Photo of Uday V. Shanbhag

Uday V. Shanbhag

Gary and Sheila Bello Chair Professor

Affiliation(s):

  • Industrial and Manufacturing Engineering

353 Leonhard Building

vvs3@psu.edu

814-865-7601

Personal or Departmental Website

Research Areas:

Operations Research

 
 

 

Education

  • BS, Aerospace Engineering, Indian Institute of Technology, 1993
  • MS, Operations Research, Massachusetts Institute of Technology, 1998
  • MS, Technology and Policy Program, Massachusetts Institute of Technology, 1998
  • Ph D, Management Science and Engineering, Stanford University, 2006

Publications

Journal Articles

  • Shisheng Cui and Uday V Shanbhag, 2021, "On the Analysis of Variance-reduced and Randomized Projection Variants of Single Projection Schemes for Monotone Stochastic Variational Inequality Problems", Set-Valued and Variational Analysis
  • Yue Xie and Uday V Shanbhag, 2021, "Tractable ADMM schemes for computing KKT points and local minimizers for l0 -minimization problems", Computational Optimization and Applications, 78, (1), pp. 43-85
  • Jinlong Lei and Uday V Shanbhag, 2020, "Asynchronous schemes for stochastic and misspecified potential games and nonconvex optimization", Operations Research, 68, (6), pp. 1742-1766
  • Hesam Ahmadi and Uday V Shanbhag, 2020, "On the resolution of misspecified convex optimization and monotone variational inequality problems", Computational Optimization and Applications, 77, (1), pp. 125-161
  • Yue Xie and Uday V Shanbhag, 2020, "SI-ADMM: A Stochastic Inexact ADMM Framework for Stochastic Convex Programs", IEEE Transactions on Automatic Control, 65, (6), pp. 2355-2370
  • Jinlong Lei, Uday V Shanbhag, Jong Shi Pang and Suvrajeet Sen, 2020, "On synchronous, asynchronous, and randomized best-response schemes for stochastic Nash games", Mathematics of Operations Research, 45, (1), pp. 157-190
  • Jinlong Lei and Uday V Shanbhag, 2020, "Asynchronous variance-reduced block schemes for composite non-convex stochastic optimization: block-specific steplengths and adapted batch-sizes", Optimization Methods and Software
  • Aswin Kannan and Uday V. Shanbhag, 2019, "Optimal stochastic extragradient schemes for pseudomonotone stochastic variational inequality problems and their variants", Computational Optimization and Applications, 74, (3), pp. 779-820
  • Afrooz Jalilzadeh, Angelia Nedich, Vinayak Shanbhag and Farzad Yousefian, 2018, "A Variable Sample-Size Stochastic Quasi-Newton Method for Smooth and Nonsmooth Stochastic Convex Optimization", IEEE Conference on Decision and Control
  • Jong-Shi Pang, Suvrajeet Sen and Uday V Shanbhag, 2017, "Two-Stage Non-Cooperative Games with Risk-Averse Players", Mathematical Programming
  • Uma Ravat, Vinayak Shanb andag, , 2017, "On the existence of solutions to stochastic quasi-variational inequality and complementarity problems", Mathematical Programming
  • Farzad Yousefian, Angelia Nedic and Vinayak Shanbhag, 2017, "On smoothing, regularization, and averaging in stochastic approximation methods for stochastic variational inequality problems", Mathematical Programming
  • Hao Jiang and Uday V Shanbhag, 2016, "On the Solution of Stochastic Optimization and Variational Problems in Imperfect Information Regimes", SIAM Journal of Optimization, pp. 32
  • Yue Xie and Vinayak Shanbhag, 2016, "On Robust Solutions to Uncertain Linear Complementarity Problems and their Variants", SIAM Journal on Optimization, 26, (4), pp. 2120–2159
  • Farzad Yousefian, Angelia Nedich and Vinayak Shanbhag, 2016, "Self-Tuned Stochastic Approximation Schemes for Non-Lipschitzian Stochastic Multi-User Optimization and Nash Games.", IEEE Transactions on Automatic Control
  • F. Yousefian, A. Nedich and Vinayak Shanbhag, 2015, "Stochastic approximation schemes for nonsmooth stochastic multi-user optimization and Nash games", IEEE Transactions on Automatic Control, pp. 32
  • Uma Ravat, Uday V. Shanbhag and Richard B. Sowers, 2014, "On the inadequacy of VaR-based risk management: VaR, CVaR, and nonlinearinteractions", Optimization Methods and Software, 29, (4), pp. 877–897
  • Ankur A Kulkarni and Vinayak Shanbhag, 2014, "A shared-constraint approach to multi-leader multi-followergames", Set Valued and Variational Analysis, 22, (4), pp. 691–720
  • Huibing Yin, Prashant G. Mehta, Sean P. Meyn and Vinayak Shanbhag, 2014, "Learning in mean-field games", IEEE Trans. Automat. Control, 59, (3), pp. 629–644
  • Huibing Yin, Prashant G. Mehta, Sean P. Meyn and Vinayak Shanbhag, 2014, "On the efficiency of equilibria in mean-field oscillator games", Dyn. Games Appl., 4, (2), pp. 177–207
  • Matthew J. Robbins, Sheldon H. Jacobson, Vinayak Shanbhag and Banafsheh Behzad, 2014, "The Weighted Set Covering Game: A Vaccine Pricing Model for Pediatric Immunization", INFORMS Journal on Computing, 26, (1), pp. 183–198
  • Ankur A Kulkarni and Uday V Shanbhag, 2014, "An Existence Result for Hierarchical Stackelberg v/s Stackelberg Games", IEEE Transactions on Automatic Control
  • Vinayak Shanbhag, 2013, "Stochastic Variational Inequality Problems: Applications, Analysis, and Algorithms", Informs TUTORIALS in Operations Research, pp. 71 – 107
  • G. Wang, Vinayak Shanbhag, T. Zheng, E. Litvinov and S. Meyn, 2013, "An Extreme-Point Subdifferential Method for Convex Hull Pricing in Energy and Reserve Markets: Part I: Algorithm Structure", IEEE Transactions on Power Systems, 28, (3), pp. 2111-2120
  • G. Wang, Vinayak Shanbhag, T. Zheng, E. Litvinov and S. Meyn, 2013, "An Extreme-Point Subdifferential Method for Convex Hull Pricing in Energy and Reserve Markets: Part II: Convergence Analysis and Numerical Performanc", IEEE Transactions on Power Systems, 28, (3), pp. 2121-2127
  • Aswin Kannan, Vinayak Shanbhag and Harrison M. Kim, 2013, "Addressing supply-side risk in uncertain power markets:stochastic Nash models, scalable algorithms and erroranalysis", Optim. Methods Softw., 28, (5), pp. 1095–1138
  • Dane A. Schiro, Jong-Shi Pang and Vinayak Shanbhag, 2013, "On the solution of affine generalized Nash games via Lemke's method", Mathematical Programming, 142, (1-2, Ser. A), pp. 1–46
  • Jayash Koshal, Angelia Nedic and Vinayak Shanbhag, 2013, "Regularized iterative stochastic approximation methods forstochastic variational inequality problems", IEEE Trans. Automat. Control, 58, (3), pp. 594–609
  • Aswin Kannan and Vinayak Shanbhag, 2012, "Distributed computation of equilibria in monotone Nash gamesvia iterative regularization techniques", SIAM J. Optim., 22, (4), pp. 1177–1205
  • Farzad Yousefian, Angelia Nedic and Vinayak Shanbhag, 2012, "On stochastic gradient and subgradient methods with adaptive steplength sequences", Automatica J. IFAC, 48, (1), pp. 56–67
  • Ankur A. Kulkarni and Vinayak Shanbhag, 2012, "On the variational equilibrium as a refinement of thegeneralized Nash equilibrium", Automatica J. IFAC, 48, (1), pp. 45–55
  • Ankur A. Kulkarni and Vinayak Shanbhag, 2012, "Recourse-based stochastic nonlinear programming: propertiesand Benders-SQP algorithms", Comput. Optim. Appl., 51, (1), pp. 77–123
  • Ankur A. Kulkarni and Vinayak Shanbhag, 2012, "Revisiting generalized Nash games and variationalinequalities", J. Optim. Theory Appl., 154, (1), pp. 175–186
  • H. Yin, P. G. Mehta, S. P. Meyn and U. V. Shanbhag, 2012, "Synchronization of Oscillators is a Game", IEEE Transactions on Automatic Control, 57, (4), pp. 920-935
  • Vinayak Shanbhag, Gerd Infanger and Peter W. Glynn, 2011, "A complementarity framework for forward contracting underuncertainty", Operations Research, 59, (4), pp. 810–834
  • Jayash Koshal, Angelia Nedic and Vinayak Shanbhag, 2011, "Multiuser optimization: distributed algorithms and erroranalysis", SIAM J. Optim., 21, (3), pp. 1046–1081
  • Huibing Yin, Vinayak Shanbhag and Prashant G. Mehta, 2011, "Nash equilibrium problems with scaled congestion costs andshared constraints", IEEE Trans. Automat. Control, 56, (7), pp. 1702–1708
  • Uma Ravat and Vinayak Shanbhag, 2011, "On the characterization of solution sets of smooth andnonsmooth convex stochastic Nash games", SIAM J. Optim., 21, (3), pp. 1168–1199
  • A. Kannan, Vinayak Shanbhag and H. M. Kim, 2011, "Strategic Behavior in Power Markets under Uncertainty", Energy Systems, 2, (2), pp. 115 – 141
  • Umesh Vaidya, Prashant G. Mehta and Vinayak Shanbhag, 2010, "Nonlinear stabilization via control Lyapunov measure", IEEE Trans. Automat. Control, 55, (6), pp. 1314–1328
  • S. Lakhera, Vinayak Shanbhag and M. McInerney, 2010, "Approximating Electrical Distribution Networks via Mixed-integer Nonlinear Programming", International Journal of Electric Power and Energy Systems, 33, (2), pp. 245 – 257
  • S. Lu, N. B. Schroeder, H. M. Kim and Vinayak Shanbhag, 2010, "Hybrid Power/Energy Generation Through Multi-disciplinary and Multilevel Design Optimization With Complementarity Constraints", Transactions of ASME: Journal of Mechanical Design, 132, (10)
  • Walter Murray and Vinayak Shanbhag, 2006, "A local relaxation approach for the siting of electricalsubstations", Comput. Optim. Appl., 33, (1), pp. 7–49
  • S. P. Koruthu and Vinayak Shanbhag, 1993, "A Distributed Parallel Processing Approach to Subsonic Potential Flow Analysis", Journal of Aeronautical Society of India, 45, (2)
  • Jayash Koshal, Angelia Nedich and Vinayak Shanbhag, , "Distributed Algorithms for Aggregative Games on Graphs", Operations Research
  • Hao Jiang, Vinayak Shanbhag and Sean P Meyn, , "Distributed computation of equilibria in misspecified convex stochastic Nash games", IEEE Transactions on Automatic Control (Conditionally Accepted)
  • Jinlong Lei, Uday V Shanbhag, Jong-Shi Pang, Suvrajeet anden, , , "On Synchronous, Asynchronous, and Randomized Best-Response schemes for Stochastic Nash games", Mathematics of Operations Research
  • Afrooz Jalilzadeh, Vinayak Shanbhag, Jose Blanchet and Peter Glynn, , "A Variable Sample-size Accelerated Proximal Method (VS-APM) for Structured Nonsmooth Strongly Convex Stochastic Optimization", Stochastic Systems
  • Afrooz Jalilzadeh, Angelia Nedich, Uday V Shanbhag and Farzad Yousefian, , "A Variable Sample-size Stochastic Quasi-Newton Method for Smooth and Nonsmooth Stochastic Convex Optimization", Mathematics of Operations Research
  • Farzad Yousefian, Angelia Nedich and Uday V Shanbhag, , "On stochastic and deterministic quasi-Newton methods for non-Strongly convex optimization: convergence and rate analysis", SIAM Journal of Optimization, 30, (2), pp. 1144--1172
  • Jinlong Lei and Uday V Shanbhag, , "Distributed Variable Sample-Size Gradient-response and Best-response Schemes for Stochastic Nash Equilibrium Problems over Graphs", SIAM Journal of Optimization
  • Min Gyung Yu, Gregory Pavlak and Vinayak Shanbhag, , "Uncertainty-aware optimal dispatch of building thermal storage portfolios via smoothed variance-reduced accelerated gradient methods", Journal of Energy Storage
  • Farzad Yousefian, Angelia Nedich and Vinayak Shanbhag, , "On stochastic mirror-prox algorithms for stochastic Cartesian variational inequalities: randomized block coordinate and optimal averaging schemes", Set-Valued and Variational Analysis
  • Afrooz Jalilzadeh, Angelia Nedich, Vinayak Shanbhag and Farzad Yousefian, , "A Variable Sample-size Stochastic Quasi-Newton Method for Smooth and Nonsmooth Stochastic Convex Optimization", Mathematics of Operations Research
  • Chiara Lo Prete, Nongchao Guo and Vinayak Shanbhag, , "Virtual Bidding and Financial Transmission Rights: An Equilibrium Model for Cross-Product Manipulation in Electricity Markets", IEEE Transactions on Power Systems
  • Necdet S Aybat, Hesam Ahmadi and Uday V Shanbhag, , "On the analysis of inexact augmented Lagrangian schemes for misspecified conic convex programs", IEEE Transactions on Automatic Control
  • Hesam Ahmadi and Vinayak Shanbhag, , "On the resolution of misspecified convex optimization and monotone variational inequality problems", Computational Optimization and Applications
  • Aswin Kannan and Vinayak Shanbhag, , "Optimal stochastic extragradient schemes for pseudomonotone stochastic variational inequality problems and their variants", Computational Optimization and Applications
  • Yue Xie and Vinayak Shanbhag, , "SI-ADMM: A Stochastic Inexact ADMM Framework for Stochastic Convex Programs", IEEE Transactions on Automatic Control
  • Jinlong Lei and Vinayak Shanbhag, , "Asynchronous Schemes for Stochastic and Misspecified Potential Games and Nonconvex Optimization", Operations Research

Conference Proceedings

  • Jinlong Lei, Uday V Shanbhag and Jie Chen, 2020, "Distributed Computation of Nash Equilibria for Monotone Aggregative Games via Iterative Regularization", 2020-December, pp. 2285-2290
  • Afrooz Jalilzadeh and Vinayak Shanbhag, 2019, "A Proximal-Point Algorithm with Variable Sample-Sizes (PPAWSS) for Monotone Stochastic Variational Inequality Problems", Winter Simulation Conference
  • Eunhye Song and Vinayak Shanbhag, 2019, "Stochastic Approximation for simulation Optimization under Input Uncertainty with Streaming Data", Winter Simulation Conference
  • Afrooz Jalilzadeh and Uday V. Shanbhag, 2019, "A Proximal-Point Algorithm with Variable Sample-Sizes (PPAWSS) for Monotone Stochastic Variational Inequality Problems", 2019-December, pp. 3551-3562
  • Eunhye Song and Uday V. Shanbhag, 2019, "Stochastic Approximation for simulation Optimization under Input Uncertainty with Streaming Data", 2019-December, pp. 3597-3608
  • Jinlong Lei and Vinayak Shanbhag, 2018, "Linearly Convergent Variable Sample-Size Schemes for Stochastic Nash Games: Best-Response Schemes and Distributed Gradient-Response Schemes.", IEEE Conference on Decision and Control
  • Jinlong Lei and Uday V Shanbhag, 2017, "An Inexact Randomized Best Response Scheme for Stochastic Potential Games"
  • Farzad Yousefian, Angelia Nedic and Vinayak Shanbhag, 2017, "A smoothing stochastic quasi-Newton method for non-Lipschitzian stochastic optimization problems", Winter Simulation Conference
  • George Kesidis, Vinayak Shanbhag, Neda Nasirani and Bhuvan Urgaonkar, 2017, "Competition and Peak-Demand Pricing in Clouds Under Tenants' Demand Response", MASCOTS
  • Afrooz Jalilzadeh and Vinayak Shanbhag, 2016, "eg-VSSA: An extragradient variable sample-size stochastic approximation scheme: Error analysis and complexity trade-offs", pp. 690–701
  • Vinayak Shanbhag, Jong-Shi Pang and Suvrajeet Sen, 2016, "Inexact best-response schemes for stochastic Nash games: Linear convergence and Iteration complexity analysis", pp. 3591–3596
  • Yue Xie and Vinayak Shanbhag, 2016, "SI-ADMM: A stochastic inexact ADMM framework for resolving structured stochastic convex programs", pp. 714–725
  • Farzad Yousefian, Angelia Nedic and Vinayak Shanbhag, 2016, "Stochastic quasi-Newton methods for non-strongly convex problems: Convergence and rate analysis", pp. 4496–4503
  • Hao Jiang and Vinayak Shanbhag, 2015, "Data-driven Schemes for Resolving Misspecified MDPs"
  • A. Kannan, A. Nedich and Vinayak Shanbhag, 2015, "Distributed Stochastic Optimization under Imperfect In-formation"
  • Hesam Ahmadi and Uday V Shanbhag, 2014, "Data-driven first-order methods for misspecified convex optimization problems: Global convergence and Rate estimates", pp. 4228-4233
  • Farzad Yousefian, Angelia Nedic and Uday V Shanbhag, 2014, "Optimal robust smoothing extragradient algorithms for stochastic variational inequality problems", pp. 5831-5836
  • Aswin Kannan and Uday V Shanbhag, 2014, "The pseudomonotone stochastic variational inequality problem: Analytical statements and stochastic extragradient schemes", pp. 2930-2935
  • Yue Xie and Uday V Shanbhag, 2014, "On robust solutions to uncertain monotone linear complementarity problems (LCPs) and their variants", pp. 2834-2839
  • Cheng Wang, Bhuvan Urgaonkar, George Kesidis, Uday V Shanbhag and Qian Wang, 2014, "A Case for Virtualizing the Electric Utility in Cloud Data Centers"
  • F. Yousefian, A. Nedic and Vinayak Shanbhag, 2013, "A regularized smoothing stochastic approximation (RSSA) algorithm for stochastic variational inequality problems", pp. 933-944
  • Hao Jiang and Vinayak Shanbhag, 2013, "On the solution of stochastic optimization problems in imperfect information regimes", pp. 821-832
  • F. Yousefian, A. Nedic and Vinayak Shanbhag, 2013, "A distributed adaptive steplength stochastic approximation method for monotone stochastic Nash Games", pp. 4765-4770
  • Bhuvan Urgaonkar, George Kesidis, Vinayak Shanbhag and C. Wang, 2013, "Pricing of Service in Clouds: Optimal Re-sponse and Strategic Interactions"
  • Vinayak Shanbhag, 2013, "On the consistency of leaders' conjectures in hierarchical games", CDC 2013, pp. 1180-1185
  • B. Urgaonkar, G. Kesidis, Vinayak Shanbhag and C. Wang, 2013, "Pricing of service in clouds: optimal response and strategic interactions", SIGMETRICS Performance Evaluation Review, 41, (3), pp. 28-30
  • J. Koshal, A. Nedic and Vinayak Shanbhag, 2012, "A gossip algorithm for aggregative games on graphs", pp. 4840-4845
  • Gui Wang, Vinayak Shanbhag and S.P. Meyn, 2012, "On Nash equilibria in duopolistic power markets subject to make-whole uplift", pp. 472-477
  • Hao Jiang and Vinayak Shanbhag, 2012, "On the convergence of joint schemes for online computation and supervised learning", pp. 4462-4467
  • M. Roytman, Vinayak Shanbhag, J.B. Cardell and C.L. Anderson, 2012, "Packaging Energy and Reserves Bids through Risk Penalties for Enhanced Reliability in Co-optimized Markets", pp. 1915-1922
  • Gui Wang, M. Negrete-Pincetic, A. Kowli, E. Shafieepoorfard, S. Meyn and Vinayak Shanbhag, 2012, "Real-time prices in an entropic grid", pp. 1-8
  • Huibing Yin, P.G. Mehta, S.P. Meyn and Vinayak Shanbhag, 2011, "Bifurcation analysis of a heterogeneous mean-field oscillator game model", pp. 3895-3900
  • Hao Jiang, Vinayak Shanbhag and S.P. Meyn, 2011, "Learning equilibria in constrained Nash-Cournot games with misspecified demand functions", pp. 1018-1023
  • J. Koshal, A. Nedic and Vinayak Shanbhag, 2011, "Single timescale stochastic approximation for stochastic Nash games in cognitive radio systems", pp. 1-8
  • Huibing Yin, P.G. Mehta, S.P. Meyn and Vinayak Shanbhag, 2011, "On the efficiency of equilibria in mean-field oscillator games", pp. 5354-5359
  • G. Wang, Vinayak Shanbhag, T. Zheng, E. Litvinov and S. P. Meyn, 2011, "A Pivot-Based Global Optimization Technique for Convex Hull Pricing"
  • A. Kannan and Vinayak Shanbhag, 2010, "Distributed iterative regularization algorithms for monotone Nash games", pp. 1963-1968
  • Huibing Yin, P.G. Mehta, S.P. Meyn and Vinayak Shanbhag, 2010, "Learning in mean-field oscillator games", pp. 3125-3132
  • J. Koshal, A. Nedic and Vinayak Shanbhag, 2010, "Single timescale regularized stochastic approximation schemes for monotone Nash games under uncertainty", pp. 231-236
  • Huibing Yin, P.G. Mehta, S.P. Meyn and Vinayak Shanbhag, 2010, "Synchronization of coupled oscillators is a game", pp. 1783-1790
  • U. Ravat and Vinayak Shanbhag, 2010, "On the characterization of solution sets of smooth and nonsmooth stochastic Nash games", pp. 5632-5637
  • F. Yousefian, Nedic´, A. and Vinayak Shanbhag, 2010, "Convex nondifferentiable stochastic optimization: A local randomized smoothing technique", pp. 4875-4880
  • J. Koshal, A. Nedic and Vinayak Shanbhag, 2009, "Distributed multiuser optimization: Algorithms and error analysis", pp. 4372-4377
  • Huibing Yin, Vinayak Shanbhag and P.G. Mehta, 2009, "Nash equilibrium problems with congestion costs and shared constraints", pp. 4649-4654
  • Huibing Yin, C.L. Cox, P.G. Mehta and Vinayak Shanbhag, 2009, "Bifurcation analysis of a thalamic relay neuron model", pp. 337-342
  • S. Lu, Vinayak Shanbhag and H. M. Kim, 2008, "Multidisciplinary and Multilevel Design Optimization Problemswith Equilibrium Constraints"
  • U. Vaidya, P.G. Mehta and Vinayak Shanbhag, 2007, "Nonlinear stabilization via control-Lyapunov measure", pp. 1722-1727
  • A. A. Kulkarni, A. Rossi, J. Alameda and Vinayak Shanbhag, 2007, "A Grid-Computing Framework for QuadraticProgramming under Uncertainty"
  • Vinayak Shanbhag, G. Infanger and P. W. Glynn, 2004, "On the Solution of Stochastic Equilibrium Problems inElectric Power Networks"
  • Vinayak Shanbhag, L. K. Norford, S. E. Englander and M. C. Caramanis, 1998, "Price Responsive Facility ControlOptimization Software for a Changing Retail Market"
  • Ibrahim E Bardakc, Constantino M Lagoa and Vinayak Shanbhag, , "Probability Maximization with Random Linear Inequalities: Alternative Formulations and Stochastic Approximation Schemes", American Control Conference

Research Projects

Honors and Awards

Service

Service to Penn State:

Service to External Organizations:

  • Participation in or Service to Professional and Learned Societies, Board Member, Associate Editor, SIAM Journal of Optimization, January 2020
  • Participation in or Service to Professional and Learned Societies, Board Member, Associate Editor, Computational Optimization and Applications, July 2019
  • Participation in or Service to Professional and Learned Societies, Board Member, Associate Editor, Optimization Letters, July 2019
 


 

About

Home of the first established industrial engineering program in the world, the Harold and Inge Marcus Department of Industrial and Manufacturing Engineering (IME) at Penn State has made a name for itself in the engineering industry through its storied tradition of unparalleled excellence and innovation in research, education, and outreach.

We are Innovators. We are Makers. We are Excellence in Engineering. We are Penn State IME.

The Harold and Inge Marcus Department of
Industrial and Manufacturing Engineering

310 Leonhard Building

The Pennsylvania State University

University Park, PA 16802-4400

Phone: 814-865-7601

FAX: 814-863-4745