Professor Deshmukh teaches courses in analytical decision modeling with Excel, business analytics, and operations management in MBA and EMBA programs. At the doctoral level, he has taught courses in stochastic processes and optimal statistical decisions.

Professor Deshmukh's research interests involve probabilistic and stochastic optimization models of decisions involving time and uncertainty, with applications in management science and economics. His research papers have appeared in a variety of scholarly journals such as Management Science, Operations Research, Journal of Applied Probability, Journal of Economic Theory, Econometrica, Review of Economic Studies, and Journal of Finance. He is a member of the Institute for Operations Research and Management Sciences (INFORMS).

Professor Deshmukh received his bachelor's degree in mechanical engineering from Pune University in India, a masters in industrial engineering from Purdue University, and a Ph. D. in Business Administration from the University of California at Berkeley.

Applied probability and stochastic optimization models of decisions involving time and uncertainty, with applications in management science and economics

• PhD, 1971, Business Administration, University of California, Berkeley
• MS, 1966, Industrial Engineering, Purdue University
• BE, 1964, Mechanical Engineering, Pune University, India

• Charles E. Morrison Professor of Decision Sciences, Kellogg School of Management, Northwestern University, 2001-present
• Co-Director, MMM Program, Northwestern University, 2006-2011
• Professor of Decision Sciences, Kellogg School of Management, Northwestern University, 1980-2001
• Assistant and Associate Professor of Decision Sciences, Kellogg School of Management, Northwestern University, 1971-1980

• 2014 Faculty of the Year, MPD Program, 2013-2014
• Sidney J. Levy Teaching Award, Kellogg School of Management, 2001-2002
• Executive MBA Program Outstanding Teaching Awards, Kellogg School of Management, 2002

Analytical decision modeling on spreadsheets, decision making under uncertainty

Decision Modeling and Optimization in Excel (OPNSX-450-0)
Analytical Decision Modeling focuses on structuring, analyzing and solving decision-problems spreadsheets. Problems involving optimal resource allocation and risk analysis are studied through applications in operations, finance and marketing. Some decision analysis, data analysis and forecasting is also covered. The course assumes working knowledge of Microsoft Excel.

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 (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.