Chaithanya Bandi
Chaithanya Bandi

MANAGERIAL ECONOMICS & DECISION SCIENCES; OPERATIONS
Donald P. Jacobs Scholar
Assistant Professor of Managerial Economics & Decision Sciences

Print Overview

Chaithanya's research is focused on problems of decision making under uncertainty in the intersection of finance and operations. His work deals with developing tractable models and and associated algorithms. He received his BTech in Computer Science from the Indian Institute of Technology, Chennai in 2008 and his Ph.D. in Operations Research from the Operations Research Center at MIT in 2013.

Print Vita
Education
Ph.D., In progress, 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 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

Conference Presentations
ISMP, TU Berlin, Germany, Optimal Design for Multi-Item Auctions: A Robust Optimization Approach, 1/01/2012
MSOM conference, New York, USA, Optimal Design for Multi-Item Auctions: A Robust Optimization Approach, 1/01/2012
Operations Management Seminar, MIT Sloan School of Management, Robust Queueing Theory, 1/01/2012
Optimization Day, HEC-Montreal, Montreal, Canada, Robust Queueing Theory, 1/01/2011
Optimization Day, HEC-Montreal, Montreal, Canada, Robust Option Pricing - An ϵ-arbitrage approach, 1/01/2011
INFORMS Annual Meeting, Austin, Texas, USA, Robust Queueing Theory, 1/01/2010
Robust Option Pricing - An ϵ-arbitrage approach, INFORMS Annual Meeting, Austin, Texas, USA, 1/01/2010
INFORMS Annual Meeting, San Diego, CA, USA, Optimal spending patterns for an endowment, 1/01/2009

 
Print Research
Articles
Bandi, Chaithanya, Dimitris Bertsimas and Si Chen. 2010. Robust Option Pricing - An ϵ-arbitrage approach. Operations Research.
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. 2012. Robust Queueing Theory. Operations Research.
Bandi, Chaithanya and Dimitris Bertsimas. Optimal Design for Multi-Item Auctions: A Robust Optimization Approach. Mathematics of Operations Research.
Bandi, Chaithanya and Dimitris Bertsimas. Network Information Theory via Robust Optimization. IEEE Transactions on Information Theory.
Bandi, Chaithanya, Dinesh Garg, Sachin Garg and Krishna Pal Singh Rathore. Dynamic Pricing Models for Online Advertising.
Working Papers
Bandi, Chaithanya and Dimitris Bertsimas. Optimal Variable Length Coding via Robust Optimization.
Bandi, Chaithanya, Dimitris Bertsimas and Nataly Youssef. Robust Transient Queueing Theory.
Bandi, Chaithanya and Dimitris Bertsimas. Optimal Spending Patterns for a foundation, endowment or an individual - A Multi-Period Robust Optimization Approach.
Bandi, Chaithanya, Dinesh Garg, Sachin Garg and Krishna Pal Singh Rathore. Dynamic CPM Pricing Models for Display Advertising.
Bandi, Chaithanya, Dimitris Bertsimas, Erik Brynjolfsson, Shachar Reichman and John Silberholz. Dashboard for Academia The Analytics of Academic Impact.
Patents
Bandi, Chaithanya, Sachin Garg and Krishna Pal Singh Rathore. 2010. "Dynamic Pricing Models for Online Advertising." United States Patent Document Number 20110166927, filed 1/7/2010, and published 1/7/2010.

 
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.