Josiah Hester works broadly in computer engineering, with a special focus on wearable devices, edge computing, and cyber-physical systems. His Ph.D. work focused on energy harvesting and battery-free devices that failed intermittentently. He now focuses on sustainable approaches to computing, via designing health wearables, interactive devices, and large-scale sensing for conservation. 
   
His work in health is focused on increasing accessibility and lowering the burden of getting preventive and acute healthcare. In both situations, he designs low-burden, high-fidelity wearable devices that monitor aspects of physiology and behavior, and use machine learning techniques to suggest or deliver adaptive and in-situ interventions ranging from pharmacological to behavioral. 
   
His work is supported by multiple grants from the NSF, NIH, and DARPA. He was named a Sloan Fellow in Computer Science and won his NSF CAREER in 2022. He was named one of Popular Science's Brilliant Ten, won the American Indian Science and Engineering Society Most Promising Scientist/Engineer Award, and the 3M Non-tenured Faculty Award in 2021. His work has been featured in the Wall Street Journal, Scientific American, BBC, Popular Science, Communications of the ACM, and the Guinness Book of World Records, among many others.

Dr. Chen is an Assistant Professor in the School of Computational Science and Engineering. Previously he was a Research Scientist at the Oden Institute for Computational Engineering and Sciences at the University of Texas at Austin. Dr. Chen’s research is in the multidisciplinary fields of computational mathematics, data science, scientific machine learning, and parallel computing with various applications in materials, energy, health, and natural hazard. Specifically, his research focuses on developing fast, scalable, and parallel computational methods for integrating data and models under high-dimensional uncertainty to make (1) statistical model learning via Bayesian inference, (2) reliable system prediction with uncertainty quantification, (3) efficient data acquisition through optimal experimental design, and (4) robust control and design by stochastic optimization.

Dr. Gunter is an Assistant Professor in Aerospace Engineering at the Georgia Institute of Technology. He received his B.S. in mechanical engineering from Rice University, and later his M.S. and Ph.D. in aerospace engineering from the University of Texas at Austin, specializing in orbital mechanics. Prior to joining Georgia Tech, Dr. Gunter was on the faculty of the Delft University of Technology (TU-Delft) in the Netherlands, as a member of the Physical and Space Geodesy section. His research activities involve various aspects of spacecraft missions and their applications, such as investigations into current and future laser altimetry missions, monitoring changes in the polar ice sheets using satellite data, applications of satellite constellations/formations, and topics surrounding kinematic orbit determination. He has been responsible for both undergraduate and graduate courses on topics such as satellite orbit determination, Earth and planetary observation, scientific applications of GPS, and space systems design. He is currently a member of the AIAA Astrodynamics Technical Committee, and also serves as the Geodesy chair for the Fall AGU Meeting Program Committee. He has received a NASA group achievement award for his work on the GRACE mission, and he is also a former recipient of a NASA Earth System Science Graduate Fellowship. He is a member of the American Institute of Aeronautics and Astronautics (AIAA), the American Geophysical Union (AGU), and the International Association of Geodesy (IAG).

Ashok Goel is a Professor of Computer Science in the School of Interactive Computing at Georgia Institute of Technology in Atlanta, USA. He obtained his Ph.D. from The Ohio State University. At Georgia Tech, he is also the Director of the Ph.D. Program in Human-Centered Computing, a Co-Director of the Center for Biologically Inspired Design, and a Fellow of Brook Byers Institute for Sustainable Systems. For more than thirty years, Ashok has conducted research into artificial intelligence, cognitive science and human-centered computing, with a focus on computational design, modeling and creativity. His recent work has explored design thinking, analogical thinking and systems thinking in biological inspired design (https://www.youtube.com/watch?v=wiRDQ4hr9i8), and his research is now developing virtual research assistants for modeling biological systems. Ashok teaches a popular course on knowledge-based AI as part of Georgia Tech's program on Online Masters of Science in Computer Science. He has pioneered the development of virtual teaching assistants, such as Jill Watson, for answering questions in online discussion forums (https://www.youtube.com/watch?v=WbCguICyfTA). Chronicle of Higher Education recently called virtual assistants exemplified by Jill Watson as one of the most transformative educational technologies in the digital era. Ashok is the Editor-in-Chief of AAAI's AI Magazine.

Neha Kumar is an Associate Professor jointly appointed at the Sam Nunn School of International Affairs and the School of Interactive Computing at Georgia Tech. Her research lies at the intersection of human-computer interaction and global sustainable development, with a focus on global health and community informatics. Her work contributes feminist perspectives to the design and integration of emerging technologies across marginalized contexts in the Global South. 

Her research has been recognized by multiple ACM Best Paper and Honorable Mention awards. Neha received the College of Computing's Lockheed Inspirational Young Faculty Award (2017) and the Lockheed Excellence in Teaching Award (2019). She currently serves as the President of ACM SIGCHI. She earned her Ph.D. in Information Management Systems from UC Berkeley, Master’s degrees in Computer Science and Education from Stanford University, and Bachelor’s in Computer Science and Applied Math from UC Berkeley.

Richard Fujimoto is a Regents’ Professor, Emeritus in the School of Computational Science and Engineering at the Georgia Institute of Technology. He received the Ph.D. degree from the University of California-Berkeley in 1983 in Computer Science and Electrical Engineering. He also received an M.S. degree from the same institution as well as two B.S. degrees from the University of Illinois-Urbana. 

Fujimoto is a pioneer in the parallel and distributed discrete event simulation field. Discrete event simulation is widely used in areas such as telecommunications, transportation, manufacturing, and defense, among others. His work developed fundamental understandings of synchronization algorithms that are needed to ensure the correct execution of discrete event simulation programs on high performance computing (HPC) platforms. His team developed many new algorithms and computational techniques to accelerate the execution of discrete event simulations and developed software realizations that impacted several application domains. For example, his Georgia Tech Time Warp software was deployed by MITRE Corp. to create online fast-time simulations of commercial air traffic to help reduce delays in the U.S. National Airspace. An active researcher in this field since 1985, he authored or co-authored three books and hundreds of technical papers including seven that were cited for “best paper” awards or other recognitions. His research included several projects with Georgia Tech faculty in telecommunications, transportation, sustainability, and materials leading to numerous publications co-authored with faculty across campus.

Xiaoming Huo is an A. Russell Chandler III Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. Dr. Huo's research interests include statistical theory, statistical computing, and issues related to data analytics. He has made numerous contributions on topics such as sparse representation, wavelets, and statistical problems in detectability. His papers appeared in top journals, and some of them are highly cited. He is a senior member of IEEE since May 2004. 

Dr. Haesun Park is a Regents' Professor and Chair in the School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia, U.S.A. She was elected as a SIAM Fellow in 2013 and IEEE Fellow in 2016 for her outstanding contributions in numerical computing, data analysis, and visual analytics. She was the Executive Director of Center for Data Analytics 2013-2015 and was the director of the NSF/DHS FODAVA-Lead (Foundations of Data and Visual Analytics) Center 2008-2014. She has published extensively in the areas of numerical computing, large-scale data analysis, visual analytics, text mining, and parallel computing. She was the conference co-chair for SIAM International Conference on Data Mining in 2008 and 2009 and an editorial board member of the leading journals in computational science and engineering such as IEEE Transactions on Pattern Analysis and Machine Intelligence, SIAM Journal on Matrix Analysis and Applications, and SIAM Journal on Scientific Computing. She was the plenary keynote speaker at major international conferences including SIAM Conference on Applied Linear Algebra in 1997 and 2015, and SIAM International Conference on Data Mining in 2011. Before joining Georgia Tech, she was a professor in Department of Computer Science and Engineering, University of Minnesota, Twin Cities 1987- 2005 and a program director in the Computing and Communication Foundations Division at the National Science Foundation, Arlington, VA, U.S.A., 2003 - 2005. She received a Ph.D. and an M.S. in Computer Science from Cornell University, Ithaca, NY in 1987 and 1985, respectively, and a B.S. in Mathematics from Seoul National University, Seoul, Korea in 1981 with the Presidential Medal for the top graduate.