Preprints

  • A. Capponi, G. Iyengar, B. Yang, and D. Bienstock. Virtual Trading in Multi-Settlement Electricity Markets. 2025. [arXiv].

  • G. Iyengar, Y.S.F. Ma, and J. Sethuraman. Regulatory Inefficacy of Bundling in Platform Fulfillment Services. 2025. [SSRN].

  • G. Iyengar, Y.S. Lin, and K. Wang. Model-Free Assessment of Simulator Fidelity via Quantile Curves. 2025. [arXiv].

  • T. Nan, S. Das Gupta, G. Iyengar, and C. Kroer. On the O(1/T) convergence of alternating gradient descent-ascent in bilinear games. 2025. [arXiv].

  • J. Cerny, C.K. Ling, D. Chakrabarti, J. Zhang, G. Farina, C. Kroer, and G. Iyengar. Contested Logistics: A Game-Theoretic Approach. 2024. [arXiv].

  • G. Iyengar, H. Lam, and T. Wang. Optimizer’s Information Criterion: Dissecting and Correcting Bias in Data-Driven Optimization. 2024. [arXiv].

  • G. Iyengar and R. Singal. Online Matching with Heterogeneous Supply and Minimum Allocation Guarantees. 2024. [SSRN].

  • A. Capponi, G. Iyengar, B. Yang, and D. Bienstock. Virtual Trading in a Multi-Settlement Electricity Market. 2024. [SSRN].

  • A. Federgruen, G. Guetta, G. Iyengar, and X. Liu. An Asymptotically Optimal Heuristic for Multi-Item Inventory Models with Joint Inventory Constraints. 2022. [SSRN].

  • A. Federgruen, G. Guetta, G. Iyengar, and X. Liu. Scalable Approximately Optimal Policies for Multi-Item Stochastic Inventory Problems. 2022. [SSRN].

  • G. Iyengar and M. Perry. Transient Kinetic Proofreading. 2021. [bioRxiv].

  • V. Goyal, G. Iyengar, and R. Udwani. Online Allocation of Reusable Resources: Achieving Optimal Competitive Ratio. 2020. [arXiv].

  • V. Goyal, G. Iyengar, and R. Udwani. Online Allocation of Reusable Resources via Algorithms Guided by Fluid Approximations. 2020. [arXiv].

  • H. Cooper, G. Iyengar, and C.Y. Lin. Attainment Ratings for Graph-Query Recommendation. 2018. [arXiv].

  • M.H. Oh and G. Iyengar. Directed exploration in PAC model-free reinforcement learning. 2018. [arXiv].

  • F. Fagan and G. Iyengar. Unbiased scalable softmax optimization. 2018. [arXiv].

  • F. Fagan and G. Iyengar. Robust implicit backpropagation. 2018. [arXiv].

  • J. Blanchet, D. Goldfarb, G. Iyengar, F. Li, and C. Zhou. Unbiased simulation for optimizing stochastic function compositions. 2017. [arXiv].

  • D. Goldfarb, G. Iyengar, and C. Zhou. Semi-Stochastic Frank-Wolfe Algorithms with Away-Steps for Block-Coordinate Structure Problems. 2016. [arXiv].

  • N.S. Aybat and G. Iyengar. An augmented Lagrangian method for conic convex programming. 2013. [arXiv].

  • N.S. Aybat, D. Goldfarb, and G. Iyengar. Fast first-order methods for stable principal component pursuit. 2011. [arXiv].

  • R.A. Carrasco, G. Iyengar, and C. Stein. Energy aware scheduling for weighted completion time and weighted tardiness. 2011. [arXiv].

  • G. Gallego, G. Iyengar, R. Phillips, and A. Dubey. Managing Flexible Products on a Network. 2004. [SSRN].

  • G. Iyengar. Discrete time growth optimal investment with transaction costs. 2002. [SSRN].

Journal Articles

  • V. Goyal, G. Iyengar, and R. Udwani. Asymptotically optimal competitive ratio for online allocation of reusable resources. Operations Research, 2025 [arXiv].

  • G. Iyengar and M. Perry. Game-Theoretic Flux Balance Analysis Model for Predicting Stable Community Composition. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 21(6):2394-2405, 2024.

  • G. Iyengar and R. Singal. Model-Free Approximate Bayesian Learning for Large-Scale Conversion Funnel Optimization. Production and Operations Management, 33(3):775–794, 2024 [arXiv].

  • G. Iyengar, F. Saleh, J. Sethuraman, and W. Wang. Blockchain adoption in a supply chain with manufacturer market power. Management Science, 70(9):6158–6178, 2024 [SSRN].

  • O. Besbes, V. Goyal, G. Iyengar, and R. Singal. Workforce Scheduling with Heterogeneous Time Preferences: Effective Wages and Workers’ Supply. Manufacturing & Service Operations Management, 26(5):1768–1786, 2024.

  • G. Iyengar, H. Lam, and T. Wang. Is Cross-validation the Gold Standard to Estimate Out-of-sample Model Performance?. Advances in Neural Information Processing Systems, 37:94736–94775, 2024 [arXiv].

  • M. Shridharan and G. Iyengar. Scalable Computation of Causal Bounds. Journal of Machine Learning Research, 24(237):1–35, 2023 [arXiv].

  • G. Costa and G.N. Iyengar. Distributionally robust end-to-end portfolio construction. Quantitative Finance, 2023 [arXiv].

  • G. Iyengar, F. Saleh, J. Sethuraman, and W. Wang. Economics of permissioned blockchain adoption. Management Science, 69(6):3415–3436, 2023 [SSRN].

  • A. Capponi, G. Iyengar, and J. Sethuraman. Decentralized finance: Protocols, risks, and governance. Foundations and Trends in Privacy and Security, 5(3):144–188, 2023 [arXiv].

  • Y. Chen, G. Iyengar, and C. Wang. Robust Inventory Management: A Cycle-Based Approach. Manufacturing & Service Operations Management, 2022 [SSRN].

  • X.Y. Gong, V. Goyal, G. Iyengar, D. Simchi-Levi, R. Udwani, and S. Wang. Online assortment optimization with reusable resources. Management Science, 68(7):4772–4785, 2022 [SSRN].

  • A. Yadav, Q. Vagne, P. Sens, G. Iyengar, and M. Rao. Glycan processing in the Golgi as optimal information coding that constrains cisternal number and enzyme specificity. Elife, 11:e76757, 2022 [bioRxiv].

  • C. Koçyiğit, G. Iyengar, D. Kuhn, and W. Wiesemann. Distributionally robust mechanism design. Management Science, 66(1):159–189, 2020 [SSRN].

  • H. Alsabah, B. Bernard, A. Capponi, G. Iyengar, and J. Sethuraman. Multiregional oligopoly with capacity constraints. Management Science, 2020 [SSRN].

  • R. Singal, O. Besbes, A. Desir, V. Goyal, and G. Iyengar. Shapley Meets Uniform: An Axiomatic Framework for Attribution in Online Advertising. Management Science, 68(10):7457–7479, 2022 [SSRN] [WWW 2019].

  • Y. Luo, G. Iyengar, and V. Venkatasubramanian. A One-Third Advice Rule Based on a Control-Theoretic Opinion Dynamics Model. IEEE Transactions on Computational Social Systems, 6(3):576–581, 2019.

  • R. Mazumder, A. Choudhury, G. Iyengar, and B. Sen. A computational framework for multivariate convex regression and its variants. Journal of the American Statistical Association, 114(525):318–331, 2019 [arXiv].

  • O. Toubia, G. Iyengar, R. Bunnell, and A. Lemaire. Extracting features of entertainment products: A guided Latent Dirichlet Allocation approach informed by the psychology of media consumption. Journal of Marketing Research, 56(1):18–36, 2019.

  • S. Keshri, M.H. Oh, S. Zhang, and G. Iyengar. Automatic event detection in basketball using HMM with energy based defensive assignment. Journal of Quantitative Analysis in Sports, 15(2):141–153, 2019 [RePec].

  • C. Dolan, J. Blanchet, G. Iyengar, and U. Lall. A model robust real options valuation methodology incorporating climate risk. Resources Policy, 57:81–87, 2018.

  • S.G. Das, M. Rao, and G. Iyengar. Cascade of transitions in molecular information theory. Journal of Statistical Mechanics: Theory and Experiment, 2018(9):093402, 2018 [arXiv].

  • R.A. Carrasco, G. Iyengar, and C. Stein. Resource cost aware scheduling. European Journal of Operational Research, 269(2):621–632, 2018 [RePec].

  • M. Haas-Heger, G. Iyengar, and M. Ciocarlie. Passive reaction analysis for grasp stability. IEEE Transactions on Automation Science and Engineering, 15(3):955–966, 2018.

  • Y. Luo, G. Iyengar, and V. Venkatasubramanian. Social influence makes self-interested crowds smarter: An optimal control perspective. IEEE Transactions on Computational Social Systems, 5(1):200–209, 2018.

  • A. Federgruen, C.D. Guetta, and G. Iyengar. Two-echelon distribution systems with random demands and storage constraints. Naval Research Logistics, 65(8):594–618, 2018 [SSRN].

  • M. Haugh, G. Iyengar, and I. Song. A generalized risk budgeting approach to portfolio construction. Computational Finance, 21(2):29–60, 2017 [SSRN].

  • Y. Chen, R. Iyengar, and G. Iyengar. Modeling multimodal continuous heterogeneity in conjoint analysis—a sparse learning approach. Marketing Science, 36(1):140–156, 2017.

  • S.G. Das, M. Rao, and G. Iyengar. Universal lower bound on the free-energy cost of molecular measurements. Physical Review E, 95(6):062410, 2017 [arXiv].

  • Y. Luo, G. Iyengar, and V. Venkatasubramanian. Soft regulation with crowd recommendation: Coordinating self-interested agents in sociotechnical systems under imperfect information. PloS one, 11(3), 2016.

  • G. Iyengar and A.K.C. Ma. A robust optimization approach to pension fund management. Asset Management, 2016.

  • M. Haugh, G. Iyengar, and C. Wang. Tax-aware dynamic asset allocation. Operations Research, 64(4):849–866, 2016 [PDF].

  • R. Bookstaber, P. Glasserman, G. Iyengar, Y. Luo, V. Venkatasubramanian, and Z. Zhang. Process systems engineering as a modeling paradigm for analyzing systemic risk in financial networks. The Journal of Investing, 24(2):147–162, 2015 [RePec].

  • C. Abad and G. Iyengar. Portfolio selection with multiple spectral risk constraints. SIAM Journal on Financial Mathematics, 6(1):467–486, 2015 [arXiv].

  • C. Abad and G. Iyengar. A near-optimal maintenance policy for automated DR devices. IEEE Transactions on Smart Grid, 7(3):1411–1419, 2015 [arXiv].

  • N.S. Aybat and G. Iyengar. An alternating direction method with increasing penalty for stable principal component pursuit. Computational Optimization and Applications, 61(3):635–668, 2015 [arXiv].

  • D. Soudry, S. Keshri, P. Stinson, M.H. Oh, G. Iyengar, and L. Paninski. Efficient shotgun inference of neural connectivity from highly sub-sampled activity data. PLoS Computational Biology, 11(10), 2015.

  • G. Iyengar and M. Rao. A cellular solution to an information-processing problem. PNAS, 111(34):12402–12407, 2014.

  • N.S. Aybat and G. Iyengar. A unified approach for minimizing composite norms. Mathematical Programming, 144(1-2):181–226, 2014 [arXiv].

  • G. Iyengar and A.K.C. Ma. Fast gradient descent method for mean-CVaR optimization. Annals of Operations Research, 205(1):203–212, 2013.

  • R.A. Carrasco, G. Iyengar, and C. Stein. Single machine scheduling with job-dependent convex cost and arbitrary precedence constraints. Operations Research Letters, 41(5):436–441, 2013.

  • C. Chen, G. Iyengar, and C.C. Moallemi. An axiomatic approach to systemic risk. Management Science, 59(6):1373–1388, 2013.

  • N.S. Aybat and G. Iyengar. A first-order augmented Lagrangian method for compressed sensing. SIAM Journal on Optimization, 22(2):429–459, 2012 [arXiv].

  • N.S. Aybat and G. Iyengar. A first-order smoothed penalty method for compressed sensing. SIAM Journal on Optimization, 21(1):287–313, 2011.

  • G. Iyengar, D.J. Phillips, and C. Stein. Approximating semidefinite packing programs. SIAM Journal on Optimization, 21(1):231–268, 2011.

  • W. Kets, G. Iyengar, R. Sethi, and S. Bowles. Inequality and network structure. Games and Economic Behavior, 73(1):215–226, 2011 [SSRN].

  • G. Iyengar. Robust Portfolio Optimization. Encyclopedia of Quantitative Finance, 2010.

  • G. Iyengar and A.K.C. Ma. A behavioral finance-based tick-by-tick model for price and volume. Journal of Computational Finance, 14(1):57, 2010.

  • G. Iyengar and A.K.C. Ma. Cash flow matching: a risk management approach. North American Actuarial Journal, 13(3):370–378, 2009.

  • E. Erdoğan, D. Goldfarb, and G. Iyengar. Robust active portfolio management. Computational Finance, 11(4):71–98, 2008.

  • A. Kumar and G. Iyengar. Optimal procurement mechanisms for divisible goods with capacitated suppliers. Review of Economic Design, 12(2):129, 2008.

  • E. Erdoğan and G. Iyengar. On two-stage convex chance constrained problems. Mathematical Methods of Operations Research, 65(1):115–140, 2007.

  • D. Bienstock and G. Iyengar. Approximating fractional packings and coverings in O(1/ε) iterations*. SIAM Journal on Computing, 35(4):825–854, 2006.

  • E. Erdoğan and G. Iyengar. Ambiguous chance constrained problems and robust optimization. Mathematical Programming, 107(1-2):37–61, 2006.

  • E. Erdoğan and G. Iyengar. An active set method for single-cone second-order cone programs. SIAM Journal on Optimization, 17(2):459–484, 2006.

  • M.T. Çezik and G. Iyengar. Cuts for mixed 0-1 conic programs. Mathematical Programming Series A, 104:179–200, 2005.

  • G. Iyengar. Robust dynamic programming. Mathematics of Operations Research, 30(2):257–280, 2005.

  • G. Iyengar. Universal investment in markets with transaction costs. Mathematical Finance, 15(2):359–371, 2005.

  • G. Iyengar and W. Kang. Inverse conic programming with applications. Operations Research Letters, 33(3):319–330, 2005.

  • G. Iyengar and K. Sigman. Exponential penalty function control of loss networks. Annals of Applied Probability, 14(4):1698–1740, 2004 [arXiv].

  • D. Goldfarb and G. Iyengar. Robust convex quadratically constrained programs. Mathematical Programming, 97(3):495–515, 2003.

  • D. Goldfarb and G. Iyengar. Robust portfolio selection problems. Mathematics of Operations Research, 28(1):1–38, 2003.

  • G. Iyengar and T.M. Cover. Growth optimal investment in horse race markets with costs. IEEE Transactions on Information Theory, 46(7):2675–2683, 2000.

  • N.R. Garud and V. Rajaraman. Nondeterministic decision tables in process control. Sadhana. Indian Acad. Sc., 21(3):381-393, 1996.

Conference Papers

  • J. Černý, G. Iyengar, and C. Kroer. Contested Route Planning. Game Theory and AI for Security: 16th International Conference, GameSec 2025, Athens, Greece, October 13–15, 2025, Proceedings, Part II, pp. 103–123, 2025 [arXiv].

  • W. Kim, G. Iyengar, and Z. Zeevi. Learning the Pareto Front Using Bootstrapped Observation Samples. 2025. To appear in AISTATS 2025. [arXiv].

  • M. Sridharan and G. Iyengar. β-th order Acyclicity Derivatives for DAG Learning. 2025. To appear in AISTATS 2025..

  • W. Kim, S. Park, G. Iyengar, A. Zeevi, and M.H. Oh. Linear Bandits with Partially Observable Features. 2025. To appear in ICML 2025. [arXiv].

  • W. Kim, G. Iyengar, and Z. Zeevi. A Doubly Robust Approach to Sparse Reinforcement Learning. AISTATS, pp. 2305–2313, 2024 [arXiv].

  • J. Černý, C.K. Ling, G. Kroer, and G. Iyengar. Layered Graph Security Games. 2024. IJCAI 2024. [arXiv].

  • G. Iyengar, H. Lam, and T. Wang. Hedging against Complexity: Distributionally Robust Optimization with Parametric Approximation. AISTATS, pp. 9976–10011, 2023 [arXiv].

  • W. Kim, G. Iyengar, and A. Zeevi. Improved Algorithms for Multi-period Multi-class Packing Problems with Bandit Feedback. ICML, pp. 16458-16501, 2023 [arXiv].

  • M. Shridharan and G. Iyengar. Causal bounds in quasi-Markovian graphs. ICML, pp. 31675–31692, 2023.

  • M.O. Oh, G. Iyengar, and A. Zeevi. Sparsity-agnostic lasso bandit. ICML, pp. 8271–8280, 2021 [arXiv].

  • H. Cooper, G. Iyengar, and C.Y. Lin. Smartgraph: An Artificially Intelligent Graph Database. 7th International Conference of Advanced Computer Science and Information Technology (ACSIT 2019), 2019.

  • H.J. Cooper, G. Iyengar, and C.Y. Lin. Deep Influence Diagrams: An Interpretable and Robust Decision Support System. International Conference on Business Information Systems, pp. 450–462, 2019.

  • H.J. Cooper, G. Iyengar, and C.Y. Lin. Personalized Product Recommendation for Interactive Media. International Conference on Intelligent Human Systems Integration, pp. 510–516, 2019.

  • M.H. Oh and G. Iyengar. Sequential anomaly detection using inverse reinforcement learning. KDD 2019, pp. 1480–1490 [arXiv].

  • M.H. Oh and G. Iyengar. Thompson sampling for multinomial logit contextual bandits. NeurIPS, 32, 2019.

  • H.J. Cooper, G. Iyengar, and C.Y. Lin. Interpretable robust decision making. Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems, pp. 1912–1914, 2018.

  • M. Haas-Heger, C. Papadimitriou, M. Yannakakis, G. Iyengar, and M. Ciocarlie. Passive static equilibrium with frictional contacts and application to grasp stability analysis. RSS 2018 [arXiv].

  • D. Goldfarb, G. Iyengar, and C. Zhou. Linear Convergence of Stochastic Frank Wolfe Variants. AISTATS, pp. 1066–1074, 2017 [arXiv].

  • M. Haas-Heger, G. Iyengar, and M. Ciocarlie. On the Distinction between Active and Passive Reaction in Grasp Stability Analysis. Workshop on the Algorithmic Foundation of Robotics (WAFR), 2016.

  • N.S. Aybat, Z. Wang, and G. Iyengar. An asynchronous distributed proximal gradient method for composite convex optimization. ICML, pp. 2454–2462, 2015.

  • M.H. Oh, S. Keshri, and G. Iyengar. Graphical Model for Basketball Match Simulation. MIT Sloan Sports Analytics Conference, 2015.

  • V. Goyal, G. Iyengar, Q. Schwarz, and S. Wang. Optimal price rebates for demand response under power flow constraints. IEEE SmartGridComm, pp. 626–631, 2014.

  • V. Goyal, G. Iyengar, and Z. Qiu. Near-optimal execution policies for demand-response contracts in electricity markets. CDC, pp. 3697–3702, 2013.

  • G. Iyengar, D.J. Phillips, and C. Stein. Fast First-Order Algorithms for Packing-Covering Semidefinite Programs. Modeling and Optimization: Theory and Applications, 2012.

  • R.A. Carrasco, G. Iyengar, and C. Stein. Energy aware scheduling: minimizing total energy cost and completion time. MAPSP 2011.

  • G. Iyengar, D.J. Phillips, and C. Stein. Feasible and accurate algorithms for covering semidefinite programs. Scandinavian Workshop on Algorithm Theory, pp. 150–162, 2010.

  • A. Kumar and G. Iyengar. An equilibrium model for matching impatient demand and patient supply over time. Proceedings of the 8th ACM Conference on Electronic Commerce, pp. 59–65, 2007.

  • A. Kumar and G. Iyengar. Characterizing optimal keyword auctions. Second Workshop on Sponsored Search Auctions, 2006 [arXiv].

  • G. Iyengar, D.J. Phillips, and C. Stein. Approximation algorithms for semidefinite packing problems with applications to maxcut and graph coloring. IPCO, pp. 152–166, 2005.

  • D. Bienstock and G. Iyengar. Solving fractional packing problems in O(1/ε) iterations*. STOC 2004, pp. 146–155.

  • M.T. Çezik and G. Iyengar. Cutting planes for mixed 0-1 semidefinite programs. IPCO, pp. 251–263, 2001.

  • G. Iyengar and T.M. Cover. Growth optimal policies with transaction costs. IEEE ISIT, pp. 173, 1998.

  • D. Pal, G. Iyengar, and J.M. Cioffi. A new method of channel shortening with applications to discrete multi-tone (DMT) systems. ICC 1998, pp. 763–768.

  • G. Iyengar. Voice channel. Asilomar Conference on Signals, Systems and Computers, pp. 1354–1358, 1997.