Dr. Esra Büyüktahtakın Toy is a Professor in the Grado Department of Industrial and Systems Engineering at Virginia Tech and the Director of the Systems Optimization and Machine Learning (SysOptiMaL) Lab. She is also an affiliated faculty member with the Global Change Center, the Invasive Species Collaborative, and the Center for Emerging, Zoonotic and Arthropod-borne Pathogens at Virginia Tech. Her research advances multi-stage stochastic mixed-integer programming and integrates machine learning, deep reinforcement learning, and computational optimization to support risk-averse decision-making under uncertainty. She applies these methods in epidemic disease modeling, healthcare logistics, invasive species management, agriculture, forestry, cancer treatment planning, and undersea warfare search operations. Dr. Toy has received significant recognitions including the NSF CAREER Award, the NSF EPSCoR First Award, five INFORMS Best Publication Awards, and major external funding from agencies such as the NSF, USDA, U.S. Forest Service, and the Office of Naval Research. She has published 45 peer-reviewed journal articles and has contributed extensively to the OR community through invited seminars, keynote talks, panel service, and interdisciplinary collaborations.

Dr. Julie Swann is the department head and A. Doug Allison Distinguished Professor of the Edward P. Fitts Department of Industrial and Systems Engineering at NC State University. She is an affiliate faculty in the Joint Department of Biomedical Engineering at NC State and the University of North Carolina at Chapel Hill. Dr. Swann is a Fellow of IISE, INFORMS and AIMBE as well as the current past-president of INFORMS. Throughout her career, Swann has conducted research, outreach and education to improve how health and humanitarian systems operate worldwide. Her work with analytics relates to public health, public policy, epidemiology, infectious disease, supply chain management, and disaster response. This work allowed her to serve as a science advisor for the H1N1 pandemic response at the Centers for Disease Control and Prevention. Along with the CDC, Swann has collaborated with health and humanitarian organizations such as: The American Red Cross, The Carter Center, CARE USA, Children’s Healthcare of Atlanta, Emory University Hospital, State Departments of Public Health, and many other companies Worldwide, she has contributed to the education of thousands of practitioners in health and humanitarian systems through the co-creation and teaching in a professional certificate program at Georgia Tech.

Dr. David B. Brown is the Snow Family Business Professor in Decision Sciences and the Faculty Director for the Center for Energy, Development and Global Environment (EDGE) at Duke University's Fuqua School of Business. Professor Brown’s research focuses on designing and analyzing optimization algorithms for decision-making under uncertainty. His recent research includes developing and analyzing solution techniques for problems such as network revenue management, dynamic pricing in shared vehicle systems, stochastic scheduling problems, and sequential search problems. Professor Brown serves an Area Editor for the Decision Analysis Area at the journal Operations Research.

Dr. Ali E. Abbas is a professor of industrial and systems engineering at the University of Southern California. His research interests include all aspects of decision-making under uncertainty broadly defined. He is the author and co-author of numerous books and research articles on decision-making and ethics including Foundations of Decision Analysis (with Ronald A. Howard), Foundations of Multiattribute Utility, Next-Generation Ethics, Improving Homeland Security Decisions, and Ethical Decision Quality: Building an Ethical Decision Culture.

He is the recipient of multiple awards from the National Science Foundation for his work including the National Science Foundation CAREER award and is recipient of numerous first-prize awards for research papers including IEEE Systems Journal's Best Paper Award and the Decision Analysis Society of INFORMS Best Paper Award. Dr. Abbas is an IEEE Systems Council Distinguished Lecturer. He serves as an Associate Editor for INFORMS Operations Research and Decision Analysis journals, Entropy, Decision and has also served as the Decision Analysis area Editor for ISE Transactions.

Dr. Lewis Ntaimo is Professor and Department Head, and Sugar and Mike Barnes Department Head Chair of the Wm

Dr. Ntaimo’s primary research interests include modeling and algorithms for decision-making problems involving uncertainty and risk, systems modeling, process optimization, and computer simulation. Applications of interest include vaccination policies for epidemics, wildfire management, healthcare management, college counseling and psychological service management, and power systems operations and maintenance. His research over the years has been funded by the U.S. federal agencies and

In this episode of the podcast, Dr. Ntaimo talks about his journey into Operations research. He also talks about different aspects of his research and what advice he would give to graduate students to navigate the research process.

To learn more about Dr. Ntaimo, make sure to visit his google scholar page: https://scholar.google.com/citations?hl=en&user=1l13jigAAAAJ

Dr. Brian Fralix is an Associate Professor in the School of Mathematical and Statistical Sciences at Clemson University. His research areas include queueing systems, Markov processes, and reliability theory. He earned his B.S. in Mathematical Sciences from Clemson University and his Ph.D. in Operations Research from Georgia Tech. Prior to joining Clemson, he was a postdoctoral fellow at EURANDOM at Eindhoven University of Technology. Dr. Fralix is also an associate editor and referee for several prestigious journals and has published extensively in his fields of expertise.

In this episode, Dr. Fralix discusses his journey into operations research, focusing on queuing systems, Markov processes, and matrix analytic methods. He shares his research interests in gene expression and Bitcoin, highlighting how stochastic processes can be applied to these fields. He also talks about his accidental yet impactful involvement in matrix analytic methods and emphasizes the importance of persistence, self-teaching, and mentorship for students pursuing a career in operations research.

To learn more about Dr. Fralix, you may visit his personal website and Google Scholar page.

Dr. Mostafa Reisi is an Assistant Professor in the Department of Industrial Engineering at the University of Florida. He received his PhD in industrial and systems engineering from Georgia Institute of Technology and M.Sc. degrees in transportation engineering and applied mathematics from the Southern Illinois University Edwardsville. His research interests focus on developing efficient methodologies and algorithms for modeling and monitoring systems with high-dimensional or network data in precision agriculture, manufacturing, healthcare, and transportation systems. He is also interested in adaptive sampling and multi-accuracy data fusion.

In this podcast episode, Dr. Reisi discusses his journey in the field of operations research, particularly focusing on high-dimensional data and machine learning. He elaborates on his work with tensor data for modeling and monitoring high-dimensional systems, emphasizing applications in healthcare and manufacturing. Dr. Reisi explains the concept and advantages of tensor regression, federated learning for data privacy, and robust models to handle outliers. He also shares valuable advice for graduate students, highlighting the importance of self-teaching and finding good mentors.

To learn more about Dr. Reisi, make sure to visit his personal website and Google Scholar page.

Dr. Seth Guikema is a professor in the Department of Civil and Environmental Engineering and Industrial Operations Engineering at the University of Michigan. He also holds an adjunct position at the University of Stavanger, Norway. Dr. Guikema’s research interests include community resilience, risk analysis, sustainability, and equity, with a focus on areas prone to significant natural hazards. He completed his BS at Cornell, MS at Stanford, MEng at the University of Canterbury, and PhD in Engineering Risk and Decision Analysis at Stanford.

In this podcast episode, Dr. Guikema shares his journey into the world of Operations Research, starting from his initial training in Civil and Environmental Engineering to his current focus on community resilience, risk, sustainability, and equity. He discusses his early fascination with risk analysis and probabilistic estimation, which led him to pursue graduate studies and a prolific research career. He emphasizes the importance of integrating data-driven approaches with traditional methods to better prepare for and respond to natural hazards.

Finally, Dr. Guikema offers valuable advice for students and early-career professionals interested in Operations Research and Analytics. He encourages trying research, embracing diverse experiences, and being open to new ideas.

To learn more about Dr. Guikema, make sure to visit his personal website and  Google Scholar page.

Dr. David Morton is the Walter P. Murphy Professor of Industrial Engineering and Management Sciences at Northwestern University and an INFORMS fellow. He holds a B.S. degree in mathematics and physics from Stetson University and M.S. and Ph.D. degrees from Stanford University. Prior to joining Northwestern, he was on the faculty at the University of Texas at Austin and worked as a Fulbright Research Scholar at Charles University in Prague and as a National Research Council Postdoctoral Fellow in the OR Department at the Naval Postgraduate School. Dr. Morton has received several honors and awards, including the George E. Nicholson Paper Prize, the Presidential Early Career Award for Scientists and Engineers, and the INFORMS Graduate Teaching Award. 

In this podcast episode, Dr. Morton explores his research in stochastic and large-scale optimization, applied to areas such as public health, security, and energy systems. He expresses enthusiasm for effectively communicating risk and uncertainty in public health, bridging the gap between operations research and computer science communities, and improving decision-making within broader communities. Dr. Morton advises graduate students to prioritize communication and connections, fostering collaborations with peers to address real-world optimization problems.

To learn more about Dr. Morton, make sure to visit his personal website and his Google Scholar page. 

Dr. Dan Li is an assistant professor in the Department of Industrial Engineering at Clemson University. She received her PhD in industrial engineering and Master’s in statistics from the Georgia Institute of Technology in 2021 and 2020, respectively. She earned her bachelor’s degree in mechanical engineering from Tsinghua University in Beijing, China, in 2015. She has recently been awarded many research grants, for instance, the most recent National Science Foundation grant for her collaborative project on Human-Centered Cybersecurity in Robotic Surgery.

In this podcast episode, Dr. Li discusses her research interests, encompassing applied statistics for cyber-physical security and resilience, online anomaly detection, complex system modeling for Internet of Things-enabled manufacturing and energy systems, as well as the application of machine learning in quality, reliability, and control. Additionally, she provides valuable advice for graduate students on proactively managing their careers, emphasizing the importance of seeking out opportunities and prioritizing self-care. For new PhD students, Dr. Li recommends gaining hands-on research experience to explore their interest in their potential adviser's research area.

To learn more about Dr. Li, make sure to visit her personal website and her Google Scholar page. You can also follow her on X (formerly known as Twitter) @LiDan_IE.