Arthi Rao is a research scientist at the Center for Quality Growth and Regional Development at Georgia Tech. She has had a consistent focus on Health and Place research throughout her career. She has an interdisciplinary educational and professional background in Urban Planning, Epidemiology and Geographic Information Systems (GIS) from Georgia Tech. Her research interests focus on social determinants of health, healthcare access, healthy communities, and spatial methods. She uses methods including spatial clustering, data mining/classification techniques and hierarchical modeling in her research. She has integrated these methods to create decision-support tools for academic and industrial applications.

She regularly collaborates with researchers at The Morehouse School of Medicine, Georgia Tech, and the American Planning Association as a subject matter expert on healthy communities’ research and geospatial methods. She has published in journals on the topics of Health Impact Assessment (HIA), sustainability, walkability analysis, regional planning, and therapeutic landscapes. She also teaches courses titled “Public Health and the Built Environment” and “Public Health Analytics” at Georgia Tech.

Specialization Area: Health and Environment

Saleeby was formerly a research staff member from Oak Ridge National Laboratory where he was in the Manufacturing Science Division. His work focuses on connecting machines and manufacturing processes with Industry 4.0 and Industrial IoT technologies. Current interests center on applications of data analytics and closed-loop control for Hybrid Manufacturing processes, where additive and subtractive (machining) processes are combined within a single machine tool.

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.

Dr. Fan Zhang received her Ph.D. in Nuclear Engineering and M.S. in Statistics from UTK in 2019. She is the recipient of the 2021 Ted Quinn Early Career Award from the American Nuclear Society and joined the Woodruff School in July, 2021. She is actively involved with multiple international collaborations on improving nuclear cybersecurity through the International Atomic Energy Agency (IAEA) and the DOE Office of International Nuclear Security (INS). Dr. Zhang’s research primarily focuses on the cybersecurity of nuclear facilities, online monitoring & fault detection using data analytics methods, instrumentation & control, and nuclear systems modeling & simulation. She has developed multiple testbeds using both simulators and physical components to investigate different aspects of cybersecurity as well as process health management.