Michael Fu Directory Page

• INFORMS Kimball Medal, 2022.
• INFORMS Saul Gass Expository Writing Award, 2021.
• Fu Wins Saul Gass Expository Writing Award
• US010417699B2 patent awarded Sep.17, 2019.
• INFORMS Simulation Society Distinguished Service Award, December 2018.
• AlphaGo article in October 2016 issue of OR/MS Today.
• Editor, Handbook of Simulation Optimization, Springer, 2015.
• Co-Editor (with Saul I. Gass), Encyclopedia of Operations Research and Management Science, 3rd edition, Springer, 2013.
• National Science Foundation Operations Research Program Director: Sep.13, 2010 - Aug.24, 2012;
• OR/MS Today articles about the Operations Research Program: part 1, part 2.
• Distinguished Scholar-Teacher, 2004-2005 , University of Maryland.
• Fellow of INFORMS and IEEE.
• Guest Co-Editor (with Barry L. Nelson), Special Issue on Simulation Optimization, ACM Transactions on Modeling and Computer Simulation, 2003.
• 2002 Institute for Systems Research Outstanding Faculty Award.
• 1999 IIE Operations Research Division Award.
• 1998 INFORMS Simulation Society Outstanding Simulation Publication Award for the book,
• Conditional Monte Carlo: Gradient Estimation and Optimization Applications(co-author Jian-Qiang Hu).
• 1998 IIE Transactions on Operations Engineering Best Paper Award, for the paper,
• Optimization of Discrete Event Systems via Simultaneous Perturbation Stochastic Approximation (co-author Stacy Hill).

Recent Invited Talks

• Plenary/Keynote, Industrial Engineering/Management Science Workshop on Smart Simulation, Peking University, June 15, 2018
• Johns Hopkins University Applied Physics Laboratory, Intelligent Systems Center, June 7, 2018
• Columbia University, November 2, 2017
• MIT, September 20, 2017
• Seoul National University, June 23, 2017
• Korea Advanced Institute of Science and Technology (KAIST), Daejeon, South Korea, June 20 & 21, 2017
• Zhejiang University, Hangzhou, China, June 2 & 3, 2016.
• Nankai University, Tianjin, China, May 24, 2016
• Instituto de Empresa (IE), Madrid, Spain, May 6, 2016,
• Cornell, April 26, 2016
• INSEAD, March 14, 2016
• Tsinghua University, July 7 & 10, 2015.
• University of Michigan, March 27, 2015
• Pennsylvania State University, March 21, 2014
• University of Massachusetts, Amherst, October 18, 2013
• WINFORMS, Washington, DC, August 20, 2013
• Zhejiang University, Hangzhou, China, June 7, 2013
• Arizona State University, April 1, 2013
• Politecnico de Milano, March 18, 2013
• University of Washington, March 8, 2013
• Stony Brook University, November 16, 2012.
• Rutgers Business School, September 10, 2012.
• Naval Postgraduate School, May 3, 2012.
• University of Washington, March 1, 2012.
• Arizona State University, December 9, 2011.
• Lehigh University, November 29, 2011.
• Macquarie University, Sydney, Australia, July 5, 2011.
• University of California at Berkeley, March 28, 2011.
• University of Illinois, March 14, 2011.
• University of Southampton, England, July 16, 2010.
• Peking University, June 30, 2010.
• United States Military Academy, West Point, NY, April 30, 2009.
• University of Wisconsin, May 8, 2009.
• Duke University Fuqua School of Business, March 21, 2008.
• University of Minnesota, April 23, 2008.

Birthday Symposium/Conference Celebrations

• Symposium in honor of Steve Marcus' 60th birthday (Apr.18, 2009).
• Conference in honor of Dilip Madan's 60th birthday (Sep.29-Oct.1, 2006).
• Symposium in honor of Saul Gass' 80th birthday (Feb.25, 2006).
• Workshop in honor of Barry Nelson's 60th birthday (April 28-30, 2017).

Simulation modeling and analysis, production/inventory control, applied probability, and queueing theory; stochastic derivative estimation, simulation optimization, Markov decision processes; with application to supply chain management and financial engineering.

Current and Recent Research Projects

• Evolution of Global Illicit Kidney Trade Networks: Identification, Reconstruction and Disruption, research sponsored by the National Science Foundation, PI at Maryland (Project Director Naoru Koizumi, GMU; co-PIs Hadi El-Amine, GMU; Monica Gentili, U. Louisville), 2022-2026.
• Optimal Desensitization Protocol in Support of a Kidney Paired Donation (KPD) System, research sponsored by the National Science Foundation, PI at Maryland (Project Director Naoru Koizumi, GMU; co-PIs Chun-Hung Chen & Hadi El-Amine, GMU; Monica Gentili, U. Louisville), 2021-2025.
• An Optimization-based Approach to Breaking the Neural Code. research sponsored by the DARPA, co-PI (Project Director Steve Marcus, co-PIs B. Babadi, J. Simon), 2018-2019.
• Simulation Optimization: New Approaches to Gradient-based Search & Maximum Likelihood Estimation, sponsored by the Air Force Office of Scientific Research, Project Director (co-PI Steve Marcus), 2020-2023.
• New Approaches for Simulation-based Optimal Decision Making,
  research sponsored by the National Science Foundation,
  Project Director (co-PI Steve Marcus), 2015-2019.
• A New Approach to Nonconvex Risk-Sensitive Stochastic Optimization,
  research sponsored by the National Science Foundation,
  co-Principal Investigator (PI Steve Marcus), 2014-2017.
• Integrating Gradient and Adaptive Search in Simulation Optimization,
  research sponsored by the National Science Foundation,
  Project Director (co-PI Steve Marcus and co-PI Jiaqiao Hu, SUNY Stony Brook), 2009-2013.
• Particle Filtering for Stochastic Control and Global Optimization,
  research sponsored by the National Science Foundation,
  co-Principal Investigator (PI Steve Marcus, co-PI Enlu Zhou, University of Illinois), 2009-2012.
• Simulation-Based Methodologies for Global Optimization and Planning,
  sponsored by the Air Force Office of Scientific Research,
  co-Principal Investigator (PI Steve Marcus and co-PI Jiaqiao Hu, SUNY Stony Brook), 2010-2013.
• Dynamic Real-Time Order Promising and Fulfillment for Global Make-to-Order Supply Chains,
  sponsored by the National Science Foundation,
  co-Principal Investigator (PI Michael Ball), 2006-2010.
• Simulation-Based Approaches to Solving Markov Decision Process,
  research sponsored by the National Science Foundation,
  Project Director (co-PI Steve Marcus), 2000-2007.
• Mathematical and Computational Finance Research Interactions Team (joint with Dilip Madan).
• Preventive Maintenance Scheduling in Semiconductor Manufacturing Fabs,
  sponsored by the Semiconductor Research Corporation and InternationalSEMATECH,
  Project Director (with co-PI Steve Marcus and Emmanuel Fernandez, University of Cincinnati), 2001-2004.

Professional Activities

• General Co-Chair, 2020 INFORMS Annual Meeting
• INFORMS Board (Treasurer & Executive Committee), 2017-2018
• Program Chair, 2011 Winter Simulation Conference (December 11-14, Phoenix, AZ).
• Stochastic Models and Simulation Department Editor, Management Science, 2006-2008.
• Associate Editor, Mathematics of Operations Research, 2006-2008.
• Simulation Area Editor, Operations Research, 2000-2005 (Associate Editor, 1998-99).
• Associate Editor, Management Science, 1998-2005.
• Associate Editor, INFORMS Journal on Computing , 1993-2000.
• Associate Editor, IIE Transactions, 1994-2000.
• Editorial Board, Production and Operations Management, 1996-2003.
• Fellow of INFORMS (formerly ORSA, TIMS) and IEEE .
• Member of Program Committee, 2013 INFORMS Applied Probability Society Meeting .
• Member of Program Committee, 2011 INFORMS Computing Society Conference.
• Member of Organizing/Program Committee, 2008 MSOM Meeting.
• Member of Program Committee, 46th IEEE Conference on Decision and Control , 2007.
• Member of Organizing Committee, Mathematical Finance Conference in honor of Dilip Madan on his 60^th birthday , 2006.
• Chair of Organizing Committee, Operations Research Symposium in honor of Saul Gass on his 80^th birthday, 2006.
• Member of Program Committee, 2004 INFORMS Applied Probability Society Meeting .
• Member of Program Committee, 2000 INFORMS Computing Society Conference.
• Member of Program Committee, 1998 INFORMS Computer Science Technical Section Conference.
• Member of Program Committee, in charge of Contributed Papers, 1996 INFORMS Spring National Meeting .
• Member of Scientific Committee, 1995 International Conference on Emerging Technologies and Factory Automation.

Click here for pdf file listing publications, including conference proceedings, book chapters, etc.

Books

• Handbook of Simulation Optimization, editor, Springer, 2014.
• Encyclopedia of Operations Research and Management Science, 3rd edition, co-edited with Saul I. Gass, Springer, 2013.
• Conditional Monte Carlo: Gradient Estimation and Optimization Applications,
  joint with J. Q. Hu; Kluwer Academic Publishers (now part of Springer), 1997 (order from Amazon.com).
  Running list of errata. (Please e-mail any errors/typos you may catch. Thanks!)
• Perspectives in Operations Research: Papers in Honor of Saul Gass’ 80th Birthday, Springer, October 2006,
  co-edited with Frank Alt and Bruce Golden.
• Simulation-Based Methods for Markov Decision Processes
  (with Hyeong Soo Chang, Jiaqiao Hu, Steve Marcus), Springer, March 2007.
• Advances in Mathematical Finance (Festschrift for Dilip Madan’s 60th birthday), Birkhäuser, July 2007,
  co-edited with Robert Elliott, Bob Jarrow, and Ju-Yi Yen;
  associated Conference (Sep.29-Oct.1, 2006).

Selected journal articles, conference proceedings, and recent working Papers

Cumulative Prospect Theory (CPT)

• Stochastic Optimization in a Cumulative Prospect Theory Framework, IEEE Transactions on Automatic Control, conditionally accepted, 2017 (with C. Jie, P. L.A., S.I. Marcus, C. Szepesvari).
• Cumulative Prospect Theory Meets Reinforcement Learning: Prediction and Control, Proceedings of the 33rd International Conference on Machine Learning, 1406–1415, 2016 (with P. L.A., C. Jie, S.I. Marcus, C. Szepesvari).
• Weighted Bandits or: How Bandits Learn Distorted Values that are Not Expected, Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17), 1941–1947, 2017 (with A. Gopalan, P. L.A., S.I. Marcus).

Markov Decision Processes

• An Adaptive Sampling Algorithm for Solving Markov Decision Processes, Operations Research, Vol.53, No.1, 126-139, 2005 (with H.S. Chang, J. Hu, S.I. Marcus) 
  earlier version available as TR 2002-19.
• An Evolutionary Random Search Algorithm for Solving Markov Decision Processes, INFORMS Journal on Computing, Vol.19, No.2, 161-174, 2007 (with J. Hu, V. Ramezani, S.I. Marcus) 
  earlier version available as TR 2005-3.
• Evolutionary Policy Iteration for Solving Markov Decision Processes, IEEE Transactions on Automatic Control, Vol.50, No.11, 1804-1808, 2005 (with H.S. Chang, H.-G. Lee, S.I. Marcus) 
  earlier version available at TR 2002-31 (Note there is a minor technical error in one of the proofs in that version).
• Recursive Learning Automata Approach to Markov Decision Processes, IEEE Transactions on Automatic Control, Vol.52, No.7, 1249-55, 2007 (with H.S. Chang, J. Hu, S.I. Marcus). 
• A Two-Timescale Stochastic Approximation Algorithm for Weighted Cost-to-Go Markov Decision Processes, Proceedings of the 44th IEEE Conference on Decision and Control, 8022-8027, 2005 (with Y. He, S.I. Marcus). 
• An Asymptotically Efficient Algorithm for Finite Horizon Stochastic Dynamic Programming Problems, IEEE Transactions on Automatic Control, Vol.52, No.1, 89-94, 2007. 
  earlier version available as TR 2003-26.
• TR 2005-84: Convergence of Sample Path Optimal Policies for Stochastic Dynamic Programming.
• TR 2003-25: A Distributed Algorithm for Solving a Class of Multi-agent Markov Decision Problems.
• TR 99-56: Simulation-Based Algorithms for Average Cost Markov Decision Processes.

Randomized Global Optimization

• A Model Reference Adaptive Search Algorithm for Global Optimization, Operations Research, Vol.55, No.3, 549-568, 2007 (with J. Hu, S.I. Marcus). 
  earlier version available as TR 2005-81.
• A Model Reference Adaptive Search Algorithm for Stochastic Global Optimization, Communications in Information and Systems, Vol.8, No.3, 245–276, 2008 (with J. Hu, S.I. Marcus). 
• New Global Optimization Algorithms for Model-Based Clustering, Computational Statistics and Data Analysis, Vol.53, No.12, 3999-4017, 2009 (with J. Heath, W. Jank). 
• Global Convergence of Model Reference Adaptive Search for Gaussian Mixtures (with J. Heath, W. Jank). 
• Model-Based Randomized Methods for Global Optimization, Proceedings of the 17th International Symposium on Mathematical Theory of Networks and Systems, 355-363, 2006 (with J. Hu, S.I. Marcus). 

Gradient Estimation (note: some papers also cross-listed under particular application area)

• Stochastic Gradient Estimation, Chapter 5 of Handbook on Simulation Optimization, M.C. Fu, editor, Springer, 2015.
• Naval Research Logistics Cover Article, What You Should Know About Simulation and Derivatives, Vol.55, No.8, 723-736, 2008.
• A New Unbiased Stochastic Derivative Estimator for Discontinuous Sample Performances with Structural Parameters, Operations Research, forthcoming, 2017 (with Y. Peng, J.Q. Hu, B. Heidergott).
• A New Stochastic Derivative Estimator for Discontinuous Payoff Functions with Application to Financial Derivatives, Operations Research, Vol.60, No.2, 447–460, 2012 (with Y. Wang, S.I. Marcus).
• On Estimating Quantile Sensitivities via Infinitesimal Perturbation Analysis, Operations Research, Vol.63, No.2, 435–441, 2015 (with G. Jiang).
• Conditional Monte Carlo Estimation of Quantile Sensitivities, Management Science, Vol.55, No.12, 2019–2027, 2009 (with L.J. Hong, J.Q. Hu).
• Conditional Monte Carlo Gradient Estimation in Economic Design of Control Limits, Production and Operations Management, Vol. 18, No. 1, 60–77, 2009 (with S. Lele, T. Vossen).
• Stochastic Gradient Estimation, Chapter 19, in Handbook on Operations Research and Management Science: Simulation, S.G. Henderson and B.L. Nelson, editors, Elsevier, 575-616, 2006. earlier version available as TR 2005-93.
• Extensions and Generalizations of Smoothed Perturbation Analysis in a Generalized Semi-Markov Process Framework, IEEE Transactions on Automatic Control, Vol.37, No.10, 1483-1500, 1992 (with J.Q.Hu). PDF
• Sample Path Derivatives for (s,S) Inventory Systems, Operations Research, Vol.42, No.2, 351-364, 1994. 
• Sensitivity Analysis for Simulation of Stochastic Activity Networks, in Perspectives in Operations Research: Papers in Honor of Saul Gass' 80th Birthday (eds. Alt, Fu, Golden), Springer, 351-366, 2006.
• Simulation Optimization of Traffic Light Signal Timings via Perturbation Analysis, working paper (with W.C. Howell). 
• Online Traffic Light Control Through Gradient Estimation Using Stochastic Fluid Models, Proceedings of the IFAC 16th Triennial World Congress, 2005 (with C. Panayiotou, W.C. Howell). 
• Fluid Approximation and Perturbation Analysis of a Dynamic Priority Call Center, Proceedings of the 43rd IEEE Conference on Decision and Control, 2304-2309, 2004 (with M. Chen, J.Q. Hu). 
• Efficient Design and Sensitivity Analysis of Control Charts Using Monte Carlo Simulation, Management Science, Vol.45, No.3, 395-413, 1999 (with J.Q. Hu) earlier version available as TR 97-91.
• Conditional Monte Carlo Gradient Estimation in Economic Design of Control Charts, POM, under review. (with S. Lele, T. Vossen)
• Second Derivative Sample Path Estimators for the GI/G/m Queue, Management Science, Vol.39, No.3, 359-383, 1993 (with J.Q.Hu).
• Derivative Estimation for Buffer Capacity of Continuous Transfer Lines Subject to Operation-dependent Failures, Discrete Event Dynamic Systems, Vol.12, No.4, 447-469, 2002 (with X. Xie); earlier version available as TR 98-57.
• Efficient Sensitivity Analysis of Mortgage-Backed Securities (with J. Chen), unpublished manuscript, 2001. much abbreviated version available here (Hedging Beyond Duration and Convexity, Proceedings of the 2002 Winter Simulation Conference, 1593-1599).
• Sensitivity Analysis for Monte Carlo Simulation of Option Pricing, Probability in the Engineering and Information Sciences, Vol.9, No.3, 417-446, 1995 (with J.Q.Hu). (published version has some typos and errors).
• A Note on Perturbation Analysis Estimators for American-Style Options, Probability in Engineering and Informational Sciences, Vol.14, 385-392, 2000 (with R. Wu, G. Gürkan, A.Y. Demir).

Simulation Optimization, Stochastic Approximation

• An Overview of Stochastic Approximation, Chapter 6 of Handbook on Simulation Optimization, M.C. Fu, editor, Springer, 2015 (with M. Chau).
• History of Seeking Better Solutions, aka Simulation Optimization, Proceedings of the Winter Simulation Conference, forthcoming, 2017 (with S.G. Henderson).
• Augmented Regression With Direct Gradient Estimates, INFORMS Journal on Computing, Vol.26, No.3, 484–499, 2014 (with H. Qu).
• Gradient Extrapolated Stochastic Kriging,” ACM Transactions on Modeling and Computer Simulation, 24(4), 2014 (with H. Qu).
• Optimization for Simulation: Theory vs. Practice (Feature Article), INFORMS Journal on Computing, Vol.14, No.3, 192-215, 2002. 
• Optimization via Simulation: A Review, Annals of Operations Research, Vol. 53, 199-248, 1994.
• Two-Timescale Simultaneous Perturbation Stochastic Approximation Using Deterministic Perturbation Sequences, ACM Transactions on Modeling and Computer Simulation, 180-209, 2003 (with S. Bhatnagar, S.I. Marcus, I.J.Wang).
• Convergence of Simultaneous Perturbation Stochastic Approximation for Nondifferentiable Optimization, IEEE Transactions on Automatic Control, Vol.48, No.8, 1459-1463, 2003 (with Y. He, S.I. Marcus). 
• On the Convergence Rate of Ordinal Comparison of Random Variables, IEEE Transactions on Automatic Control, Vol.,46, No.12, 1950-1954, 2001 (with X. Jin).
• An Optimal Structured Feedback Policy for ABR Flow Control Using Two Timescale SPSA, IEEE/ACM Transactions on Networking, Vol.9, No.4, 479-491, 2001 (with S. Bhatnagar, S.I. Marcus, P.J.M. Fard); earlier version available as TR 99-86.
• Two Timescale Algorithms for Simulation Optimization of Hidden Markov Models, IIE Transactions, Vol.33, No.3, 245-258, 2001 (with S. Bhatnagar, S.I. Marcus, S. Bhatnagar); PDF earlier version available as TR 2000-13.
• Optimization of Discrete Event Systems via Simultaneous Perturbation Stochastic Approximation, IIE Transactions, Vol. 29, No.3, pp.233-243, 1997 (with S.D. Hill). 
• Convergence of a Stochastic Approximation Algorithm for the GI/G/1 Queue Using Infinitesimal Perturbation Analysis, Journal of Optimization Theory and Applications, Vol.65, No.1, 149-160, 1990. 

Simulation Efficiency

• Simulation Allocation for Determining the Best Design in the Presence of Correlated Sampling, INFORMS Journal on Computing, Vol.19, No.1, 101-111, 2007 (with J.Q. Hu, C.H. Chen, X. Xiong).
• Efficient Dynamic Simulation Allocation in Ordinal Optimization, IEEE Transactions on Automatic Control, Vol.51, No.12, 2005-2009, 2006 (with D. He, C.H. Chen). 
• Efficient Simulation Budget Allocation for Selecting an Optimal Subset, INFORMS Journal on Computing, Vol.20, No.4, 579–595, 2008 (with D. He, C.H. Chen, L.H. Lee). 
• Asymptotically Optimal Simulation Allocation under Dependent Sampling (with X. Xiong, S. Juneja). 
• Probabilistic Error Bounds for Simulation Quantile Estimation, Management Science, Vol.49, No.2, 230-246, 2003 (with X. Jin, X. Xiong); PDF earlier version finalist in INFORMS Nicholson Student Paper competition: A Large Deviations Analysis of Quantile Estimation with Application to Value at Risk, available as pdf at DRUM.

Financial Engineering/Computational Finance

• Variance-Gamma and Monte Carlo, in Advances in Mathematical Finance (eds. Fu, Jarrow, Yen, Elliott), Birkhäuser, 21-35, 2007. (tutorial article on Monte Carlo simulation for Variance-Gamma process, including bridge sampling and sensitivity estimation)
• Pricing American-Style Derivatives with European Call Options, Management Science, Vol.52, No.1, 95-110, 2006 (with S. Laprise, S.I. Marcus, A.E.B. Lim, H. Zhang); much abbreviated preliminary version available here (A New Approach to Pricing American-Style Derivatives, Proceedings of the 2001 Winter Simulation Conference, 329-337).
• Optimal Exercise Policies and Simulation-based Valuation for American-Asian Options, Operations Research, Vol.51, No.1, 52-66, 2003 (with R. Wu).
• Optimal Importance Sampling in Securities Pricing, Journal of Computational Finance, Vol.5, No.4, 27-50, 2002 (with Y. Su); (Note: published version has numerous typos.) much abbreviated preliminary version available here (Importance Sampling in Derivative Securities Pricing, Proceedings of the 2000 Winter Simulation Conference, 587-596).
• Pricing American Options: A Comparison of Monte Carlo Simulation Approaches, Journal of Computational Finance, Vol.4, No.3, 39-88, Spring 2001 (with S.B.Laprise, D.B. Madan, Y. Su, R. Wu). 
• Pricing Continuous Asian Options: A Comparison of Monte Carlo and Laplace Transform Inversion Methods, Journal of Computational Finance, Vol.2, No.2, 49-74, 1999 (with D.B. Madan, T. Wang). 
• Efficient Sensitivity Analysis of Mortgage-Backed Securities (with J. Chen), unpublished manuscript, 2001. much abbreviated version available here (Hedging Beyond Duration and Convexity, Proceedings of the 2002 Winter Simulation Conference, 1593-1599).
• Sensitivity Analysis for Monte Carlo Simulation of Option Pricing, Probability in the Engineering and Information Sciences, Vol.9, No.3, 417-446, 1995 (with J.Q.Hu).
• A Note on Perturbation Analysis Estimators for American-Style Options, Probability in Engineering and Informational Sciences, Vol.14, 385-392, 2000 (with R. Wu, G. Gürkan, A.Y. Demir). 

Semiconductor Manufacturing and Supply Chain Management

• Optimal Preventive Maintenance Scheduling in Semiconductor Manufacturing, IEEE Transactions on Semiconductor Manufacturing, Vol.17, No.3, 345-356, 2004 (with X. Yao, E. Fernández- Gaucherand, S.I. Marcus).
• Optimal Joint Preventive Maintenance and Production Policies, Naval Research Logistics, Vol.52, No.7, 668-681, 2005 (with X. Yao, X. Xie, S.I. Marcus). 
• TR 2000-49: Approximate Policy Iteration for Semiconductor Fab-Level Decision Making - a Case Study
• TR 2000-48: Simulation-Based Approach for Semiconductor Fab-Level Decision Making - Implementation Issues
• TR 2000-1: Comparing Gradient Estimation Methods Applied to Stochastic Manufacturing Systems

Queueing and Inventory

• Optimization of (s,S) Inventory Systems with Random Lead Times and a Service Level Constraint, Management Science, Vol.44, No.12, S243-S256, 1998 (with S. Bashyam).
• Queueing Theory in Manufacturing: A Review, Journal of Manufacturing Systems, Vol.18, No.3, 214-240, 1999 (with M.K. Govil). 
• Sample Path Derivatives for (s,S) Inventory Systems, Operations Research, Vol.42, No.2, 351-364, 1994. 
• Monotone Optimal Policies for a Transient Queueing Staffing Problem, Operations Research, No.2, 327-331, 2000 (with S.I. Marcus, I.J. Wang); earlier version available as TR 97-62.
• Minimizing Work-in-Process and Material Handling in the Facilities Layout Problem, IIE Transactions, Vol. 29, No.1, pp.29-36, 1997 (with B.K. Kaku); earlier version available as TR 95-41.
• Models for Multi-Echelon Repairable Item Inventory Systems with Limited Repair Capacity, European Journal of Operational Research, Vol. 97, No.3, pp.480-492, 1997 (with A. Diáz).
• Second Derivative Sample Path Estimators for the GI/G/m Queue, Management Science, Vol.39, No.3, 359-383, 1993 (with J.Q.Hu).
• TR 98-7: A Lower Bounding Result for the Optimal Policy in an Adaptive Staffing Problem.
• Multi-Echelon Models for Repairable Items: A Review (with A. Diaz). available as pdf at DRUM.

Note: other unpublished Technical Reports can be found at the ISR TR Web site.

Courses Taught

• HONR 229Q Making Decisions in an Uncertain World
• BMGT 231 Statistical Models for Business
• BMGT 332 Operations Research for Management Decisions
• BMGT 435 Introduction to Applied Probability Models
• BMGT 671 Supply Chain Logistics and Operations Management (MBA Core Course Coordinator 1999-2005)
• BMGT 734 Models for Operations Management
• BMGT 772 Logistics Management (Executive MBA)
• BMGT 798B Computational Finance
• BMGT 798Z Operations Research in Finance
• BMGT 830 Operations Research: Linear Programming
• BMGT 834 Operations Research: Probabilistic Models
• BMGT 835 Simulation of Discrete-Event Systems

PhD students current: Peng Wan, Yi Zhou, Xingyu Ren

PhD students graduated

1. Sridhar Bashyam, retired (last position at Frito Lay).
2. Angel Díaz, retired (last position on faculty at Instituto de Empresa, Madrid, Spain).
3. Jae-sin Yoo (co-advisor Arjang Assad).
4. Kefeng Xu (co-advisor Phil Evers), currently on faculty at University of Texas–San Antonio.
5. Tong Wang (co-advisor Dilip Madan), currently at the World Bank.
6. Yi Su (co-advisor Dilip Madan).
7. Rongwen Wu (co-advisor Dilip Madan), currently senior director at Capital One (previously Freddie Mac).
8. Xing Jin (co-advisor Dilip Madan), currently Professor, Tianjin University of Finance and Economics (previously faculty member at Warwick Business School and math department at National University of Singapore).
9. Scott Laprise, currently at Johns Hopkins Applied Physics Laboratory (previously at Apogee Research and BAE Systems).
10. Ying He (co-advisor Steve Marcus), currently at Fannie Mae (previously NIH, IMF).
11. Xiaodong Yao (co-advisor Steve Marcus), currently at SAS.
12. Jian Chen, currently at MSCI (previously at Fannie Mae, Freddie Mac).
13. Ahmad Ridley (co-advisor Bill Massey), currently at MitreTek.
14. Xiaoping Xiong, currently at Freddie Mac.
15. Sun-Hee Kim (co-advisor Dilip Madan).
16. Jiaqiao Hu (co-advisor Steve Marcus), currently on Applied Mathematics & Statistics faculty at SUNY Stony Brook.
17. William Howell, previously at BAE Systems.
18. Huiju Zhang, currently VP at Morgan Stanley (previously Fitch Ratings, Capital One).
19. Jeff Heath (co-advisor Wolfgang Jank), currently on faculty at Centre College.
20. Colonel Scott Nestler (co-advisor Dilip Madan), currently at Accenture (previously on faculty of U.S. Military Academy at West Point, Naval Postgraduate School, U.S. Army War College, Notre Dame Mendoza Business School).
21. Colonel Andrew Hall, currently on faculty at Marymount University (previously on faculty of U.S. Military Academy at West Point, and served on Pentagon Joint Staff).
22. Enlu Zhou (co-advisor Steve Marcus), currently on faculty at Georgia Tech (previously University of Illinois).
23. Matthew Reindorp (previously faculty member at Technical University of Eindhoven).
24. Lingyan Cao (co-advisor Dilip Madan), currently at Fannie Mae (previously IMF).
25. Yongqiang Wang (co-advisor Steve Marcus), currently at Amazon (previously at Campbell and Company).
26. Huashuai Qu (co-advisor Ilya Ryzhov), currently at Netflix (previously Google).
27. Marie Chau, currently at Johns Hopkins Applied Physics Laboratory (previously Assistant Professor in the Department of Statistical Sciences and Operations Research at Virginia Commonwealth University).
28. Cheng Jie, currently at Walmart Labs.
29. Guowei Sun, currently at Facebook.
30. Yunchuan Li, currently at Facebook.

Postdoctoral Fellows supervised (all jointly with Steve Marcus)

• Prashanth L.A., 2015-2017, currently on faculty at Indian Institute for Technology, Madras.
• Shalabh Bhatnatar, 1997-2000, currently on faculty at Indian Institute for Science, Bangalore.
• Andrew Lim, 2001, previously on faculty at University of California, Berkeley.
• Grazyna Badowski, 2001-2002, on faculty at University of Guam.
• Vijay Konda, 2002-2003.
• Vahid Ramezani, 2003-2005.
• Chang Su, 2004-2005.

MS students (w/thesis) graduated

1. Murali Narayanaswamy (MSSE, co-advisor Jeffrey Herrmann).
2. Praveen Mellacheruvu (MSSE, co-advisor Jeffrey Herrmann).
3. Vera Osidach (MSSE), 2003.
4. Mauricio Manterola (ECE), 2011.
5. Aurora Bristor (AMSC, co-advisor Sean Barnes), 2013.
6. Narryn Fisher (AMSC), 2014.
7. Jonathan Lin (MSSE), 2017.
8. Arturo Davila-Andino (MSSE), 2018.
9. Aditya Shinde (MSSE), 2018.

Visiting Scholars hosted

• Yijie Peng, 2012-2013, 2015-2016 (Fudan University), currently on faculty at Peking University.
• Guangxin Jiang, 2013-2014 (Tongji University), currently on faculty at Harbin Institute of Technology (previously on faculty at Shanghai University, postdoctoral fellow at City University of Hong Kong).
• Lei Lei, 2016-2017 (Fudan University).
• Jennifer Guozhen Li, 2017 (Nankai University), currently on faculty at Hunan University.
• Chunyue Song (Zhejiang University).

• Inspirational: The Last Lecture.
• Books online
  • Convex Optimization by Boyd and Vandenberghe (2008). 
  • Approximate Dynamic Programming (updated Chapter 6 of Dynamic Programming and Optimal Control, Volume II) by Bertsekas (2011). 
  • Control Techniques for Complex Networks by Meyn (2007). 
  • Introduction to Queueing Theory by Cooper (1981). 
  • Markov Chains and Stochastic Stability by Meyn and Tweedie (1993). 
  • Mathematical Control Theory, 2nd edition, by Sontag (1998). 
  • Non-Uniform Random Variate Generation by Devroye (1986). 
  • Stochastic Programming by Kall and Wallace (2003). 
  • Mathematical Methods of Engineering Analysis by Çinlar and Vanderbei (2000). 
  • Multiple Comparison Procedures by Hochberg and Tamhane (1987).
  • Algorithms and Complexity by Wilf (1986). 
  • Applied Mathematical Programming by Bradley, Hax, and Magnanti (1977).

• “Give a man a fish, feed him for a day; teach him how to fish, feed him for a lifetime.” – Lao Tzu (Lao Tse, Laozi)
• “Chance favors the prepared mind.” – Louis Pasteur
• “When life hands you a lemon, make lemonade.”
• “It is not possible to wait for inspiration, and even inspiration alone is not sufficient. Work and more work is necessary. Man blessed by genius can create nothing really great, not even anything mediocre, if he does not toil as hard as a slave.” – Peter Ilyich Tchaikovsky
• “As a well spent day brings happy sleep, so a life well used brings happy death.” - Leonardo da Vinci
• “Success is not final, failure is not fatal: it is the courage to continue that counts.” – Unknown, sometimes attributed to Winston Churchill

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