Chaithanya Bandi
Chaithanya Bandi

Associate Professor of Operations

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 IIT Madras in 2008. He has worked in technology and Financial services companies such as Yahoo, Bell Labs, Lehman Brothers, and Investment Technology Group.

Chaithanya is broadly interested in the problems of decision making under uncertainty, incomplete information and risk with applications to operations management. In particular, I have focussed on developing Robust Optimization based models to formulate key problems in applications such as queueing control, risk optimization, mechanism design, and online algorithms; with applications ranging from e-commerce, healthcare, crowdsourcing, data-centers, and cloud-computing.

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

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

Honors and Awards
Google Research Award
ORC Best Paper Award
Finalist George Nicholon Best Paper
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, Phebe Vayanos and Nikolaos Trichakis. Forthcoming. Robust Multiclass Queuing Theory for Wait Time Estimation in Resource Allocation Systems. Management Science.
Bandi, Chaithanya and Dimitris Bertsimas. 2014. 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.
Bandi, Chaithanya, Dimitris Bertsimas and Nataly Youssef. 2017. Robust transient analysis of multi-server queueing systems and feed-forward networks. Queueing Systems.
Bandi, Chaithanya, Dimitris Bertsimas and Nataly Youssef. 2015. Robust Queueing Theory. Operations Research.
Working Papers
Bandi, Chaithanya. 2018. Simulation Optimization via Parametric Robust Optimization.
Bandi, Chaithanya. 2018. Design of Patient Flows via Robust Analysis of Fork-join Queues.
Bandi, Chaithanya. 2018. Pricing The Service Level Guarantees in Cloud computing.
Bandi, Chaithanya and Omar El Housni. 2018. Dynamic Resource Provisioning in Data Centers via Robust Queueing Theory.
Bandi, Chaithanya. 2018. Designing Optimal Priority Policies in Multi Class Queues via Robust Queueing Theory.
Bandi, Chaithanya. 2017. Machine Learning Based Robust Optimization Models for Limit Order Books to Predict Price Movements.
Bandi, Chaithanya and Eojin Han. 2017. Sustainable Inventory with Robust Periodic-Affine Policies.
Bandi, ChaithanyaAntonio Moreno-Garcia and Richard Xu. 2017. The Hidden Costs of Dynamic Pricing: Empirical Evidence from Online Retailing in Emerging Markets.
Bandi, Chaithanya and Ermin Wei. 2016. Robust Price of Anarchy in Supply function Equilibria.
Bandi, Chaithanya and Benjamin Grant. 2017. Optimal Tournament Design: Case study of Fantasy Sports Tournaments.
Bandi, ChaithanyaSunil Chopra and Pei-Ju Wu. 2017. Enhancing the Economic Impact of Environmental Performance.
Bandi, Chaithanya and Diwakar Gupta. 2017. Operating-Room Staffing and Online Scheduling.
Bandi, Chaithanya and Paat Rusmevichientong. 2017. Robust Optimal Allocation under uncertain Risk Preferences.
Bandi, Chaithanya and Dimitris Bertsimas. 2014. Optimal Spending Patterns for a foundation, endowment or an individual - A Multi-Period Robust Optimization Approach.
Bandi, Chaithanya and Rajarshi Ghosh. 2017. Robust All-Pay Auctions with Applications to Crowdsourcing tournaments.
Bandi, Chaithanya and Dimitris Bertsimas. 2015. Optimal Variable Length Coding via Robust Optimization.
Bandi, Chaithanya and Dimitris Bertsimas. 2015. Network Information Theory via Robust Optimization.
Bandi, Chaithanya, Dimitris Bertsimas, Erik Brynjolfsson, Shachar Reichman and John Silberholz. 2014. Dashboard for Academia The Analytics of Academic Impact.
Bandi, Chaithanya, Dinesh Garg, Sachin Garg and KrishnaPalSingh Rathore. 2017. Dynamic CPM Pricing Models for Display Advertising.
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 / Evening & Weekend MBA
Analytical Decision Modeling (OPNS-450-0)
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.

Applied Advanced Analytics (OPNS-940-0)
In this course we will develop a logical, analytical, practical approach to problem solving. In particular, we will model, analyze, and solve problems in operations management that involve resource allocation and risk analysis. We will apply optimization, simulation, and decision theory methodologies to modeling and analysis on the Excel platform. We will also perform some data analysis and time series analysis for estimation and forecasting model parameters.

Analytical Decision Modeling (OPNSM-450-0)

Queueing Networks: Performance Analysis (OPNS-522-0)
The course is to introduce the basic methods that are often used for analyzing performance in queueing network models. The students will learn how to characterize various queueing performance measures and apply to managerial decision making. Students should have familiarity with Markov process.