Chaithanya Bandi
Chaithanya Bandi

Assistant Professor of Managerial Economics & Decision Sciences

Print Overview

Professor Chaithanya Bandi  joined the department of Managerial Economics and Decision Sciences at the Kellogg School of Management in 2013. He received a Ph.D in Operations Research from MIT in 2013, and a Bachelors of Technology in Computer Science and Engineering from the Indian Institute of Technology Chennai, India in 2008. He has worked in technology and Financial services companies such as Yahoo, Bell Labs, Lehman Brothers, and Investment Technology Group.

Professor Bandi  is broadly interested in the problems of decision making under uncertainty with applications to operations management. He has focused on developing optimization based models, in particular Robust Optimization models, to formulate and solve the key problems in many of these applications. He has worked on the problems of modeling and analysis of large-scale queueing systems, mechanism design problems, optimal portfolio construction and hedging etc. He is a recipient of the Operations Research Center Best Paper Award in 2013, a finalist in the INFORMS Nicholson Student Paper Competition in 2013, and Best Presentation in the Financial Services Section at INFORMS 2010.

Print Vita
Ph.D., 2013, Operations Research, Sloan School of Management, Massachusetts Institute of Technology
B. Tech, 2008, Computer Science and Engineering, Department of Computer Science and Engineering, Indian Institute of Technology - Chennai (Madras)

Academic Positions
Teaching Faculty, Analytical Decision Modeling, Kellogg School of Management, Northwestern University, 2013-present
Teaching Assistant, Sloan School of Management, Massachusetts Institute of Technology, 2008-present

Other Professional Experience
Research Intern, Investment Technology Group, 2011-2011
Intern, Yahoo!, 2009-2009
Intern, Lehman Brothers, 2007-2007

Grants and Awards
Presidential Fellowship to pursue doctoral studies, MIT
Best Presentation Award in Financial Services Section, INFORMS Annual Meeting

Print Research
Research Interests
Robust Optimization, Applied Probability, and Optimization methods with applications to Control and Analysis of large scale multi-class queueing networks, Mechanism Design, and Finance-OM interface.

Bandi, Chaithanya and Dimitris Bertsimas. Forthcoming. Optimal Design for Multi-Item Auctions: A Robust Optimization Approach. Mathematics of Operations Research.
Bandi, Chaithanya and Dimitris Bertsimas. 2014. Robust Option Pricing. European Journal of Operational Research. 239(3): 842-853.
Bandi, Chaithanya and Dimitris Bertsimas. 2012. Tractable stochastic analysis in high dimensions via robust optimization. Mathematical Programming. 134(1): 23-70.
Working Papers
Bandi, Chaithanya and Dimitris Bertsimas. Optimal Spending Patterns for a foundation, endowment or an individual - A Multi-Period Robust Optimization Approach.
Bandi, Chaithanya and Rajarshi Ghosh. Robust All-Pay Auctions with Applications to Crowdsourcing tournaments.
Bandi, Chaithanya and Dimitris Bertsimas. Optimal Variable Length Coding via Robust Optimization.
Bandi, Chaithanya and Dimitris Bertsimas. Network Information Theory via Robust Optimization.
Bandi, Chaithanya, Dimitris Bertsimas and Nataly Youssef. Robust Transient Queueing Theory.
Bandi, Chaithanya, Dimitris Bertsimas and Nataly Youssef. Robust Queueing Theory.
Bandi, Chaithanya, Dinesh Garg, Sachin Garg and KrishnaPalSingh Rathore. 2011. "Dynamic Pricing Models for Online Advertising." United States Patent US 2011/0166927 A1, filed 6/1/2011.

Print Teaching
Full-Time / Part-Time MBA
Analytical Decision Modeling (OPNS-450-0)

This course counts toward the following majors: Decision Sciences, Managerial Analytics, Operations.

This course focuses on structuring, analyzing and solving managerial decision problems on Excel spreadsheets. We address problems of resource allocation (how to use available resources optimally), risk analysis (how to simulate the effects of uncertainty in problem parameters), decision analysis (how to analyze sequential decisions involving uncertainty), data analysis (how to synthesize the available data into useful information) and forecasting (how to extrapolate past observations into the future). In each area, we pose specific problems from operations, finance and marketing, structure them on Excel spreadsheets, and analyze and solve them using the available Excel commands, tools and add-ins. The course involves a hands-on, in-class learning experience in modeling and analyzing a variety of business decision problems on a common spreadsheet platform. It should, therefore, enhance one's problem-solving capabilities as well as spreadsheet skills. A good working knowledge of Microsoft Excel is required. Prerequisites: OPNS-430 and FINC-430/FINC-440. May be taken concurrently.