Alex Weidong Chen is an optimization problem specialist, using mathematical modeling with linear/stochastic/dynamic programming to improve systems. He has been with Warmilu since the beginning in the materials science engineering senior design capstone course. Alex has been instrumental to the initial design of the blanket, calculation and theoretical modeling for the warming models, programming and logic design, and helped with the operations and manufacturing at Warmilu. Alex is a team champion and brings people together. In addition to Warmilu, Alex is currently a Ph.D. Candidate at the University of Michigan focusing on reinforcement and online learning with application in inventory control and revenue management. Alex is passionate about making sure the team makes the right informed vital decisions in smart inventory management, dynamic pricing, and supply chain management based on his data and operations research knowledge and direct experience.
Currently, Alex develops online learning algorithms to achieve optimal solution for the multi-period stochasticinventory control problem with unknown demand distribution, unknown capacity distribution,unknown production rate, unknown arrival rate, and other demand variables. He applies online convex optimization and machinelearning techniques to prove a guaranteed convergence rate between proposed algorithm and optimal hindsight solution. He has also developed a heuristic to minimize the expected cost of operating room management under both deterministic and non-deterministic cases.
He earned his bachelor’s degree (BSE) in Materials Science & Engineering and Electric Engineering at the University of Michigan College of Engineering. Prior to Warmilu, Alex has conducted research on batteries and semi-conductors and during Warmilu has interned at Alibaba. Fun fact: Alex has composed an operations research case study chapter in Professor Murty’s new book.