Garud N. Iyengar
Senior Vice Dean of Research and Academic Programs
535B S.W. Mudd
Garud Iyengar’s research is focused on understanding uncertain systems and exploiting available information using data-driven control and optimization algorithms. He and his students have explored applications in many diverse fields, such as machine learning, systemic risk, asset management, operations management, sports analytics, and biology.
Research Interests
Large scale optimization, Information theory, Financial Engineering, Operations ManagementIyengar’s research group is currently working on thermodynamics of sensing and memory in cells, an automatic defensive assignment and event detection in NBA games, a deep neural-network-based framework for interpretable robust decision making, attribution schemes for allocating payment in a multi-channel advertising, systemic risk associated with extreme weather, and an NLP-based model for predicting stock performance using news reports.
Iyengar received a B Tech in electrical engineering from the Indian Institute of Technology in 1993 and a PhD in electrical engineering from Stanford University in 1998. He is a member of Columbia’s Data Science Institute.
Professional Experience
- Chair, industrial engineering and operations research, Columbia University, 2013–2019
- Professor, IEOR Department, Columbia University, 2010–
- Associate Professor, IEOR Department, Columbia University, 2006-10
- Assistant Professor, IEOR Department, Columbia University, 1998-2006
Professional Affiliations
- Institute for Operations Research and Management Sciences (INFORMS)
- Institute for Electrical and Electronics Engineers (IEEE)
Honors & Awards
- CAREER Award, National Science Foundation, 2000
- President’s Gold Medal, Indian Institute of Technology, Kanpur, 1993
Selected Publications
- 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.
- M. Haugh, G. Iyengar, C. Wang. Tax-Aware Dynamic Asset Allocation. Operations Research 64(4):849-866. 2016.
- M. Oh, S. Keshri, G. Iyengar. Graphical Model for Baskeball Match Simulation. Proceedings of the 9th Annual MIT Sloan Sports Analytics Conference. 2015.
- G. Iyengar and M. Rao. A cellular solution to an information-processing problem. PNAS. 111(34): 12402–12407. 2014.
- C. Chen, G. Iyengar, 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 J. Optim., 22(2), 429–459. 2012.
- Kumar and G. Iyengar. Optimal procurement mechanisms for divisible goods with capacitated suppliers. Rev. Econ. Design 12:129–154. 2008.
- D. Bienstock and G. Iyengar. Approximating fractional packing and covering in O(1/epsilon) iterations. SIAM J. Comput. 35(4), 825–854. 2006.
- E. Erdogan and G. Iyengar. Ambiguous chance constrained problems and robust optimization. Math. Program., Ser. B 107, 37–61. 2006.
- G. Iyengar. Robust Dynamic Programming. Math. Oper. Res. 30(2):257-280. 2005.
- D. Goldfarb and G. Iyengar. Robust Portfolio Selection Problems. Math. Oper. Res. 28(1):1-38. 2003.