Colton's research interests are in the areas of design and manufacturing, focusing on polymers and polymer composites. Processing techniques, such as micro-molding, injection molding, filament winding, resin transfer molding and the like, are studied and used to fabricate these devices and products, such as smart composite structures.

The design of processing techniques and equipment for metamaterials also are being studied with applications being dielectric materials for electromagnetic applications. Due to the small-scale physics associated with their engineering, nano-scale metamaterials exhibit superior properties and enhanced performance.

Colton has a strong passion for the application of engineering for the common good – "humanitarian design and engineering" and "design that matters," - such as in developing countries and other resource limited environments. To be successful, multidisciplinary teams must work together to produce products that function as well as delight, that exceed customer's expectations, regardless of where the product is used. Along these lines, product design and role that the interactions between engineering and industrial design forms another research interest.

Yue Chen is an assistant professor in the Department of Biomedical Engineering, GT/Emory. He received his Ph.D. degree in Mechanical Engineering from Vanderbilt University, M.S. in Mechanical Engineering from Hong Kong Polytechnic University, and a B.S. in Vehicle Engineering from Hunan University. His research focused on designing, modeling, and control of continuum robots and apply them in medicine.

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.

Vince Calhoun, Ph.D., is the founding director of the tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) where he holds appointments at Georgia State, Georgia Tech and Emory. He is the author of more than 900 full journal articles. His work includes the development of flexible methods to analyze neuroimaging data including blind source separation, deep learning, multimodal fusion and genomics, neuroinformatics tools. Calhoun is a fellow of the Institute of Electrical and Electronic Engineers, The American Association for the Advancement of Science, The American Institute of Biomedical and Medical Engineers, The American College of Neuropsychopharmacology, The Organization for Human Brain Mapping (OHBM) and the International Society of Magnetic Resonance in Medicine. He currently serves on the IEEE BISP Technical Committee and is also a member of IEEE Data Science Initiative Steering Committee as well as the IEEE Brain Technical Committee.

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.

David V. Anderson received the B.S and M.S. degrees from Brigham Young University and the Ph.D. degree from Georgia Institute of Technology (Georgia Tech) in 1993, 1994, and 1999, respectively. He is currently a professor in the School of Electrical and Computer Engineering at Georgia Tech. Anderson's research interests include audio and psycho-acoustics, machine learning and signal processing in the context of human auditory characteristics, and the real-time application of such techniques. His research has included the development of a digital hearing aid algorithm that has now been made into a successful commercial product. Anderson was awarded the National Science Foundation CAREER Award for excellence as a young educator and researcher in 2004 and the Presidential Early Career Award for Scientists and Engineers in the same year. He has over 150 technical publications and 8 patents/patents pending. Anderson is a senior member of the IEEE, and a member the Acoustical Society of America, and Tau Beta Pi. He has been actively involved in the

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.