Mathieu Dahan is an Assistant Professor in the H. Milton Stewart School of Industrial and Systems Engineering. His research interests are in combinatorial optimization, game theory, and predictive analytics, with applications to service operations management and disaster logistics. His primary focus is on developing strategies for improving the resilience of large-scale infrastructures — particularly, transportation and natural gas networks — in the face of correlated failures such as security attacks and natural disasters. Current projects include: (i) Strategic design of network inspection systems; and (ii) Analytics-based response operations under uncertainty.

Dr. Dahan received a Ph.D. and M.S. in Computational Science and Engineering from the Massachusetts Institute of Technology, a M.Eng. and B.Eng. from the École Centrale Paris, and a B.S. in Mathematics from Paris-Sud University. He is the recipient of the MIT Robert Thurber Fellowship, the MIT Robert Guenassia Award, the Honorable Mention for the J-WAFS Fellowships, and the Best Poster Award at the Princeton Day of Optimization.

During the summer of 2016, he worked as a research scientist intern at Amazon.com (Seattle) in the Supply Chain Optimization Technologies team. Using Machine-Learning techniques, he worked on predicting the fulfillment cost and developing a prototype to grant a fast and accurate access to future shipping cost estimates.

Shaheen Azim Dewji, Ph.D., (she/her/hers) is an Assistant Professor in the Nuclear & Radiological Engineering and Medical Physics Programs at the Georgia Institute of Technology, where she leads the Radiological Engineering, Detection, and Dosimetry (RED²) research group. Dewji joined Georgia Tech following three years as faculty at Texas A&M University in the Department of Nuclear Engineering, and as a Faculty Fellow of the Center for Nuclear Security Science and Policy Initiatives (NSSPI). In her prior role at Oak Ridge National Laboratory, where she remained for almost 9 years, Dewji was Radiological Scientist in the Center for Radiation Protection Knowledge. Her research interests include development of dose coefficients, shielding design, and nuclear material detection assay using gamma-ray spectroscopy. Her recent work has focused on associated challenges in uncertainty quantification in dose estimation/reconstruction associated with the external exposure and internal uptake of radionuclides associated with applications of emergency response, defense, nuclear medicine, and occupational/public safety using Monte Carlo radiation transport codes and internal dose modeling. Dewji completed her Masters and Ph.D. degrees in Nuclear and Radiological Engineering at the Georgia Institute of Technology in Atlanta, GA and was a fellow of the Sam Nunn Security Program. She received her Bachelor of Science in Physics from the University of British Columbia. Dewji currently serves on the National Academies of Science, Engineering, and Medicine – Nuclear and Radiation Studies Board and is a member of the Board of Directors for both the American Nuclear Society and Health Physics Society.
   

Aarn Stebner works at the intersection of manufacturing, machine learning, materials, and mechanics. He joined the Georgia Tech faculty as an associate professor of Mechanical Engineering and Materials Science and Engineering in 2020.

Previously, he was the Rowlinson Associate Professor of Mechanical Engineering and Materials Science at the Colorado School of Mines (2013 – 2020), a postdoctoral scholar at the Graduate Aerospace Laboratories of the California Institute of Technology (2012 – 2013), a Lecturer in the Segal Design Institute at Northwestern University (2009 – 2012), a Research Scientist at Telezygology Inc. establishing manufacturing and “internet of things” technologies for shape memory alloy-secured latching devices (2008-2009), a Research Fellow at the NASA Glenn Research Center developing smart materials technologies for morphing aircraft structures (2006 – 2008), and a Mechanical Engineer at the Electric Device Corporation in Canfield, OH developing manufacturing and automation technologies for the circuit breaker industry (1995 – 2000).

Dr. Anirban Mazumdar joined Georgia Tech as an Assistant Professor in Mechanical Engineering in 2018. Dr. Mazumdar studies robot mobility with the goal of understanding and achieving agile, versatile, and efficient robot behaviors in unstructured environments. His previous experience includes a postdoctoral research position in the High Consequence Automation and Robotics Group at Sandia National Laboratories in Albuquerque, NM. He has broad experience with novel robotic systems including energy efficient bipedal robots, reconfigurable aerial vehicles, prosthetic devices, and relaxed stability mobile robots.

Dr. Liang began at Tech in 1990 as an assistant professor. Previously, he was an assistant professor at Oklahoma State University. He was named to the Bryan Professorship in 2005. He was President of Walsin-Lihwa Corporation in 2008-2010.

Professor Nagi Gebraeel is the Georgia Power Early Career Professor and Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. He received his MS and PhD from Purdue University in 1998 and 2003, respectively.

Dr. Gebraeel's research interests lie at the intersection of Predictive Analytics and Machine Learning in IoT enabled maintenance, repair and operations (MRO) and service logistics. His key focus is on developing fundamental statistical learning algorithms specifically tailored for real-time equipment diagnostics and prognostics, and optimization models for subsequent operational and logistical decision-making in IoT ecosystems. Dr. Gebraeel also develops cyber-security algorithms intended to protect IoT-enabled critical assets from ICS-type cyberattacks (cyberattacks that target Industrial Control Systems). From the standpoint of application domains, Dr. Gebraeel has general interests in manufacturing, power generation, and service-type industries. Applications in Deep Space missions are a recent addition to his research interests, specifically, developing Self-Aware Deep Space Habitats through NASA's HOME Space Technology Research Institute.

Dr. Gebraeel leads Predictive Analytics and Intelligent Systems (PAIS) research group at Georgia Tech's Supply Chain and Logistics Institute. He also directs activities and testing at the Analytics and Prognostics Systems laboratory at Georgia Tech's Manufacturing Institute. Formerly, Dr. Gebraeel served as an associate director at Georgia Tech's Strategic Energy Institute (from 2014 until 2019) where he was responsible for identifying and promoting research initiatives and thought-leadership at the intersection of Data Science and Energy applications. He was also the former president of the Institute of Industrial and Systems Engineers (IISE) Quality and Reliability Engineering Division, and is currently a member of the Institute for Operations Research and the Management Sciences (INFORMS), and IISE (since 2005).