Weiwei Chen

Associate Professor

Area of expertise

Supply Chain Management

848-445-9471 wchen@business.rutgers.edu Curriculum Vitae

Dr. Chen’s research interest lies in operations and finance interface, as well as supply chain operations planning and scheduling. He also works on simulation and randomized global optimization methodologies. He has extensive experience working with businesses and public sectors, especially in energy and healthcare, to improve strategic decisions and operational efficiencies using data analytics. His work has appeared in Operations Research, Manufacturing & Service Operations Management, Interfaces, Automatica, IEEE Transactions on Automatic Control, IEEE Transactions on Smart Grid, etc. Dr. Chen received his Ph.D. degree from University of Wisconsin-Madison, and the M.S. and B.S. degree from Tsinghua University, Beijing, China. Prior to joining Rutgers Business School, he was a Scientist at GE Global Research, NY, solving various problems from GE Energy, GE Aviation, Lockheed Martin and electric utility companies.

Academic degrees

Ph.D., University of Wisconsin-Madison; Industrial Engineering
M.S., Tsinghua University; Control Science and Engineering
B.S., Tsinghua University; Automation

Insights

Research aims to improve operational efficiencies at busy U.S. border crossings

Wednesday, January 03, 2018

Master of Science in Supply Chain Management ranked No. 6 in the nation

Monday, April 08, 2019

Faculty Snapshot: Supply chain expertise built on a zeal for problem-solving

Monday, October 16, 2017

Taking supply chain knowledge to the next level with analytics

Tuesday, July 11, 2017

Rutgers professor's research may hold key to less congested U.S. border crossings

Thursday, February 25, 2016

Media Mentions

Beijing Institute of Technology. 2019 Informs Service Science Conference Best Paper Award, Weiwei Chen

Sunday, July 14, 2019

Customs Broker News. 5 things operations managers must know about opportunity cost, Weiwei Chen

Wednesday, June 12, 2019

Publications

Recent Publications

For a complete list of publications, see Google page.

W. Chen, B. Melamed, O. Sokolinskiy and B. Sopranzetti. Cash Conversion Systems in Corporate Subsidiaries, Manufacturing & Service Operations Management, 19(4): 604–619, 2017.
R. Tyagi, W. Chen, J. Black, P. Tiwari, B. Lecours and J. Shaver. Transforming Electrical Load from an Operational Constraint to a Controllable Resource, Interfaces, 47(4): 292–304, 2017.
S. Gao, W. Chen and L. Shi. A New Budget Allocation Framework for the Expected Opportunity Cost, Operations Research, 65(3): 787–803, 2017.
W. Chen. Sensitivity-based Nested Partitions for Solving Markov Decision Processes, Operations Research Letters, 45(5): 481–487, 2017.
S. Gao and W. Chen. A Partition-based Random Search for Stochastic Constrained Optimization via Simulation, IEEE Transactions on Automatic Control, 62(2): 740–752, 2017.
W. Chen, L. Lei, Z. Wang, M. Teng and J. Liu. Coordinating Supplier Selection and Project Scheduling in Resource-Constrained Construction Supply Chains, International Journal of Production Research, forthcoming.

Dissertations Supervised

Name: Jian, Zhe
Graduation Date: 2017/May
Thesis Title: Multimodal Freight Transportation Problem: Model, Algorithm and Environmental Impacts
(Co-Advised with Lei Lei)

Name: Wang, Zhengwei
Graduation Date: 2016/October
Thesis Title: Coordinated Supplier Selection and Project Scheduling in a Resource-Constrained Construction Supply Chains
(Co-Advised with Lei Lei)

Executive Education Programs

Mini-MBA: Artificial Intelligence

The Artificial Intelligence Mini-MBA is intended to (1) acquaint the leaders of a business enterprise on the general principles of automation (Robotic Process Automation and Artificial Intelligence), (2) apply the principles to address persistent business pain points, (3) augment the capability of technical and human resources, and/or (4) execute a change management/ transformation process.

In Class program: $4995.00

Next Class Date

Nov 01 - Dec 08, 2022

Learn More

Artifical Intelligence depicted by x-ray of human brain overlayed on data lines