This event is open to all IOE students, faculty, and staff. Link to attend virtually will be added closer to the event date.

Title:
INFORMS Navigating the Academic Job Market Panel

Abstract:
The academic job market is highly competitive and might seem like a complex process for the first-time job seekers. We are fortunate to have a number of wonderful Ph.D. students with first-hand experience who are willing to share their experience attaining faculty positions on the recent job market. We are holding a virtual lunch-and-learn event to help Ph.D. students learn more about different aspects and steps of finding an academic job. The event is open to all IOE students and faculty, and we particularly encourage attendance of Ph.D. students who are entering the job market this year or considering going on the academic job market in the future.

Bio:
Emily Tucker is an industrial engineer who develops operations research models to help others, particularly in the areas of healthcare operations and policy. In the fall of 2020, she will join the Department of Industrial Engineering at Clemson University as an Assistant Professor. She received her PhD and MSE in Industrial and Operations Engineering (IOE) from the University of Michigan. Emily was supported by an NSF Graduate Research Fellowship and a Rackham Merit Fellowship. Her dissertation work received the Richard and Eleanor Towner Prize for Outstanding PhD Research from the College of Engineering. While at Michigan, she served as President of the Student Leadership Board in IOE and an Editor of OR/MS Tomorrow. Prior to graduate school, Emily worked as a Research Health Economist for RTI Health Solutions and received her BS in Industrial Engineering from NC State.

Gian-Gabriel Garcia is a PhD Candidate in the Industrial and Operations Engineering Department at the University of Michigan. He holds a Bachelor’s degree in Industrial Engineering from the University of Pittsburgh and a Master’s degree in Industrial and Operations Engineering from the University of Michigan. In his research, Gian is interested in developing data-driven frameworks using predictive and prescriptive analytics to address by high-impact problems in healthcare. Motivated by applications in concussion, glaucoma, and cardiovascular disease, his current research focuses on (1) using large clinical datasets to gain patient-specific insights on disease progression and (2) combining these insights with stakeholders’ perspectives to improve diagnosis and treatment decisions. Upon completing his PhD, Gian will spend one year as a Postdoctoral Research Fellow at the Institute for Technology Assessment within Massachusetts General Hospital and the Harvard Medical School. Then, in Fall 2021, he will begin as an Assistant Professor at the H. Milton Stewart School of Industrial and Systems Engineering at the Georgia Institute of Technology.

Sentao Miao is a PhD candidate, supervised by Prof. Xiuli Chao, at Department of Industrial and Operations Engineering at University of Michigan. For methodologies, Sentao Miao focuses on statistical and machine learning algorithms such as online learning, multi-arm bandit, reinforcement learning, etc. For applications, he mainly works on operations management problems such as dynamic pricing, assortment selection, inventory control, etc. Sentao Miao obtained his Bachelor degree in Mathematics at Jacobs University Bremen, Germany. In college, he mainly worked on computational methods and approximation algorithms for high dimensional data. In the Fall 2020, he will join Bensadoun School of Retail Management (co-appointed at Operations Management division of Desautels Faculty of Management), McGill University, as an Assistant Professor.

Qi Luo is a PhD candidate in the Department of Industrial and Operations Engineering and Scientific Computing at the University of Michigan. He holds a Bachelor’s degree in Nuclear Science and Engineering from Xi’an Jiaotong University and a Master’s degree from the University of Michigan. Prior to graduate school, he worked as a research assistant at Argonne National Laboratory. His research focuses on bridging operations research with reinforcement learning and game theory to support data-driven decision making with applications to transportation, supply chain, and public policy. He is the student PI in NSF Convergence Accelerator Pilot (C-Accel) and works with many industrial partners including Ford, DiDi Chuxing, and Mcity to address the pressing problems in emerging mobility ecosystem. He has served as the PhD Liaison of the INFORMS student chapter at the University of Michigan. In the Spring of 2021, he will join the Department of Industrial Engineering at Clemson University as an Assistant Professor.