I am an Assistant Professor in the College of Business at the University of Michigan-Dearborn, where I teach courses in business analytics. My area of research expertise is Operations Research.
Faculty bio: http://umdearborn.edu/users/davidlk
Google Scholar site: David L. Kaufman
I also serve as a faculty advisor for the Tauber Institute for Global Operations at the University of Michigan. Over the years, I have had the pleasure of advising 16 projects, at Amazon, Amazon Robotics, Boeing, Borg Warner, General Mills, Grainger, Microsoft, and SRG Global. Recent projects:
Boeing 2022: Build Optimization
Amazon Robotics 2021: Supplier Assessment
Amazon 2020: New Site Launch
Amazon 2019: Amazon Delivery Electrification
Amazon 2018: Fulfillment Center Truck Yard Forecasting
Amazon 2017: Outbound Problem Elimination
General Mills 2016: New Product Forecasting using Machine Learning
Amazon 2015: Amazon Robotics Stow Error Reduction
Microsoft 2015: Pricing Strategies for an Infrastructure-As-A-Service Cloud Market
Two of my papers were featured in ISE Magazine*:
1. ISE Magazine September 2021 feature: Tackling the next level of uncertainty in medical decision-making, with Lauren N. Steimle and Brian P. Denton.
2. ISE Magazine July 2020 feature: The trials of the operations that conduct clinical trials, with Jivan Deglise-Hawkinson, Blake Roessler, and Mark Van Oyen.
* This Research section is provided for informational purposes only with permission of the Institute of Industrial and Systems Engineers (from the July 2020 issue of ISE Magazine, Copyright©2020, and the September 2021 issue of ISE Magazine, Copyright©2021). All rights reserved.
1. Lauren N. Steimle, David L. Kaufman, and Brian T. Denton. Multi-model Markov decision processes. IISE Transactions, 53 (10): 1124-1139, 2021. [journal] Featured in ISE Magazine.
2. Gabriel Zayas-Cabán, Emmett J. Lodree, and David L. Kaufman. Optimal control of parallel queues for managing volunteer convergence. Production and Operations Management, 29 (10): 2268-2288, 2020. [journal]
3. Jivan Deglise-Hawkinson, David L. Kaufman, Blake Roessler, and Mark P. Van Oyen. Access planning and resource coordination for clinical research operations. IISE Transactions, 52 (8): 832-846, 2020. [journal] Featured in ISE Magazine.
4. Jivan Deglise-Hawkinson, Jonathan E. Helm, Todd R. Huschka, David L. Kaufman, and Mark P. Van Oyen. A capacity allocation planning model for integrated care and access management. Production and Operations Management: Special Issue on Patient-Centric Healthcare Management in the Age of Analytics, 27 (12): 2270-2290, 2018. [journal]
5. Jeffrey Hobbs, David L. Kaufman, Hei-Wai Lee, and Vivek Singh. Stock returns and disagreement among sell-side analysts. Journal of Applied Business Research, 34 (3): 487-496, 2018. [journal]
6. David L. Kaufman and Andrew J. Schaefer. Robust Modified Policy Iteration. INFORMS Journal on Computing, 25 (3): 396-410, 2013. [journal]
7. Luz A. Caudillo-Fuentes, David L. Kaufman, and Mark E. Lewis. A Simple Heuristic for Load Balancing in Parallel Processing Networks with Highly Variable Service Time Distributions. Queueing Systems: Theory and Applications, 64 (2): 135-171, 2010. [heavy-tail-questa-final.pdf]
8. David L. Kaufman and Mark E. Lewis. Machine maintenance with workload considerations. Naval Research Logistics, 54 (7): 750-766, 2007. [reliability.pdf]
9. David L. Kaufman, Hyun-Soo Ahn, and Mark E. Lewis. On the introduction of an agile, temporary workforce into a tandem queueing system. Queueing Systems: Theory and Applications, 51 (1-2): 135-171, 2005. [flex-temp.pdf]
10. David L. Kaufman, Ioan Kosztin, and Klaus Schulten. Expansion method for stationary states of quantum billiards. American Journal of Physics 67 (2): 133-141, 1999. [KAUF99.ps , journal]
11. Don Lemons and David L. Kaufman. Brownian motion of a charged particle in a magnetic field. IEEE Transactions on Plasma Science 27 (5): 1288-1296, 1999. [ieeeexplore]
1. David L. Kaufman, Andrew J. Schaefer, and Mark S. Roberts. Living-Donor Liver Transplantation Timing Under Ambiguous Health State Transition Probabilities, SSRN, 2017. [robustLivingDonor.pdf]
1. Lauren N. Steimle, David L. Kaufman, and Brian T. Denton. Multi-model Markov decision processes. Proceedings of the 2018 Manufacturing & Service Operations Management (MSOM) Conference (Healthcare Operations Management SIG), 2018. The full paper is published in IISE Transactions [journal], and was featured in ISE Magazine.
2. David L. Kaufman, Andrew J. Schaefer, and Mark S. Roberts. Living-Donor Liver Transplantation Timing Under Ambiguous Health State Transition Probabilities ‐ Extended Abstract. Proceedings of the 2011 Manufacturing & Service Operations Management (MSOM) Conference, 2011. [robustLiverExtendedAbstract.pdf] The full paper is available through SSRN. [robustLivingDonor.pdf]
1. David Kaufman, Katta G. Murty, and Ahmed AlSaati. Clustering problems in offshore drilling of crude oil wells. In: Models for Optimum Decision Making. International Series in Operations Research & Management Science, vol. 286, Springer, Cham, 29-42, 2020.
2. Katta G. Murty and David Kaufman. Blending operations in crude oil refineries. In: Models for Optimum Decision Making. International Series in Operations Research & Management Science, vol. 286, Springer, Cham, 51-62, 2020.
David L. Kaufman. Dynamic control of production systems with varying service capacity. Ph.D. dissertation, University of Michigan, 2005. [link]