Preparing healthcare
for the AI era.

Demetri Giannikopoulos is Chief Innovation Officer at Rad AI and a national leader in healthcare artificial intelligence, AI governance, and responsible innovation. He works with healthcare organizations, industry leaders, and academic collaborators to advance trustworthy, human-centered AI through governance, education, and clinical implementation. His leadership spans radiology, cardiology, critical care, and enterprise clinical operations, where he works to align innovation with patient safety, clinical quality, operational excellence, and measurable healthcare outcomes.

His contributions include leadership with the Coalition for Health AI (CHAI), development of the BRIDGE Guidelines, participation on URAC's Health Care AI Advisory Committee, service on the American College of Radiology's Patient and Family Centered Care Quality Experience Committee, and advocacy as a PCORI Ambassador. His work focuses on building transparent, explainable, and patient-centered AI that improves healthcare quality and outcomes.

Jamie L. Fairclough, PhD, MPH, MS is a data scientist, educator, and healthcare researcher specializing in artificial intelligence, biomedical data science, machine learning, and health analytics. She serves as Director of Mental Health Evaluation and Assessment and is a VA researcher at the VA Southern Nevada Healthcare System. At Roseman University College of Medicine, she provides strategic leadership in data science, analytics, assessment, and evaluation to support medical education and institutional decision-making.

Dr. Fairclough's research focuses on machine learning, computer vision for medical imaging, AI systems engineering, digital twin modeling, disease surveillance, and spatial epidemiology. She is Co-Chair of the AI Primer for Medical Students and Co-Chair of the Emerging Leaders Interdisciplinary Conference: AI in Healthcare, reflecting her commitment to advancing AI education and interdisciplinary collaboration. With more than 15 years of experience in higher education, government, and healthcare, she continues to lead initiatives that integrate data science, artificial intelligence, and evidence-based evaluation to improve healthcare delivery and medical education.

Tanveer Syeda-Mahmood, PhD is an IBM Fellow, Chief Scientist, and Stanford Adjunct Professor recognized as a global leader in artificial intelligence, medical imaging, and multimodal foundation models. Her work focuses on advancing computer vision, healthcare AI, trustworthy AI, and clinical decision support systems, translating cutting-edge research into scalable technologies deployed in real-world healthcare and enterprise environments.

Dr. Syeda-Mahmood has led the development and commercialization of AI innovations that bridge scientific discovery and clinical practice. She also mentors the next generation of AI researchers through Stanford's Biomedical Data Science Program while collaborating with leading clinicians, researchers, industry partners, and healthcare organizations worldwide to advance responsible AI and precision medicine. Dr. Syeda-Mahmood was declared Master Inventor in 2011 and in 2019. She is the recipient of key awards including IBM Corporate Award 2015, Best of IBM Award 2015, 2016 and several outstanding innovation awards.

Mark Hiatt, MD, MBA, MS, is a physician executive, cardiovascular radiologist, and founding board member of the American Board of Artificial Intelligence in Healthcare (ABAIH). He serves as Chief Medical Officer of RadSite, a CMS-approved accrediting organization for advanced diagnostic imaging, and as Principal of Hiatt Advisory Services, where he advises healthcare organizations, health plans, diagnostic companies, and medical technology firms on clinical strategy, evidence development, medical policy, reimbursement, market access, and the responsible adoption of artificial intelligence.

Dr. Hiatt’s experience spans clinical practice, payer leadership, precision diagnostics, accreditation, utilization management, and medical affairs. He previously held senior medical leadership roles at Guardant Health, Regence BlueCross BlueShield, HealthHelp, BostonGene, and FrontRunnerHC and completed fellowship training in cardiovascular imaging at Stanford University. Through ABAIH, he supports practical AI education, rigorous competency assessment, and evidence-based approaches to the safe and effective implementation of AI across healthcare.

Di Lacey, DHSc is a senior healthcare executive with more than three decades of leadership experience in healthcare strategy, organizational transformation, innovation, and academic medicine. As Senior Executive for Strategy, Growth and Transformation at Western University of Health Sciences, she leads strategic initiatives focused on institutional growth, leadership development, program expansion, and healthcare innovation.

With a clinical background in medical imaging and diagnostic ultrasound, Dr. Lacey has been an early advocate for the adoption of emerging healthcare technologies. Her career has spanned executive leadership in healthcare systems, strategic planning, business development, and academic medicine, including previous leadership roles in strategy and innovation at PeaceHealth.

Dr. Lacey is a founding member of the American Board of Artificial Intelligence in Healthcare (ABAIH) and serves as Co-Advisor for the Artificial Intelligence in Medicine Club at Western University of Health Sciences. She is a strong advocate for responsible and ethical AI adoption in healthcare education and clinical practice. She also serves on the Inteleos POCUS Certification Academy Committee, contributing to national efforts in professional competency, AI education, and workforce development.

Through her leadership, Dr. Lacey continues to advance innovation, interdisciplinary collaboration, and the responsible integration of artificial intelligence to prepare the next generation of healthcare professionals.

Micah Thorp, DO is a nephrologist and clinical researcher specializing in chronic kidney disease, hypertension, predictive analytics, and artificial intelligence in population health. He provides comprehensive care for patients across the spectrum of kidney disease, from early-stage chronic kidney disease to dialysis and kidney transplantation, with a focus on delivering long-term, patient-centered care.

In addition to his clinical practice, Dr. Thorp is a researcher at the Kaiser Permanente Center for Health Research, where he investigates innovative approaches to improving kidney care through predictive modeling and data-driven clinical decision support. His research focuses on translating real-world evidence into clinical practice to improve outcomes and optimize care delivery.

Dr. Thorp has been actively involved in the application of artificial intelligence and machine learning to nephrology, collaborating with Medial EarlySign on initiatives to identify Kaiser Permanente patients most likely to benefit from targeted care interventions. His work reflects a commitment to leveraging AI to advance precision medicine, improve population health, and support proactive, value-based care for patients with kidney disease.