Rui Zhou received her MSc in Management Science & Engineering from Donghua University (DHU) in May 2020. Her research topics are mainly the operation of integrated energy systems with the building cluster (supervised by Dr. Dong Yang) and supply risk management (supervised by Dr. Hugh Medal). In her thesis, OPTIMIZATION FOR THE OPERATION OF THE BUILDING CLUSTER CONSIDERING THE BENEFIT REQUIREMENTS OF INDIVIDUAL BUILDING OWNERS, she developed a decision framework to assist building owners to set their benefit requirements and to support managers in determining the operational decisions of energy systems within the building cluster considering uncertain energy demands. The optimal operational decisions obtained using the developed framework can guarantee both individual benefits of owners and the collective benefit of the cluster, which effectively handle the benefit conflict existing the operation of the building cluster. Besides research related to her thesis, Rui also devoted herself to research on supplier risk management. She focused on the mitigation of endogenous supplier risk in low-volume-high-value manufacturing (e.g., shipbuilding and power plant construction). To solve the large-sized problems in her research, she studied and mastered Bender’s decomposition algorithm and the greedy algorithm.
Dr. Medal and Dr. Nicholas Hall (Ohio State) will be co-chairing the Doctoral Student Colloquium (DSC) at the 2020 INFORMS Annual Meeting on November 6-7 in National Harbor, MD. Dr. Medal was the chair for the 2019 INFORMS DSC.
Dr. Medal has been named as an associate editor for the journal Networks, a premier journal in the area of network optimization algorithms.
Mike Sherwin joined the Industrial Engineering Department at the University of Pittsburgh as an Assistant Professor in January 2020. Mike teaches courses focused on supply chain management, design of experiments, facility layout, and material handling. He is also pursuing research in the areas of engineering education, supply chain reliability, and predictive analytics. (Faculty Page |Personal Website)
Dr. Medal is the co-PI of a grant titled “Machine-Learning-Enabled Modeling for High-Dimensional Dynamics of Materials Processes,” and funded by the StART seed funding program organized by the Science Alliance at the University of Tennessee (https://scialli.utk.edu/)
Bhuiyan, T. H., Nandi, A. K., Medal, H., and Halappanavar, M. (2017) Risk-averse bi-level Stochastic Network interdiction model for Cyber-security. Technical report, Mississippi State University, Starkville, MS.
Gedik, R., Medal, H., Rainwater, C., Pohl, E., and Mason, S. (2014) Vulnerability assessment and re-routing of freight trains under disruptions: A coal supply chain network application. Transportation Research Part E, 71, 45–57.