automation Science and Engineering (Accepted). 2023. 

[P26] M. Bansal, “Semi-infinite generalized disjunctive and mixed integer convex programs with(out) uncertainty,” under review, 2023.

[P25]  M. Bansal, ``Semi-infinite mixed binary and disjunctive programs: Applications to implicit hitting set and set-covering with infinite demand points," under review, 2023.

[P24] K. Kulkarni* and M. Bansal, “Transportation and inventory planning in serial supply chain with heterogeneous capacitated vehicles,''Management Science (Major Revision), December 2022.

[P23] K. Kulkarni* and M. Bansal, "Exact algorithms for multi-module capacitated lot-sizing problem, and its generalizations with two-echelons and piecewise concave production costs," IISE Transactions, 2022.

[P22] S. Kang*, M. Bansal, "Distributionally risk-receptive and risk-averse network interdiction problems with general ambiguity set," Networks 81(1), 3-22, 2022.

[P21] K. Kulkarni*, M. Bansal, "Discrete Multi-Module Capacitated Lot-Sizing Problems with Multiple Items," Operations Research Letters 50 (2), 168-175, 2022.

[P20] H. Gangammanavar, M. Bansal, "Stochastic Decomposition Method for Two-Stage Distributionally Robust Optimization," SIAM Journal on Optimization 32(3), 1901-1930, 2022.

[P19] P. Borwankar*, W. Zhao, R. Kapania, M. Bansal, “Optimization of hybrid composite laminates with distinct ply thicknesses using integer programming," American Institute of Aeronautics and Astronautics (AIAA) Journal (Accepted), 2022.

[P18] P. Borwankar*, W. Zhao, R. K. Kapania, and M. Bansal, "Two-level Weight Optimization of Composite Laminates using Integer Programming," American Institute of Aeronautics and Astronautics (AIAA) Journal 60(11), 6436-6446, 2022.

 [P17] M. Bansal, Y. Zhang*, "Scenario-based cuts for two-stage stochastic and distributionally robust p-order conic mixed integer programs," Journal on Global Optimization 81, 391-433, 2021.

[P16] M. Bansal, P. Shojaee*, “Planar Maximum Coverage Location Problem with Partial Coverage, Continuous Spatial Demand, and Adjustable Quality of Service”, Technical Report, 2020.

[P15] Y. Zhang*, M. Bansal, A. R. Escobedo, "Risk-neutral and risk-averse transmission switching for load shed recovery with uncertain renewable generation and demand," IET Generation, Transmission & Distribution 14 (21), 4936-4945, 2020.

[P14] P. Borwankar*, W. Zhao, R. K. Kapania, and M. Bansal, "Two-level Weight Optimization of Composite Laminates using Integer Programming," American Institute of Aeronautics and Astronautics (AIAA) SciTech Forum, 2021.

[P13] M. Bansal, S. Mehrotra, "On solving two-stage distributionally robust disjunctive programs with a general ambiguity set," European Journal of Operational Research 279(2), 296-307, 2019..

[P12] M. Bansal, "Facets for single module and multi-module capacitated lot-sizing problems without backlogging," Discrete Applied Mathematics, 255, 117-141, 2019.

[P11] M. Bansal, K. L. Huang, S. Mehrotra, "Decomposition algorithms for two-stage distributionally robust mixed binary programs," SIAM Journal on Optimization, 28(3), 2360-2383, 2018.

[P10] J. Hu, M. Bansal, S. Mehrotra, "​Robust decision making using a general utility set," European Journal of Operational Research, 269(2), 699-714, 2018.

[P9] M. Bansal, K. L. Huang, S. Mehrotra, "Tight second-stage formulations for two-stage stochastic mixed integer programming problems," SIAM Journal on Optimization, 28(1), 788-819, 2018.

[P8] M. Bansal, K. Kianfar, "Planar maximum coverage location problem with partial coverage and rectangular demand and service zones," INFORMS Journal on Computing, 29(1), 152-169, 2017.

[P7] M. Bansal, K. Kianfar, "Facets for the continuous multi-mixing set with general coefficients and bounded integer variables," Discrete Optimization, 26, 1-25, 2017.

[P6] M. Bansal, "Planar Maximum Coverage Location Problem with Partial Coverage and General Spatial Representation of Demand and Service Zones," Technical Report, 2017.

[P5] M. Bansal, K. Kianfar, "n-step cycle inequalities: facets for the continuous multi-mixing set and strong cuts for multi-module capacitated lot-sizing problem," Mathematical Programming, 154 (1), 113-144, 2015.

[P4] M. Bansal, K. Kianfar, "n-step cycle inequalities: facets for the continuous n-mixing set and strong cuts for multi-module capacitated lot-sizing problem (extended abstract)," In: Lee, J., Vygen, J. (eds) Integer Programming and Combinatorial Optimization. IPCO 2014. Lecture Notes in Computer Science, vol 8494. Springer.

[P3] M. Bansal, K. Kianfar, Y. Ding, and E. Moreno-Centeno, "Hybridization of bound-and-decompose and mixed integer feasibility to measure redundancy in structured linear systems," IEEE Transactions on Automation Science and Engineering, 10(4): 1151-1157, 2013.

[P2] A. Sen, A. Banerjee, A. Sinha, and M. Bansal, "Clinical decision support: Converging toward an integrated architecture," Journal of Biomedical Informatics, 45(5): 1009-1017, 2012.

[P1] M. Bansal, K. Kianfar, "An exact algorithm for coverage problem with a single rectangle," Proceedings of Industrial Engineering Research Conference, Cancun, 2010. 

  • Modeling and Solution of Planar Facility Location Problems with Uncertainty. Sponsor: National Science Foundation. Role: PI. Share: 100%. Aug 2018 - August 2023.
  • Novel Algorithms for Multi-Agent Autonomous Telerobotic Surveillance and Reconnaissance System. Sponsor: Automotive Research Center at University of Michigan; Role: PI; Share: 100%, Jan 2020 - July 2023.
  • Novel Modeling and Analytical Approaches for Two-stage Assembly and Related Lot Streaming Problems. Sponsor: National Science Foundation. Role: Co-PI. Share: 50%. July 2021 - June 2024.
  • Managing Data for Autonomous Vehicles. Sponsor: Cyber Commonwealth Initiative, Southwest Virginia; Role: PI; Share: 100%, July 2022 - June 2023
  • Novel Algorithms for Stochastic Mixed Integer Programs with Application in Aircraft Designing under Uncertainty, ICTAS Junior Faculty Award, VT. Role: PI. Share: 67%. 2019-2021.
  • Novel Data-Driven Algorithms for Autonomous Vehicle Path Planning Problems with Uncertain Data Parameters, Ground Vehicle Systems and Automotive Research Center, Michigan. Role: Co-PI. Share: 40%, 2019.
  • Institute for Operations Research and the Management Sciences (INFORMS) - Member since 2010 
  • Institute of Industrial and Systems Engineers (IISE) - Member since 2016
  • Society for Industrial and Applied Mathematics (SIAM) - Member since 2018
  • Mathematical Optimization Society - Member since 2018
  • Elected President (2023-2024), Vice-President (2022-2023), and Secretary (2021-2022), Engineering Faculty Organization (EFO), VT, 2022-2023.
  • Operations Research Area Lead, Industrial and Systems Engineering, Virginia Tech, 2023 - present.
  • Chair, Optimization OR Faculty Search Committee, ISE-VT, 2022-2023.
  • Elected Vice-President/President-Elect for INFORMS Junior Faculty Interest Group (JFIG), 2020-21; President of JFIG in 2021-22.
  • Organizing Committee Member (Scheduling Chair), 2022 INFORMS Conference on Security, Arlington, VA.
  • Stakeholder Committee Member, Apex Center for Entrepreneurs, Pamplin College of Business, Virginia Tech, Dec 2022 - present.
  • Member of 2022 INFORMS Computing Society Student Paper Competition Committee.