Dyer’s research interests lie at the intersection of machine learning, optimization, and neuroscience. Her lab develops computational methods for discovering principles that govern the organization and structure of the brain, as well as methods for integrating multi-modal datasets to reveal the link between neural structure and function.

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. Jon Duke is the director of the Center for Health Analytics and Informatics at the Georgia Tech Research Institute (GTRI) and a principal research scientist at the School of Interactive Computing in the College of Computing. He began working at Georgia Tech in 2016. His career before Tech was entirely in medical environments, both as a physician and a researcher.  

At Georgia Tech his research focuses on advancing techniques for identifying patients of interest from diverse data sources with applications spanning research, quality, and clinical domains. 

Dr. Duke has led over $21 million in funded research for industry, government, and foundation partners. Dr. Duke’s research focuses on advancing techniques for identifying patients of interest from diverse data sources with applications spanning research, quality, and clinical domains.  He led the Merck-Regenstrief Partnership in Healthcare Innovation and was a founding member of OHDSI, an open-source international health data analytics collaborative.  In addition to numerous peer-reviewed publications, his work has been featured in the lay media including the New York Times, NPR, and MSNBC.  Dr. Duke completed his medical degree at Harvard Medical School and a master's in human-computer interaction at Indiana University.

I am an assistant professor in the School of Interactive Computing at Georgia Tech. Before joining Georgia Tech, I spent two wonderful years at Virginia Tech as a faculty member. Prior to this, I was a postdoctoral fellow in the Visual Computing Group at Harvard University, and received my Ph.D. from Human-Centred Computing Department, Monash University, Australia.

My research encompasses a wide range of topics within the fields of Visualization (VIS), VR/AR, and Human-Computer Interaction (HCI). I actively contribute to these communities and regularly publish my work in leading venues such as IEEE VIS, ACM CHI, IEEE TVCG, EuroVis, and IEEE VR. I am honored to have received three best paper honorable mention awards, notably from IEEE VIS in 2016 and 2022, as well as ACM CHI in 2021. I also serve as a program committee member for several prestigious conferences in my fields, including IEEE VIS 2022/23/24, ACM CHI 2023/24, and IEEE VR 2022/23/24.

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).

King Jordan is Professor in the School of Biological Sciences and Director of the Bioinformatics Graduate Program at the Georgia Institute of Technology. He has a computational laboratory and his group works on a wide variety of research and development projects related to: (1) human clinical & population genomics, (2) computational genomics for public health, and (3) computational approaches to functional genomics. He is particularly interested in the relationship between human genetic ancestry and health. His lab is also actively engaged in capacity building efforts in genomics and bioinformatics in Latin America. 

Grover’s research activities in process systems engineering focus on understanding macromolecular organization and the emergence of biological function. Discrete atoms and molecules interact to form macromolecules and even larger mesoscale assemblies, ultimately yielding macroscopic structures and properties. A quantitative relationship between the nanoscale discrete interactions and the macroscale properties is required to design, optimize, and control such systems; yet in many applications, predictive models do not exist or are computationally intractable.

The Grover group is dedicated to the development of tractable and practical approaches for the engineering of macroscale behavior via explicit consideration of molecular and atomic scale interactions. We focus on applications involving the kinetics of self-assembly, specifically those in which methods from non-equilibrium statistical mechanics do not provide closed form solutions. General approaches employed include stochastic modeling, model reduction, machine learning, experimental design, robust parameter design, and estimation.

Omar I. Asensio is an Associate Professor in the Jimmy and Rosalynn Carter School of Public Policy and the Director of the Data Science & Policy Lab at Georgia Tech. During the 2023-2024 academic year, he was a fellow at the Institute for Business in Global Society at Harvard Business School. Professor Asensio’s research focuses on climate and electrification strategies at the intersection of technology, AI, and sustainability. He employs large-scale data, field experiments, and human-in-the-loop AI systems to address innovation challenges in energy systems, transportation, and human mobility. He contributed to the zero emission vehicles (ZEV) policy guidance for COP26 and the Glasgow Climate Pact.

Prof. Asensio is a member of the U.S. National Academies of Sciences, Engineering, and Medicine (NASEM) New Voices 2021 cohort, which recognizes early- to-mid career leaders for exceptional contributions to science, engineering and medicine. He is a two-time former chair of the Natural Resource, Energy, and Environmental Policy section of APPAM, and is the recipient of the 2023 Faculty Excellence in Research Award from the Ivan Allen College. At Georgia Tech, he is a Brook Byers Institute for Sustainable Systems (BBISS) Fellow and a faculty affiliate of the Institute for Data Engineering & Science (IDEaS), the Machine Learning Center, and the Strategic Energy Institute (SEI).

Professor Asensio has received multiple awards for his research, including the National Science Foundation CAREER Award, the Alliance for Research on Corporate Sustainability (ARCS) Emerging Scholar Award, and the Research Impact on Practice Award (RIPA) from the Academy of Management’s Organizations & the Natural Environment Division (ONE-NBS). His work has been published in leading journals such as Nature Energy, Nature Sustainability, and PNAS. 

Professor Asensio’s research and teaching have been supported by awards from the National Science Foundation, Microsoft, ESRI, the U.S. State Department’s Diplomacy Lab, and the U.S. Department of Energy. His work has informed policy advisory communications for the U.S. National Academy of Sciences, the UK government, the United Nations Economic Commission for Latin America and the Caribbean, and the IndiaAI initiative. His research has been featured in popular press, including Bloomberg, Scientific American, Motor Trend, Fast Company, NPR’s All Things Considered, Yahoo! News, The Huffington Post, and the Washington Post.

Dr. Asensio serves as Associate Editor of Data & Policy journal published by Cambridge University Press. He earned his doctorate in Environmental Science & Engineering with specialties in Economics from UCLA.

Tom Conte holds a joint appointment in the Schools of Electrical & Computer Engineering and Computer Science at the Georgia Institute of Technology. He is the founding director of the Center for Research into Novel Computing Hierarchies (CRNCH). His research is in the areas of computer architecture and compiler optimization, with emphasis on manycore architectures, microprocessor architectures, back-end compiler code generation, architectural performance evaluation and embedded computer system architectures.