Lennart Baardman

Currently, I am an Assistant Professor of Technology and Operations at the Ross School of Business. Prior to joining the University of Michigan, I received my Ph.D. in Operations Research from the Massachusetts Institute of Technology, an MASt in Mathematics from the University of Cambridge, and a BSc in Econometrics and Operations Research from the University of Groningen.

My research interests focus on using analytical techniques such as mathematical modeling, optimization, statistics, and machine learning to solve practice- and data-driven problems in revenue management, pricing, supply chain management, and logistics. My current research mainly focuses on developing and testing novel models for promotional pricing and advertising challenges in the retail, manufacturing, and online industries. These research problems are motivated by the practice and data of our collaborators: Adobe, CMPC, Johnson & Johnson, Oracle.

Research

Papers Published and Accepted

L. Baardman, M.C. Cohen, K. Panchamgam, G. Perakis. 2021. Using Business Analytics to Upgrade Sales Promotions. Management and Business Review 1(3):54-63.

L. Baardman, K.J. Roodbergen, H.J. Carlo, A.H. Schrotenboer. 2021. A Special Case of the Multiple Traveling Salesman Problem in End-of-aisle Picking Systems. Transportation Science 55(5):1151-1169.

L. Baardman, S. Borjian Boroujeni, T. Cohen-Hillel, K. Panchamgam, G. Perakis. 2020. Detecting Customer Trends for Optimal Promotion Targeting. Manufacturing & Service Operations Management.

First place in POMS College of Supply Chain Management Best Student Paper Award (2019).
Honorable mention in MSOM Practice-Based Paper Competition (2019).
Finalist in POMS-JD.com Best Data-Driven Research Paper Competition (2019).
Finalist in INFORMS Service Science Cluster Best Paper Award (2019).
Finalist in INFORMS Social Media Analytics Best Student Paper Award (2019).

L. Baardman, M.C. Cohen, K. Panchamgam, G. Perakis, D. Segev. 2019. Scheduling Promotion Vehicles to Boost Profits. Management Science 65(1):50-70.

First place in INFORMS Service Science Cluster Best Paper Award (2016).

L. Baardman, K.J. Roodbergen, H.J. Carlo. 2016. Job Sequencing in a Miniload System. 14th IMHRC Proceedings, Karlsruhe.

Papers Under Review and In Progress

Z. Zhang, H.S. Ahn, L. Baardman. 2022. Ordering and Ranking Products for an Online Retailer. Submitted to Operations Research.

L. Baardman, C. Rares, G. Perakis, D. Singhvi, O. Skali Lami, L. Thayaparan. 2021. The Role of Optimization in Some Recent Advances in Data-Driven Decision-Making. Major revision in Mathematical Programming.

L. Baardman, E. Fata, A. Pani, G. Perakis. 2021 Dynamic Creative Content Optimization in Online Display Advertising. R&R in Management Science.

L. Baardman, I. Levin, G. Perakis, D. Singhvi. 2020. Leveraging Comparables for New Product Sales Forecasting. R&R in Management Science.

First place in POMS Applied Research Challenge (2018).
First place in POMS College of Supply Chain Management Best Student Paper Award (2018).
Honorable mention in MIT Operations Research Center Best Student Paper Competition (2018).

L. Baardman, E. Fata, A. Pani, G. Perakis. 2020. Learning Optimal Online Advertising Portfolios with Periodic Budgets. R&R in Operations Research.

Finalist in George Nicholson Student Paper Competition (2018).
Finalist in INFORMS Service Science Cluster Best Student Paper Award (2019).

L. Baardman, K. Panchamgam, G. Perakis. 2019. Pass-through Constrained Vendor Funds for Promotion Planning. Major revision in Manufacturing & Service Operations Management.

R. Hu, H.S. Ahn, L. Baardman. Designing Micro-Fulfillment Centers to Reduce Picking Costs in Online Grocery. Work in progress.

L. Baardman. Passing Data Directly into Prescriptive Analytics. Work in progress.

L. Baardman, X Wang. Improving Product Availability to Reduce Customer Attrition in Clothing Rental Subscriptions. Work in progress.

Patents

US20190066128A1 - Computer System and Method to Predict Customer Behavior Based on Inter-Customer Influences and to Control Distribution of Electronics Messages. Application published in February 2019 (L. Baardman, S. Borjian Boroujeni, T. Cohen-Hillel, K. Panchamgam, G. Perakis)

Teaching

2022 Winter TO 899 Doctoral Seminar in Technology and Operations (PhD)

2022 Winter TO 640 Big Data Tools and Techniques (MBA)

2020 Fall TO 640 Big Data Tools and Techniques (MBA)

2020 Winter TO 640 Big Data Tools and Techniques (MBA)

2019 Fall TO 899 Predictive and Prescriptive Analytics in Operations Management (PhD)

Students

Zijin Zhang co-advised with Hyun-Soo Ahn (2019-present)
Renjun Hu co-advised with Hyun-Soo Ahn (2020-present)

Honors

2021 - First place in Tauber Spotlight! Competition
2020 - Finalist in INFORMS Innovative Applications in Analytics Award
2019 - Finalist in INFORMS Service Science Cluster Best Paper Award
2019 - Finalist in INFORMS Service Science Cluster Best Student Paper Award
2019 - Finalist in INFORMS Social Media Analytics Best Student Paper Award
2019 - Honorable mention in MSOM Practice-Based Paper Competition
2019 - Finalist in POMS-JD.com Best Data-Driven Research Paper Competition
2019 - First place in POMS College of Supply Chain Management Best Student Paper Award
2018 - Finalist in George Nicholson Student Paper Competition
2018 - MIT Sloan Excellence in Teaching Award - Outstanding Teaching Assistant
2018 - First place in POMS Applied Research Challenge
2018 - First place in POMS College of Supply Chain Management Best Student Paper Award
2018 - Honorable mention in MIT Operations Research Center Best Student Paper Competition
2016 - First place in INFORMS Service Science Cluster Best Paper Award
2016 - Finalist in Facebook Fellowship
2015 - Finalist in INFORMS Revenue Management and Pricing Practice Award
2013 - Groningen University Fund-100 Prize
2011-2013 - Member of the Honours College of the University of Groningen

Contact

Address
Michigan Ross School of Business
701 Tappan Street, Room R4484
Ann Arbor, MI 48109-1234
United States

Phone
+1 617-417-7461
Email
baardman at umich dot edu