I am currently a lecturer and a postdoctoral associate at the Operations Research and Statistics Group at Sloan School of Management. This semester I am teaching the course Statistical thinking and data analysis at the Sloan School of Management. My postdoctoral supervisor is Dimitris Bertsimas.
One recurrent theme of my research is to design and understand operations strategies for managing uncertainties. Being excited about decision-making problems in complex operational environments, I spent the past three years as a postdoctoral associate in operations research at MIT.
Logistics and supply chain management: flexibility in manufacturing and inventory planning. Risk management.
Revenue management and business analytics.
Dynamic and data-driven optimization under uncertainty and risk.
Machine learning: data mining for predictive modeling.
(More information here.)
- On the Performance of Affine Policies for Two-Stage Adaptive Optimization: a Geometric Perspective, with D. Bertsimas, Mathematical Programming, Series A, 2014, to appear. Robust optimization for inventory planning
- Analyzing Process Flexibility: A Distribution Free Approach with Conditional Expectations, with D. Simchi-Levi and Y. Wei. Under revision for Operations Research, 2014. Flexibility in manufacturing
- Combining Metamodel Technique and Bayesian Selection Procedures to Drive Computationally efficient Simulation-based Optimization Algorithms, with C. Osorio. Winter Simulation Conference, 2012. Simulation for traffic management, we worked with traffic data of the city of Lausanne
- Optimal Flexibility Designs: Adaptive Optimization Approach, with D. Bertsimas. Working paper, 2014.
Flexibility in manufacturing
- Pareto Efficiency in Affine Adaptive Optimization, with D. Bertsimas. Working paper, 2014. Dynamic robust optimization
- Understanding Process Flexibility in Supply Chain Networks with Disruption, with S. Amin. Working paper, 2014. Flexibility in manufacturing under risk of disruption
- Detecting Crime Series with a Mathematical Programming Approach to Clustering, with C. Rudin and Cambridge Police Department. Working paper, 2013. Crime data mining, we worked with dataset of housebreaks in cambridge area
Selected Teaching Experience
(More information here.)
- Instructor for Statistical thinking and data analysis. Fall 2014, MIT.
Textbook: Data Mining for Business Intelligence, 2nd ed.
In this course, we teach data-driven thinking, problem solving, and decision making. We teach analytics methods using the statistical software R.
- Guest lecturer for Reliability on supply chain networks and optimization methods for operations management. Fall 2013, MIT. (For MBA and graduate students)
Advising eight undergraduate students at MIT, 2007 – 2010. (I won Roger family prizes at MIT for the best mentorship)
Dr. Hoda Bidkhori
MIT Sloan School of Management
Cambridge, MA 02139