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
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.
During my Ph.D at MIT, I was exposed to the field of
Operations Research and have been actively working with Professor Bertsimas and other faculty at MIT's Operations Research Center and Sloan School of Management since 2010.
Logistics and supply chain management: flexibility in manufacturing and inventory planning.
Revenue management and business analytics.
Dynamic optimization in uncertainty.
Machine learning: data mining for predictive modeling.
- 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. Submitted to 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.
- 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. Machine learning for law enforcement.
Selected Teaching Experience
- 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