Daniel Alexander is the Director of the UCL Centre for Medical Image Computing (CMIC) at University College London (UCL) and Professor of Imaging Science in UCL’s Department of Computer Science. His expertise is in computational modelling, machine learning, imaging and image analysis. He has a BA in Mathematics from the University of Oxford (1993), an MSc in Computer Science from UCL (1994), and a PhD in Computer Science from UCL (1998). He has worked as a post-doc at the University of Pennsylvania until 2000 when he returned to London to take up an academic position. He became full professor in 2009, Director of CMIC in 2015, and senior fellow of the ISMRM in 2017.

Dr. Calhoun is 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 950 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. Dr. 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.

Yonina Eldar is a Professor in the Department of Mathematics and Computer Science, Weizmann Institute of Science, Rehovot, Israel, where the heads the center for biomedical engineering. She was previously a Professor in the Department of Electrical Engineering at the Technion, where she held the Edwards Chair in Engineering. She is also a Visiting Professor at MIT, a Visiting Scientist at the Broad Institute, and an Adjunct Professor at Duke University and was a Visiting Professor at Stanford. She received the B.Sc. degree in physics and the B.Sc. degree in electrical engineering both from Tel-Aviv University (TAU), Tel-Aviv, Israel, in 1995 and 1996, respectively, and the Ph.D. degree in electrical engineering and computer science from the Massachusetts Institute of Technology (MIT), Cambridge, in 2002. She is a member of the Israel Academy of Sciences and Humanities, an IEEE Fellow and a EURASIP Fellow. She has received many awards for excellence in research and teaching, including the IEEE Signal Processing Society Technical Achievement Award (2013), the IEEE/AESS Fred Nathanson Memorial Radar Award (2014) and the IEEE Kiyo Tomiyasu Award (2016). She was a Horev Fellow of the Leaders in Science and Technology program at the Technion and an Alon Fellow. She received the Michael Bruno Memorial Award from the Rothschild Foundation, the Weizmann Prize for Exact Sciences, the Wolf Foundation Krill Prize for Excellence in Scientific Research, the Henry Taub Prize for Excellence in Research (twice), the Hershel Rich Innovation Award (three times), the Award for Women with Distinguished Contributions, the Andre and Bella Meyer Lectureship, the Career Development Chair at the Technion, the Muriel & David Jacknow Award for Excellence in Teaching, and the Technion’s Award for Excellence in Teaching (two times). She received several best paper awards and best demo awards together with her research students and colleagues, was selected as one of the 50 most influential women in Israel, and was a member of the Israel Committee for Higher Education. She is the Editor in Chief of Foundations and Trends in Signal Processing and a member of several IEEE Technical Committees and Award Committees.

Sushmita Mitra is a full professor at the Machine Intelligence Unit (MIU), Indian Statistical Institute, Kolkata. From 1992 to 1994 she was in the RWTH, Aachen, Germany as a DAAD Fellow. She was a Visiting Professor in the Computer Science Departments of the University of Alberta, Edmonton, Canada; Meiji University, Japan; and Aalborg University Esbjerg, Denmark. Dr. Mitra received the National Talent Search Scholarship (1978-1983) from NCERT, India, the University Gold Medal in 1988, the IEEE TNN Outstanding Paper Award in 1994 for her pioneering work in neuro-fuzzy computing, the CIMPA-INRIA-UNESCO Fellowship in 1996, and Fulbright-Nehru Senior Research Fellowship in 2018-2020. She was the INAE Chair Professor during 2018-2020. Dr. Mitra has been awarded the prestigious J. C. Bose National Fellowship, 2021.

Dr. Mitra is the author of the books “Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing” and “Data Mining: Multimedia, Soft Computing, and Bioinformatics” published by John Wiley, and “Introduction to Machine Learning and Bioinformatics”, Chapman & Hall/CRC Press, beside a host of other edited books. Dr. Mitra has guest edited special issues of several journals, is an Associate Editor of “IEEE/ACM Trans. on Computational Biology and Bioinformatics”, “Information Sciences”, “Neurocomputing”, “Fundamenta Informatica”, “Computers in Biology and Medicine”, SN Computer Sciences and is a Founding Associate Editor of “Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery (WIRE DMKD)”. She has more than 150 research publications in referred international journals. According to the Stanford List, Dr. Mitra is ranked among the top 2% scientists worldwide in the domain of Artificial Intelligence and Image Processing.

Dr. Mitra is a Fellow of the IEEE, The World Academy of Sciences (TWAS), Indian National Science Academy (INSA), International Association for Pattern Recognition (IAPR), and Fellow of the Indian National Academy of Engineering (INAE) and The National Academy of Sciences, India (NASI). She is an IEEE CIS Distinguished Lecturer, Member of Inter-Academy Panel Panel for Women in STEMM, and the current Chair, IEEE Kolkata Section. She has visited more than 30 countries as a Plenary/Invited Speaker or an academic visitor. She served in the capacity of Program Chair, Tutorial Chair, and as member of programme committees of many international conferences. Her current research interests include data science, pattern recognition, soft computing, medical image processing, and Bioinformatics.

Rakesh Mullick is the Chief Scientist in the Advanced Technology Group, Edison AI, as part of GE Healthcare Digital Platform and Solutions. As AI methods make deepening inroads into the healthcare eco-system, Rakesh leads the way working closely with GE Healthcare Advanced Technology Strategy & Product teams to co-create analytics solutions for numerous problems enabling autonomous multi-modal and upstream AI solutions for clinical decision support, image synthesis, signal analysis, quantitative imaging, and accelerated workflows supporting the vision of precision health.

Rakesh has filed over 50 patents, an author on over 120 Journal and Conference Papers, recipient of multiple awards in GE, and an invited speaker to multiple forums. He is a Six Sigma Black Belt and certified TRIZ practitioner. Prior to joining GE, Rakesh was a Research Fellow at the Diagnostic Radiology Department, Clinical Center, National Institutes of Health (NIH) (1999-2000) and Senior Scientist at the Center for Information enhanced Medicine (CieMed), a Joint Research Collaboration between National University of Singapore, Johns Hopkins University, NIH and Intel Corporation. Rakesh obtained his Ph.D. from the Graphics, Visualization and Usability (GVU) Center at Georgia Institute of Technology, Atlanta, GA, USA and his B.S. in Electrical Engineering from the University of Rochester, NY, USA.

Ronald M. Summers, M.D., Ph.D. is a tenured Senior Investigator and Staff Radiologist in the Radiology and Imaging Sciences Department at the NIH Clinical Center in Bethesda, MD. He is a Fellow of the Society of Abdominal Radiologists and of the American Institute for Medical and Biological Engineering. His awards include the Presidential Early Career Award for Scientists and Engineers, the NIH Director’s Award, and the NIH Clinical Center Director’s Award. He is a member of the editorial boards of the Journal of Medical Imaging, Radiology: Artificial Intelligence and Academic Radiology and a past member of the editorial board of Radiology. He was Co-Chair of the 2018 and 2019 SPIE Medical Imaging conferences and Program Co-Chair of the 2018 IEEE ISBI symposium. He has co-authored over 500 journal, review and conference proceedings articles and is a co-inventor on 14 patents. His research interests include abdominal imaging, large radiology image databases, and artificial intelligence.