Keynote Speakers of MICAD 2025

Prof. Junzhou Huang

The University of Texas at Arlington, United States
FAIMBE
Jenkins Garrett Professor

Dr. Junzhou Huang is the Jenkins Garrett Professor in the Computer Science and Engineering department at the University of Texas at Arlington. His major research interests include machine learning, computer vision, medical image analysis and bioinformatics. His research has been recognized by several awards including the NSF CAREER Award, Google TensorFlow Model Garden Award, Microsoft Accelerate Foundation Models Research Award, four Best Paper Awards (MICCAI'10, FIMH'11, STMI'12 and MICCAI'15) as well as two Best Paper Nominations (MICCAI'11 and MICCAI'14). His research projects are supported by both federal/state agencies (NSF, NIH, CPRIT) and industry (Google, Amazon, Microsoft, IBM, Samsung, XtaiPi, Nokia and Johnson & Johnson). He enjoys to develop efficient algorithms with nice theoretical guarantees to solve practical problems involved large scale data.

Prof. Yiyu Shi

University of Notre Dame, United States

Dr. Yiyu Shi is currently a professor in the Department of Computer Science and Engineering at the University of Notre Dame, the site director of National Science Foundation I/UCRC Alternative and Sustainable Intelligent Computing, and the director of the Sustainable Computing Lab (SCL). He is also a visiting scientist at Boston Children’s Hospital, the primary pediatric program of Harvard Medical School. He received his B.S. in Electronic Engineering from Tsinghua University, Beijing, China in 2005, the M.S and Ph.D. degree in Electrical Engineering from the University of California, Los Angeles in 2007 and 2009 respectively. His current research interests focus on hardware intelligence and biomedical applications. In recognition of his research, more than a dozen of his papers have been nominated for or awarded as the best paper in top journals and conferences, including the 2021 IEEE Transactions on Computer-Aided Design Donald O Pederson Best Paper Award. He is also the recipient of Facebook Research Award, IBM Invention Achievement Award, Japan Society for the Promotion of Science (JSPS) Faculty Invitation Fellowship, Humboldt Research Fellowship, IEEE St. Louis Section Outstanding Educator Award, Academy of Science (St. Louis) Innovation Award, Missouri S&T Faculty Excellence Award, NSF CAREER Award, IEEE Region 5 Outstanding Individual Achievement Award, the Air Force Summer Faculty Fellowship, and IEEE Computer Society Mid-Career Research Achievement Award. He has served on the technical program committee of many international conferences. He is the deputy editor-in-chief of IEEE VLSI CAS Newsletter, and an associate editor of various IEEE and ACM journals. He is an IEEE CEDA distinguished lecturer and an ACM distinguished speaker.

Prof. Tom Vercauteren

King's College London, UK

Tom Vercauteren is Professor of Interventional Image Computing at King’s College London since 2018. He is also co-founder and Chief Scientific Officer of Hypervision Surgical, a spin-out company focusing on intraoperative hyperspectral imaging. From 2018-2023, he held the Medtronic / Royal Academy of Engineering Research Chair in Machine Learning for Computer-assisted Neurosurgery at King’s. From 2014 to 2018, he was Associate Professor at UCL where he acted as Deputy Director for the Wellcome / EPSRC Centre for Interventional and Surgical Sciences (2017-18).
From 2004 to 2014, he worked for Mauna Kea Technologies, Paris where he led the research and development team designing image computing solutions for the company’s CE-marked and FDA-cleared optical biopsy device. His work is now used in hundreds of hospitals worldwide. He is a Columbia University and Ecole Polytechnique graduate and obtained his PhD from Inria in 2008. Tom is also an established open-source software supporter.
Tom Vercauteren's research focuses on translational medical image computing, machine learning and interventional imaging devices with a specific interest in their development for surgery and interventional sciences.