Dr. Aidun joined the Woodruff School as a Professor in 2003 after completion of a two-year period as program director at the National Science Foundation. He began at Tech in 1988 as an Assistant Professor at the Institute of Paper Science and Technology. Prior, he was a research Scientist at Battelle Research Laboratories, Postdoctoral Associate at Cornell University and Senior Research Consultant at the National Science Foundation's Supercomputer Center at Cornell. 

Dr. Aidun's research is at the intersection between fundamentals of the physics of complex fluids/thermal transport and applications to engineering and biotransport. He has a diverse research portfolio in fluid mechanics, bioengineering, renewable bioproducts and decarbonization of industrial processes. 

A major focus has been to understand the physics of blood cell transport and interaction with glycoproteins (e.g., vWF) with applications to cardiovascular diseases.

Prof. AlRegib is currently the John and Marilu McCarty Chair Professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. His group is the Omni Lab for Intelligent Visual Engineering and Science (OLIVES) at Georgia Tech. In 2012, he was named the Director of Georgia Tech’s Center for Energy and Geo Processing (CeGP). He is the director of the Center for Signal and Information Processing (CSIP). He also served as the Director of Georgia Tech’s Initiatives and Programs in MENA between 2015 and 2018. He has authored and co-authored more than 300 articles in international journals and conference proceedings. He has been issued several U.S. patents and invention disclosures. He is a Fellow of the IEEE.

Prof. AlRegib received the ECE Outstanding Graduate Teaching Award in 2001 and both the CSIP Research and the CSIP Service Awards in 2003. In 2008, he received the ECE Outstanding Junior Faculty Member Award. In 2017, he received the 2017 Denning Faculty Award for Global Engagement. He and his students received the Beat Paper Award in ICIP 2019. He received the 2024 ECE Distinguished Faculty Achievement Award at Georgia Tech. He and his students received the Best Paper Award in ICIP 2019 and the 2023 EURASIP Best Paper Award for Image communication Journal.

Prof. AlRegib participated in a number of activities. He has served as Technical Program co-Chair for ICIP 2020 and ICIP 2024. He served two terms as a member of the IEEE SPS Technical Committees on Multimedia Signal Processing (MMSP) and Image, Video, and Multidimensional Signal Processing (IVMSP), 2015-2017 and 2018-2020. He was a member of the Editorial Boards of both the IEEE Transactions on Image Processing (TIP), 2009-2022, and the Elsevier Journal Signal Processing: Image Communications, 2014-2022. He was a member of the editorial board of the Wireless Networks Journal (WiNET), 2009-2016 and the IEEE Transaction on Circuits and Systems for Video Technology (CSVT), 2014-2016. He was an Area Chair for ICME 2016/17 and the Tutorial Chair for ICIP 2016. He served as the chair of the Special Sessions Program at ICIP’06, the area editor for Columns and Forums in the IEEE Signal Processing Magazine (SPM), 2009–12, the associate editor for IEEE SPM, 2007-09, the Tutorials co-chair in ICIP’09, a guest editor for IEEE J-STSP, 2012, a track chair in ICME’11, the co-chair of the IEEE MMTC Interest Group on 3D Rendering, Processing, and Communications, 2010-12, the chair of the Speech and Video Processing Track at Asilomar 2012, and the Technical Program co-Chair of IEEE GlobalSIP, 2014. He lead a team that organized the IEEE VIP Cup, 2017 and the 2023 IEEEE VIP Cup. He delivered short courses and several tutorials at international events such as BigData, NeurIPS, ICIP, ICME, CVPR, AAAI, and WACV.

In the Omni Lab for Intelligent Visual Engineering and Science (OLIVES), he and his group work on robust and interpretable machine learning algorithms, uncertainty and trust, and human in the loop algorithms. The group studies interventions into AI systems to enhance their trustworthiness. The group has demonstrated their work on a wide range of applications such as Autonomous Systems, Medical Imaging, and Subsurface Imaging. The group is interested in advancing the fundamentals as well as the deployment of such systems in real-world scenarios. His research group is working on projects related to machine learning, image and video processing, image and video understanding, subsurface imaging, perception in visual data processing, healthcare intelligence, and video analytics. The primary applications of the research span from Autonomous Vehicles to Portable AI-based Ophthalmology and Eye Exam and from Microscopic Imaging to Seismic Interpretation. The group was the first to introduce modern machine learning to seismic interpretation.

In 2024, and after more than three years of continuous work, he co-founded Georgia Tech’s AI Makerspace. The AI Makerspace is a resource for the entire campus community to access AI. Its purpose is to democratize access to AI. Together with his team, they are developing tools and services for the AI Makerspace via a VIP Team called AI Makerspace Nexus. In addition, he created two AI classes from scratch with innovative hands-on exercises using the AI Makerspace. One class is the ECE4252/8803 FunML class (Fundamentals of Machine Learning) where students learn the basics of Machine Learning as well as eight weeks of Deep learning both mathematically and using hands-on exercises on real-world data. The second class is a sophomore-level AI Foundations class (AI First) that teaches any student from any college the basics of AI such as data literacy, learning, decision, planning, and ethics using theory and hands-on exercises on the AI Makerspace. Prof. AlRegib wrote two textbooks for both classes.

Prof. AlRegib has provided services and consultation to several firms, companies, and international educational and R&D organizations. He has been a witness expert in a number of patents infringement cases and Inter Partes Review (IRP) cases.

Greeshma Agasthya (she/her/hers) is an Assistant Professor in the Nuclear & Radiological Engineering and Medical Physics Program at the George W. Woodruff School of Mechanical Engineering at Georgia Institute of Technology. She leads the Computational Medical Physics Laboratory, and her research interests are: (1) developing multiscale digital twins for personalized radiation dosimetry for imaging, therapy, and theranostics, (2) modeling and simulations to assess novel radiation protocols from cancer diagnosis to cancer treatment, and (3) developing AI frameworks to model patient trajectories for early intervention and treatment in oncology.

Previously, she was a research scientist at Oak Ridge National Laboratory in the Advanced Computing for Health Sciences section. Agasthya received her doctorate in Biomedical Engineering from Duke University and completed her postdoctoral training at Emory University's Winship Cancer Institute. She has experience in medical imaging research, modeling and simulation for radiation dosimetry, and AI and Machine learning for healthcare. Agasthya has developed and used multi-scale modeling and simulations of the human body for virtual clinical trials, radiation dosimetry, and optimization of medical imaging systems for cancer applications. She has worked on artificial intelligence (AI) for cancer surveillance, predicting disease outcomes, and clinical decision support. She has collaborated with experts in medical physics, radiology, cardiology, computer engineering, and statistics to tackle interdisciplinary challenges in medical physics and biomedical engineering. She has worked on imaging modalities including neutron imaging, x-ray radiography, computed tomography (CT), and tomosynthesis systems for cancer applications.

Alexander Vlahos is an Assistant Professor in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University. Alexander received his B.S. in Biochemistry from McMaster University and his Ph.D. from the University of Toronto under the supervision of Professor Michael Sefton. His Ph.D. work focused on developing an injectable bioartificial pancreas that could be delivered underneath the skin. He then transitioned to mammalian synthetic biology, where he conducted his postdoctoral work as an HFSP long-term fellow at Stanford University with Professor Xiaojing Gao.

His research integrates principles from synthetic biology, protein engineering, and tissue engineering to develop synthetic protein circuits for mammalian cellular engineering. The Vlahos lab synergizes synthetic biology and tissue engineering to create programmable gene and cell therapies for biomedical applications in regenerative medicine, cancer, and autoimmune disease. His lab has three main research themes, including 1) generating protein sensors to sense changes in internal cell states or the external microenvironment, 2) programming engineered cells to model cell-to-cell communication and elucidate the dynamics and expression of key signals that govern fibrosis and immune rejection, and 3) applying synthetic protein circuits to modulate the immune system and improve cell transplantation.

Justin Kim is an Associate Professor in the School of Chemistry and Biochemistry. He received his A.B. in Chemistry and Physics and an A.M. in Chemistry from Harvard College in 2003 then received his Ph.D. in Organic Chemistry from the Massachusetts Institute of Technology in 2013. After a postdoctoral fellowship as a Miller Institute Fellow at UC Berkeley and at Stanford University, he joined the faculty of the Department of Cancer Biology at Dana-Farber Cancer Institute and the Department of Biological Chemistry and Molecular Pharmacology at Harvard Medical School in 2016 as an Assistant Professor. He later joined the faculty at Georgia Tech in 2024. He is the recipient of the NIH Director’s New Innovator Award (2018), Thieme Chemistry Journal Award (2021), and the NSF CAREER Award (2023). Professor Kim’s research program is defined by the development of biologically relevant reactions for use in chemistry, biology, and materials science. His primary research interests are in expanding the functional repertoire of bioorthogonal chemistry, specifically exploring new bond-forming and breaking methods that enable platforms for discovering and targeting small molecule-protein and protein-protein interactions as well as for creating functionally dynamic biomaterials.

Julie Champion is the William R. McLain Endowed Term Professor in the School of Chemical and Biomolecular Engineering at Georgia Institute of Technology. She earned her B.S.E. in chemical engineering from the University of Michigan and Ph.D. in chemical engineering at the University of California Santa Barbara. She was an NIH postdoctoral fellow at the California Institute of Technology. Champion is a fellow of the American Institute for Medical and Biological Engineering and has received awards including American Chemical Society Women Chemists Committee Rising Star, NSF BRIGE Award, Georgia Tech Women in Engineering Faculty Award for Excellence in Teaching, Georgia Tech BioEngineering Program Outstanding Advisor Award. Professor Champion’s current research focuses on design and self-assembly of functional nanomaterials made from engineered proteins for applications in immunology, cancer, and biocatalysis.

Dr. Borodovsky and his group develop machine learning algorithms for computational analysis of biological sequences: DNA, RNA and proteins. Our primary focus is on prediction of protein-coding genes and regulatory sites in genomic DNA. Probabilistic models play an important role in the algorithm framework, given the probabilistic nature of biological sequence evolution.

Jaydev P. Desai, Ph.D, is currently a Professor and BME Distinguished Faculty Fellow in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech. Prior to joining Georgia Tech in August 2016, he was a Professor in the Department of Mechanical Engineering at the University of Maryland, College Park (UMCP). He completed his undergraduate studies from the Indian Institute of Technology, Bombay, India, in 1993. He received his M.A. in Mathematics in 1997, M.S. and Ph.D. in Mechanical Engineering and Applied Mechanics in 1995 and 1998 respectively, all from the University of Pennsylvania. He was also a Post-Doctoral Fellow in the Division of Engineering and Applied Sciences at Harvard University. He is a recipient of several NIH R01 grants, NSF CAREER award, and was also the lead inventor on the "Outstanding Invention of 2007 in Physical Science Category" at the University of Maryland, College Park. He is also the recipient of the Ralph R. Teetor Educational Award. In 2011, he was an invited speaker at the National Academy of Sciences "Distinctive Voices" seminar series on the topic of "Robot-Assisted Neurosurgery" at the Beckman Center. He was also invited to attend the National Academy of Engineering's 2011 U.S. Frontiers of Engineering Symposium. He has over 150 publications, is the founding Editor-in-Chief of the Journal of Medical Robotics Research, and Editor-in-Chief of the Encyclopedia of Medical Robotics (currently in preparation). His research interests are primarily in the area of image-guided surgical robotics, rehabilitation robotics, cancer diagnosis at the micro-scale, and rehabilitation robotics. He is a Fellow of the ASME and AIMBE.