Featured Speakers
3rd Annual
AI for Pediatric Health Symposium
Collaborative Intelligence: Transforming Research for Pediatric Health with AI
About Dr. Annapragada
Ananth Annapragada is professor and vice-chair for Research in Radiology at Texas Children's Hospital and Baylor College of Medicine. He received his Ph.D. in Chemical Engineering from The University of Michigan in 1989. After postdoctoral fellowships at the University of Minnesota and MIT, he joined Abbott Laboratories as a Research Scientist in 1991. In 1996, he joined SEQUUS Pharmaceuticals, Menlo Park, CA and stayed on till it was acquired by Johnson and Johnson. In 2000, he started his first academic position at the Cleveland State University and Cleveland Clinic Foundation. In 2003, he moved to University of Texas and subsequently, joined Texas Children's Hospital in June 2011. Dr. Annapragada's research interests include the development of nanomaterial based solutions to medical and imaging problems, 3d bioprinting, and the applications of AI in medicine.
About Dr. Anwar
Syed Muhammad Anwar is principal investigator at Children’s National Hospital and associate professor of Radiology and Pediatrics at the George Washington University School of Medicine and Health Sciences. Within the hospital, he is associated with the Sheikh Zayed Institute (SZI) for Pediatric Surgical Innovation doing cutting edge research in surgical planning, treatment and device innovation. Prior to this, Dr. Anwar was associated with the University of Engineering and Technology, Taxila as associate professor (tenured) in the Department of Software Engineering and was a Fulbright Research Fellow at the Center for Research in Computer Vision (CRCV) at the University of Central Florida. CRCV is one of the top-ranked computer vision centers in the world. Dr. Anwar's research interests include developing computational & engineering solutions for healthcare systems that benefit from computer vision and artificial intelligence. He has expertise in a wide range of application areas related to machine learning, image processing and biomedical engineering. Dr. Anwar has co-authored more than 100 peer-reviewed articles in leading journals and conferences. He is a member of IEEE and MICCAI societies and has mentored both in academia and industry. He has mentored students in machine learning and computer science at all academic levels and has graduated multiple PhD students. His research has been supported by research grants from various national and international funding agencies and is well-cited. Dr. Anwar has appeared in the Stanford list of top 2% scientists for the year 2021 and 2022. As part of the Precision Medical Imaging lab, Dr. Anwar intends to expand the research and development of AI for improving pediatric healthcare.
About Dr. Gable
Christopher Gable is an emergency pediatrician at Children’s National Hospital and the ED Director of Emergency Mental and Behavioral Health. He is a national authority on emergency mental and behavioral health care, and his research focuses on how policy and care systems impact the quality of care for patients experiencing an emergent mental or behavioral health issue, especially during times of crisis and acute disasters. Dr. Gable is also a pioneer in pediatric medical device innovation and the founder and CEO of Otobud Systems. His work bridges clinical care, policy, and device innovation to enhance the treatment of children with acute and emergent needs.
About Dr. Iyer
Krithika Iyer is a Postdoctoral Research Fellow at Children’s National Hospital, specializing in statistical shape modeling, deep learning, and medical image analysis, with a focus on mathematically grounded, rigorous, and clinically meaningful AI for pediatric healthcare. Her current work includes MRI-to-CT synthesis for infant skull and suture visualization, as well as super-resolution methods for ultra-low-field brain MRI and prediction of cognitive outcomes to improve access to neuroimaging in low-resource settings. She received her Ph.D. in Computing (Image Analysis) from the University of Utah, where she worked on probabilistic mesh- and image-based statistical shape models and diffeomorphic image registration methods for analyzing complex anatomies. Dr. Iyer plays an active role in the medical imaging and AI community, organizing international challenges and reviewing for leading conferences and journals.
About Dr. Kim
Erika Kim joined ARPA-H as a Program Manager in September 2025 from the National Cancer Institute, where she is a Senior Program Director leading strategic programs at the intersection of data science, data interoperability, and cancer research. With over 20 years of experience in deep data analytics on complex diseases and translational research, she is a nationally recognized leader with deep expertise in AI/ML, data interoperability, privacy-preserving analytics, and scalable cloud platforms. Kim plays a pivotal role in advancing cross-agency and public-private collaborations to drive innovation in precision medicine and next-generation healthcare delivery. She received her doctorate from Johns Hopkins School of Medicine in Human Genetics and Molecular Biology and carried out postdoctoral research focusing on molecular mechanisms of leukemia at the National Human Genome Research Institute.
About Dr. LaConte
Stephen LaConte is professor and interim co-director of the Addiction Recovery Research Center at Virginia Tech's Fralin Biomedical Research Institute at VTC. His lab is devoted to advanced neuroimaging acquisition and data analysis approaches, aimed at improving basic understanding of normal brain function and exploring the potential for rehabilitation and therapy for neurological and psychiatric conditions. He has applied his methods to fields ranging from alcohol abuse to traumatic brain injury.
About Dr. Patel
Anita Patel is a double board-certified Pediatrician & Pediatric Critical Care Attending at Children’s National Medical Center, where she also serves as an Associate Professor of Pediatrics at George Washington University School of Medicine. Her work combines clinical practice with research, powered by big data and AI-driven predictive analytics. From managing sedation and delirium in critically ill children to understanding severity of illness, she focuses on improving outcomes for our most vulnerable patients.
About Dr. Rider
Nicholas L. Rider is a board certified clinical immunologist and clinical informaticist. He has longstanding expertise as a care team member in the management of patients with primary and secondary immune disease. Dr. Rider serves as a Professor in the Department of Health Systems & Implementation Science at the Virginia Tech Carilion School of Medicine. Additionally, he is an Associate Chief Medical Information Officer and research informatician at the Carilion Clinic. He runs "CHILI" the Computational Human Immunology Lab and Innovation hub which seeks to leverage epidemologic, statistical, machine learning and AI approaches to improve patient diagnosis, outcomes and mechanistic insights.
About Dr. Roberts
Kirk Roberts joined McWilliams School of Biomedical Informatics at UTHealth Houston, formerly UTHealth Houston School of Biomedical Informatics (SBMI) on April 16, 2016 as an assistant professor. On September 1, 2021, Dr. Roberts was promoted to Associate Professor. He has previously conducted research in natural language processing (NLP) in academia, government, and industry. His research work includes using NLP to both extract structured information from unstructured free text and create interactive natural language applications, such as question answering systems and search engines. He actively performs research in clinical information extraction, spatial information extraction, question answering, and information retrieval. His research draws inspiration from fields as diverse as medicine, linguistics, health data science, and machine learning. Roberts is also the primary organizer of the TREC Clinical Decision Support track and a recipient of a National Library of Medicine Career Development Award.
About Dr. Sands
Paul Sands is a research assistant professor in the Montague Lab at Virginia Tech's Fralin Biomedical Research Institute at VTC, and a member of the institute's Human Neuroimaging Laboratory and Computational Psychiatry Unit. He was trained in biochemistry and psychology and conducted behavioral pharmacology research until he entered graduate school and began focusing on the neuroscience of human learning and decision-making. He earned is Ph.D. in neuroscience from Wake Forest University School of Medicine. His interests include developing mathematical models of human learning, choice behaviors, and subjective feelings as well as developing neurochemical and functional neuroimaging methods and analyses for understanding the neural bases of human behaviors.
About Dr. Tapp
Austin Tapp is a Staff Scientist at Children’s National Hospital, where his research focuses on developing AI methods for pediatric medical imaging, particularly in ultra-low-field MRI, image synthesis, and image enhancement. He received his Ph.D. in Biomedical Engineering from Old Dominion University, where he developed patient-specific spine models and AI-based approaches for scoliosis surgical planning. Dr. Tapp currently leads projects in AI-enhanced portable MRI, MRI-to-CT translation, and pediatric craniofacial analysis, with a strong focus on improving diagnostic utility, accessibility, and clinical translation of medical imaging. He is a Visiting Lecturer in the Fischell Department of Bioengineering at the University of Maryland and an active contributor to the medical imaging community as a MICCAI challenge organizer and area chair. His work in uLF imaging has received broad recognition, including a Chief Academic Officer Pilot Award from Children’s National Hospital.
About Dr. Weston
Matt Weston is an Associate Professor at Virginia Tech's Fralin Biomedical Research Institute at VTC and in the university's School of Neuroscience. He earned his Ph.D. in neuroscience at Baylor College of Medicine. His research focuses on how the brain balances excitation and inhibition in cortical circuits so that it can generate proper pattens of network activity. He studies gene variants that cause severe human childhood epilepsies, collectively referred to as Developmental Epileptic Encephalopathies (DEEs), and seeks to understand how they alter neuronal physiology to cause network hyperexcitability and seizures. His premise is that this work will advance understanding of normal physiological processes, delineate disease mechanisms, and point toward novel therapeutic strategies.
About Dr. Yao
Danfeng (Daphne) Yao is a Professor of Computer Science at Virginia Tech. She is an Elizabeth and James E. Turner Jr. '56 Faculty Fellow and CACI Faculty Fellow. Her research spans across cybersecurity and AI digital health, with a shared focus on accuracy and deployment. Her recent work, which highlights the low responsiveness of learning-based disease prediction models, has been widely reported by the media. Dr. Yao’s patents on anomaly detection are extremely influential in the industry, cited by patents from major cybersecurity firms and technology companies. Dr. Yao is an AAAS Fellow and an IEEE Fellow. She is a Senior Member of the National Academy of Inventors (NAI) and an ACM Distinguished Scientist. Dr. Yao is the Chair of the ACM Special Interest Group on Security, Audit, and Control (SIGSAC) and has been serving on the SIGSAC executive committee since 2017. Daphne received her Ph.D. degree from Brown University (Computer Science), M.S. degrees from Princeton University (Chemistry) and Indiana University (Computer Science), Bloomington, and a B.S. degree from Peking University in China (Chemistry).