Keynotes

Rebecca Richards-Kortum

Rice University, USA

Optical Imaging and Computational Microscopy to Improve Early Cancer Detection and Prevention in Low-Resource Settings

Monday | April 14, 2025 | 18:00 – 19:00

Biography: Rebecca Richards-Kortum is the Malcolm Gillis University Professor and member of the Department of Bioengineering at Rice University. After receiving a B.S. in Physics and Mathematics from the University of Nebraska-Lincoln in 1985, she continued her graduate work at the Massachusetts Institute of Technology, where she received a PhD in Medical Physics in 1990. She joined the faculty in Bioengineering at Rice University in 2005 and served as Chair of Bioengineering from 2005-2008 and 2012-2014.

She was named a Howard Hughes Medical Institute Professor in 2002 and 2006, and is an elected member of the US National Academy of Engineering, US National Academy of Sciences, the US National Academy of Inventors, the American Academy of Arts and Sciences, and the American Philosophical Society. She is a recipient of a MacArthur Foundation Fellowship.

Dr. Richards-Kortum’s group is developing imaging systems to enable better screening for oral, esophageal, and cervical cancer at the point-of-care in low-resource settings; novel, low-cost sensors to detect infectious diseases at the point-of-care; and technologies to improve neonatal care in low-resource settings.

Berkman Sahiner

ARPA-H, USA

Revolutionizing Health Research: Insights from ARPA-H Programs

Tuesday | April 15, 2025 | 8:00 – 9:00

Abstract: ARPA-H is a relatively new funding agency under US Health and Human Services that generally funds outcome-based contracts with accelerated award timelines. In this presentation, I will describe the unique role that ARPA-H plays in jumpstarting innovation in areas where there is a significant and unmet need. I will also share insights from ongoing or newly launched programs related to biomedical imaging, and outline opportunities for the involvement of the biomedical imaging community.

Biography: Berkman Sahiner joined ARPA-H in April 2024 after spending 15 years as a Senior Biomedical Research Scientist at the US Food and Drug Administration (FDA). In the FDA Division of Imaging, Diagnostics and Software Reliability, he performed research and developed tools for the evaluation of medical imaging devices and devices incorporating artificial intelligence. At ARPA-H, he is acting as a Program Manager and currently leads programs in the intersection of medical imaging and AI. His research interests include medical imaging, machine learning, computerized image analysis, and performance assessment methodology.

Berkman earned a Ph.D. in Electrical Engineering and Computer Science from the University of Michigan and completed post-doctoral training in radiology at the same university. He was also an Associate Professor at the University of Michigan’s medical school and has published over 140 peer-reviewed research papers in topics ranging from machine learning to clinical study design.

Rama Chellappa

Johns Hopkins University, USA

Problems and Partial Solutions in Medicine AI

Tuesday | April 15, 2025 | 14:00 – 15:00

Abstract: Despite impressive advances in computer vision and medical imaging, owing to the reemergence of deep learning/AI methods, two basic questions remain unanswered. Will deep learning/AI methods work everywhere? Will they work for everyone? These two questions can be decomposed into the following problems that need attention, especially in medicine AI. These include domain adaptation and generalization, bias detection and mitigation, the effectiveness of self-supervised learning, the fidelity and veracity of synthetic data, selecting the best subsets of training data, robust methods for handling adversarial attacks, federated learning, and performance guarantees for hierarchical, non-linear regression models,. In this talk, I will discuss these problems and present partial solutions to them.

Biography: Prof. Rama Chellappa is a Bloomberg Distinguished Professor Computer Vision and Artificial Intelligence in the Departments of Electrical and Computer Engineering (ECE) in the Whiting School of Engineering and Biomedical Engineering in the School of Medicine at Johns Hopkins University (JHU). At Hopkins, he is serving as an interim co-Director of the Data Science and Artificial Intelligence Institute, and is affiliated with CIS, CLSP, IAA and MINDS. He also holds the non-tenured position as a College Park Professor in the ECE department at the University of Maryland. His research interests are in artificial intelligence, computer vision, machine learning, medical imaging and pattern recognition. He received the 2012 K. S. Fu Prize from the International Association of Pattern Recognition (IAPR). He is a recipient of the Society, Technical Achievement, and Meritorious Service Awards from the IEEE Signal Processing Society, the Technical Achievement and Meritorious Service Awards from the IEEE Computer Society and the Inaugural Leadership Award from the IEEE Biometrics Council. He received the 2020 IEEE Jack S. Kilby Medal for Signal Processing, the 2023 IEEE Computer Society Pattern Analysis and Machine Intelligence Distinguished Researcher Award, and the 2024 Edwin H. Land Medal from Optica (formerly Optical Society of America). He is a member of the National Academy of Engineering and a Foreign Fellow of the Indian National Academy of Engineering. He has been recognized as a Distinguished Alumni by the ECE department at Purdue University and the Indian Institute of Science. He is a Fellow of AAAI, AAAS, ACM, AIMBE, IAPR, IEEE, NAI, OSA, and the Washington Academy of Sciences and holds nine patents.

Martin Pomper

University of Texas Southwestern Medical Center, USA

Precision Imaging

Wednesday | April 16, 2025 | 11:00 – 12:00

Abstract: One often considers precision medicine as a genetic phenomenon, whereby a patient’s genome or epigenome may determine what specific treatment would be of particular benefit to them. However, the genetics merely provides on-the-ground intelligence about the patient. Similarly, precision imaging leverages specific cellular targets, unique to the patient, but also provides spatial information that enables construction of guided missiles that might remove the offending lesions, such as through molecular radiotherapy, also known as “theranostics.” In that context, theranostics are agents that are used both to confirm the presence of target within the patient and then, by switching from the imaging to a therapeutic isotope, treating the target lesions with particulate radiation. We will discuss what is becoming a classic target among theranostics, namely, the prostate-specific membrane antigen (PSMA), and the development of precision imaging and therapeutic agents to leverage it in the treatment of prostate and potentially other cancers. The discussion will serve as an introduction to the field and provide a model for how new agents may be introduced to treat a wide variety of malignancies.

Biography: Martin Pomper is Professor and Chair of Radiology at the University of Texas Southwestern Medical Center. He received undergraduate, graduate (organic chemistry) and medical degrees from the University of Illinois at Urbana-Champaign. Postgraduate medical training was at Johns Hopkins University, including internship on the Osler Medical Service, residencies in diagnostic radiology and nuclear medicine and a fellowship in neuroradiology. His interest is in the development of new imaging and therapeutic agents for cancer, central nervous system disease, and other disorders.

Jayashree Kalpathy-Cramer

University of Colorado (CU) School of Medicine, USA

AI in Ophthalmology, Radiology and Oncology – Opportunities and Challenges

Thursday | April 17, 2025 | 11:00 – 12:00

Abstract: AI, particularly deep learning, has the potential to revolutionize healthcare, especially in those areas where imaging plays an important part of the patient’s journey. This talk will showcase recent applications of these technologies to clinical questions in radiology, oncology, and ophthalmology that highlight the promise. Despite these impressive developments, the adoption of such tools in routine clinical practice remains limited. We will explore the challenges of transitioning algorithms from the lab to widespread deployment and discuss strategies to address these barriers.

Biography: Jayashree Kalpathy-Cramer is the endowed chair in Ophthalmic data sciences and the founding chief of the Division of Artificial Medical Intelligence in the Department of Ophthalmology at the University of Colorado (CU) School of Medicine. She is also the Director for Health Informatics at the Colorado Clinical and Translational Sciences Institute. She leads the development and translation of novel artificial intelligence (AI) methods into effective patient care practices at the Sue Anschutz-Rodgers Eye Center. Her research interests span the spectrum from novel algorithm development to clinical development. She is passionate about the potential that machine learning and artificial intelligence have to improve the access and the quality of healthcare in the US and worldwide. She graduated from IIT Bombay, India, with a degree in electrical engineering and received her PhD from Rensselaer Polytechnic Institute, also in the Electrical Engineering. Dr. Kalpathy-Cramer spent almost a decade in the semiconductor industry before a pivot to academia and healthcare. She has co-authored over 250 peer-reviewed publications, has written over a dozen book chapters and is a co-inventor on 15 patents.