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.

Kamran Paynabar is the Fouts Family Early Career Professor and Associate Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. He received his B.Sc. and M.Sc. in Industrial Engineering from Iran in 2002 and 2004, respectively, and his Ph.D. in Industrial and Operations Engineering from The University of Michigan in 2012. He also holds an M.A. in Statistics from The University of Michigan. His research interests comprise both applied and methodological aspects of machine-learning and statistical modeling integrated with engineering principles. He is a recipient of the INFORMS Data Mining Best Student Paper Award, the Best Application Paper Award from IIE Transactions, the Best QSR refereed paper from INFORMS, and the Best Paper Award from POMS. He has been recognized with the Georgia Tech campus level 2014 CETL/BP Junior Faculty Teaching Excellence Award and the Provost Teaching and Learning Fellowship. He served as the chair of QSR of INFORMS, and the president of QCRE of IISE.

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.

We strive to innovate in ways that both advance the imaging science and also impact biological and translational research. We are particularly interested in new imaging physics, bottom-up opto-electronic system design, as well as new principles for light propagation, light-matter interaction and image formation in complex biological materials, especially at the single-molecule level. Toward the application end, we have expertise in a wide range of imaging instrumentation and techniques, such as super-resolution, adaptive optics, light-field, miniaturized, light-sheet, computational microscopy and endoscopy.

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).

Shaheen Azim Dewji, Ph.D., (she/her/hers) is an Assistant Professor in the Nuclear & Radiological Engineering and Medical Physics Programs at the Georgia Institute of Technology, where she leads the Radiological Engineering, Detection, and Dosimetry (RED²) research group. Dewji joined Georgia Tech following three years as faculty at Texas A&M University in the Department of Nuclear Engineering, and as a Faculty Fellow of the Center for Nuclear Security Science and Policy Initiatives (NSSPI). In her prior role at Oak Ridge National Laboratory, where she remained for almost 9 years, Dewji was Radiological Scientist in the Center for Radiation Protection Knowledge. Her research interests include development of dose coefficients, shielding design, and nuclear material detection assay using gamma-ray spectroscopy. Her recent work has focused on associated challenges in uncertainty quantification in dose estimation/reconstruction associated with the external exposure and internal uptake of radionuclides associated with applications of emergency response, defense, nuclear medicine, and occupational/public safety using Monte Carlo radiation transport codes and internal dose modeling. Dewji completed her Masters and Ph.D. degrees in Nuclear and Radiological Engineering at the Georgia Institute of Technology in Atlanta, GA and was a fellow of the Sam Nunn Security Program. She received her Bachelor of Science in Physics from the University of British Columbia. Dewji currently serves on the National Academies of Science, Engineering, and Medicine – Nuclear and Radiation Studies Board and is a member of the Board of Directors for both the American Nuclear Society and Health Physics Society.
   

Christopher E. Carr is an engineer/scientist with training in aero/astro, electrical engineering, medical physics, and molecular biology. At Georgia Tech he is an Assistant Professor in the Daniel Guggenheim School of Aerospace Engineering with a secondary appointment in the School of Earth and Atmospheric Sciences. He is a member of the Space Systems Design Lab (SSDL) and runs the Planetary eXploration Lab (PXL). He serves as the Principal Investigator (PI) or Science PI for several life detection instrument and/or astrobiology/space biology projects, and is broadly interested in searching for and expanding the presence of life beyond Earth while enabling a sustainable human future. He previously served as a Research Scientist at MIT in the Department of Earth, Atmospheric and Planetary Sciences and a Research Fellow at the Massachusetts General Hospital in the Department of Molecular Biology. He serves as a Scott M. Johnson Fellow in the U.S. Japan Leadership Program.

Dr. Bhasin's laboratory has developed strategies for analysis of transcriptome, epigenome, and proteomics data to perform multi-scale modeling of interaction among different cells molecular level and to identify novel biomarkers. He and his team are currently focusing on developing novel single-cell omics approaches to understand disease heterogeneity and the impact of treatments at single-cell resolution. He is involved in developing approaches for the analysis of multi-dimensional single-cell data by developing innovative approaches for single-cell sparsity, batch correction, annotation, and integration. Using these approaches, his group is working toward understanding: 1. Understanding heterogeneity and relapse mechanisms in pediatric hematological malignancies 2. Understanding heterogeneity and progression in multiple myeloma. 3. Development of molecular diagnostics platforms for cancer diagnosis and prognosis 4. Identification of biomarkers for early detection of pancreatic cancer, glioblastoma, and colon cancer 5. Artificial intelligence-based histopathology and radiology cancer image analysis approaches 6. Single-cell Atlas for Pediatric Cancers Additionally, our group is also developing Biomarkers associated with impaired healing of Diabetic Foot Ulcers using single-cell profiling and deep learning-driven wound image analysis. We are working collaboratively to develop innovative genomics and clinical data-driven drug repurposing approaches.

Amirali Aghazadeh is an Assistant Professor in the School of Electrical and Computer Engineering and also program faculty of Machine Learning, Bioinformatics, and Bioengineering Ph.D. programs. He has affiliations with the Institute for Data Engineering and Science (IDEAS) and Institute for Bioengineering and Biosciences. Before joining Georgia Tech, Aghazaeh was a postdoc at Stanford and UC Berkeley and completed his Ph.D. at Rice University. His research focuses on developing machine learning and deep learning solutions for protein and small molecular design and engineering.
 

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.