Munmun De Choudhury is an Associate Professor at the School of Interactive Computing in Georgia Institute of Technology. Dr. De Choudhury is renowned for her groundbreaking contributions to the fields of computational social science, human-computer interaction, and digital mental health. Through fostering interdisciplinary collaborations across academia, industry, and public health sectors, Dr. De Choudhury and her collaborators have contributed significantly to advancing the development of computational techniques for early detection and intervention in mental health, as well as in unpacking how social media use benefits or harms mental well-being. De Choudhury's contributions have been recognized worldwide, with significant scholarly impact evidenced by numerous awards like induction into the SIGCHI Academy and the 2023 SIGCHI Societal Impact Award. Beyond her academic achievements, Dr. De Choudhury is a proactive community leader, a persistent contributor to policy-framing and advocacy initiatives, and is frequently sought for expert advice to governments, and national and international media.

Alex Adams’s research focuses on designing, fabricating, and implementing new ubiquitous and wearable sensing systems. In particular, he is interested in how to develop these systems using equity-driven design principles for healthcare. Alex leverages sensing, signal processing, and fabrication techniques to design, deploy, and evaluate novel sensing technologies.

Originally a musician, Alex became fascinated by how he could capture and manipulate sounds through analog hardware and digital signal processing, which led him back to his hometown (Concord, NC). Alex completed his BS at the University of North Carolina at Charlotte in 2014 and his Ph.D. at Cornell University in 2021 (advised by Professor Tanzeem Choudhury). Alex then became the resident Research Scientist for the Precision Behavioral Health Initiative at Cornell Tech (NYC) until the fall of 2022, when he joined the School of Interactive Computing at the Georgia Institute of Technology. Currently, his research focuses on the equity-driven design and the development of multi-modal sensing systems to simultaneously assess mental and physical health to enable a new class of mobile health technologies.

The effortlessness of moving your body belies the lurking complexity driving it. We are trying to understand how the nervous system makes something so complicated as controlling a human body feel so natural. We use human subjects studies, animal experiments, mathematical biology, and artificial intelligence to understand neural control of movement. New theories and insight promise advances in physical therapy, human-machine collaboration, brain-computer interfaces, neural modulation of peripheral reflexes, and more.

Lynn Kamerlin received her Master of Natural Sciences from the University of Birmingham (UK), in 2002, where she remained to complete a PhD in Theoretical Organic Chemistry under the supervision of Dr. John Wilkie (awarded 2005). Subsequently, she was a postdoctoral researcher in the labs of Stefan Boresch at the University of Vienna (2005-2007), Arieh Warshel at the University of Southern California (2007-2009, Research Associate at the University of Southern California in 2010) and Researcher with Fahmi Himo (2010). She is currently a Professor and Georgia Research Alliance – Vasser Wooley Chair of Molecular Design at Georgia Tech, a Professor of Structural Biology at Uppsala University, a Fellow of the Royal Society of Chemistry. She has also been a Wallenberg Scholar, the recipient of an ERC Starting Independent Researcher Grant (2012-2017) and the Chair of the Young Academy of Europe (YAE) in 2014-2015. Her non-scientific interests include languages (fluent in 5), amateur photography and playing the piano.

Mijin Kim is an assistant professor in the School of Chemistry and Biochemistry at Georgia Tech. Her research program is focused on the development and implementation of novel nanosensor technology to improve cancer research and diagnosis. The Kim Lab combines nanoscale engineering, fluorescence spectroscopy, machine learning approaches, and biochemical tools (1) to understand the exciton photophysics in low-dimensional nanomaterials, (2) to develop diagnostic/nano-omics sensor technology for early disease detection, and (3) to investigate biological processes with focusing problems in lysosome biology and autophagy. For her scientific innovation, Kim has received multiple recognitions, including being named as one of the STAT Wunderkinds and the MIT Technology Review Innovators Under 35 List.

Peter Kasson is an international leader in the study of biological membrane structure, dynamics, and fusion, with particular application to how viruses gain entry to cells. His group performs both high-level experimental and computational work – a powerful combination that is critical to advancing our understanding of this important problem. His publications describe inventive approaches to the measurement of viral fusion rates and characterization of fusion mechanisms, and to the modeling of large-scale biomolecular and lipid assemblies. He has applied these insights to the prediction of pandemic outbreaks and drug resistance, with particular attention to Zika, SARS-CoV-2, and influenza pathogens in recent years. See https://kassonlab.org/ for more information.

Our goal is to contribute to the fundamental understanding of the Earth's biogeochemical cycling in the present and past climate, to conduct research in Ecosystem and Biogeochemistry, Ocean Carbon Cycle, Global Climate Change, and Ocean Deoxygenation using computational modeling, observations and AI/machine learning approaches. 

Anqi Wu is an Assistant Professor at the School of Computational Science and Engineering (CSE), Georgia Institute of Technology. She was a Postdoctoral Research Fellow at the Center for Theoretical Neuroscience, the Zuckerman Mind Brain Behavior Institute, Columbia University. She received her Ph.D. degree in Computational and Quantitative Neuroscience and a graduate certificate in Statistics and Machine Learning from Princeton University. Anqi was selected for the 2018 MIT Rising Star in EECS, 2022 DARPA Riser, and 2023 Alfred P. Sloan Fellow. Her research interest is to develop scientifically-motivated Bayesian statistical models to characterize structure in neural data and behavior data in the interdisciplinary field of machine learning and computational neuroscience. She has a general interest in building data-driven models to promote both animal and human studies in the system and cognitive neuroscience.

Nate Damen is a Research Engineer I with Aerospace, Transportation and Advanced Systems Laboratory of Georgia Tech Research Institute. Damen’s work at ATAS has focused on Mixed Reality applications, robotics, the automation of CAR-T cellular expansions, and bioreactor design. Before joining GTRI, Damen conducted research into the manipulation of textiles with Softwear Automation and the design of deformable parcel manipulation systems with Dorabot. His creative work ATLTVHEAD with the Atlanta Beltline Inc., includes the creation of several wearable electronic systems for remote computing and novel interactions between wearable systems and live user input from those walking the Atlanta Beltline. 

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.