AIMLx27: Personalized AI

Jonathan H. Chen

Affiliation: Stanford Medicine; Director of Medical Education in Artificial Intelligence

Website Bio: Jonathan H. Chen MD, PhD leads a clinical informatics research group to empower individuals with the collective experience of the many, combining human and artificial intelligence to deliver better care than either alone. He also serves as Director of Medical Education in Artificial Intelligence for Stanford Medicine. Before his medical training, Dr. Chen co-founded a company to translate his Computer Science graduate work into an expert system used by people around the world. He continues to practice medicine for the concrete rewards of caring for real people and to inspire his work to advance not just the science and technology, but to redefine how we train (and retrain) an entire generation of the healthcare workforce to safely and effectively integrate intelligent systems to reach all patients in need. His expertise is featured in the popular press with over 100 research publications and awards from the NIH, ARPA-H, American Medical Informatics Association, International Brotherhood of Magicians, and more.

Presentation Title: AI in Medicine: Real Magic or Technological Illusions?

Jonathan L. Adams

Affiliation: Florida State University, College of Communication and Information; Director, CCI Machine Learning Lab; Professor Emeritus

Website Bio: Dr. Jonathan L. Adams is Professor Emeritus in Florida State University's College of Communication and Information and Director of the CCI Machine Learning Lab. His work focuses on learning technologies, artificial intelligence, and the future of education. He explores how emerging technologies are transforming teaching, learning, credentialing, and workforce development. His AIMLX27 presentation examines how AI may accelerate a transition from traditional lecture-based instruction toward more learner-centered educational models.

Presentation Title: The Paideia Proposal Revisited: From Sage on the Stage to Guide on the Side

Delaney W. La Rosa

Affiliation: Florida State University College of Nursing

Website Bio: Delaney W. La Rosa, EdD, MSN Ed, RN, is a Teaching Professor in Artificial Intelligence in Healthcare and AI Program Track Coordinator in Florida State University's College of Nursing. Her work focuses on integrating artificial intelligence into healthcare education and practice through responsible, equitable, and evidence-based approaches. She is the author and editor of scholarship examining nursing education in the AI era and explores how AI literacy and discernment can support effective decision-making across healthcare environments.

Presentation Title: AI Discernment for Responsible Healthcare Innovation

Oliver Steinbock

Affiliation: Florida State University

Website Bio: Oliver Steinbock is a professor of chemistry at Florida State University whose research explores complex chemical systems, pattern formation, and innovative approaches to scientific discovery. His AIMLX27 presentation examines how artificial intelligence is enabling personalized approaches to chemistry, including chemical analysis, health monitoring, education, and scientific research. His work highlights how AI can tailor chemical applications and learning experiences to individual users while raising important questions about privacy, reliability, and access.

Presentation Title: Same Equation, Different Song: Personalized AI in Chemistry

Christian Hubicki

Affiliation: FAMU-FSU College of Engineering, Department of Mechanical and Aerospace Engineering; Associate Professor

Website Bio: Christian Hubicki, Ph.D., is an Associate Professor of Mechanical and Aerospace Engineering at the FAMU-FSU College of Engineering and leads research in robotics, bipedal locomotion, optimal control, and biomechanical modeling. He earned his Ph.D. from Oregon State University and directs research focused on enabling legged robots to move with the speed, maneuverability, and stability seen in animals. His work combines robotics, control systems, and biomechanics to advance the capabilities of autonomous machines.

Michael Wolfe

Affiliation: Florida State University; Director of AI Research Solutions

Website Bio: Michael Wolfe is Director of AI Research Solutions at Florida State University. His scholarship spans gene regulation, machine learning, and the application of artificial intelligence to scientific research. With a background in computational and molecular biology, he has authored widely cited research on transcriptional regulation, RNA biology, bacterial genomics, and data-driven discovery. His current work focuses on helping researchers apply AI and advanced computational methods to accelerate scientific innovation across disciplines.

Presentation Title: People-centered Infrastructure for AI-accelerated Science