Event Speaker
Bardia Khosravi, MD, MPH, MHPE
Radiology Resident
Yale University
Bardia Khosravi is an MD, with two masters in medical education (MHPE) and public health (MPH). He has been a full stack developer since he was 19 and started his research on deep learning applications in Raiology at Mayo Clinic in 2021, with a focus on generative AI and fairness. He is also serving as a memebr of SIIM Machine Learning Education sub-comittee since 2022. He is passionate about culinary arts and his hobby is cooking different cuisines.
Sessions
AI-Powered Productivity: Practical Tools Beyond Clinical Applications
Presented by Eduardo Farina, MD, Amirali Khosravi, Pouria Rouzrokh, MD, MPH, MHPE, Bardia Khosravi, MD, MPH, MHPE Jun 12, 2026 | 7:30 AM.
Healthcare professionals are under constant pressure to do more with less time, often spending hours each week on non-clinical work such as literature review, content creation, administrative tasks, and workflow coordination. This interactive session addresses a clear and growing need: helping attendees reclaim meaningful time by using AI tools in practical, low-barrier ways that fit…
Applying AI to Facilitate Clinical Research & Peer Review Workflows: A Recipe for Effective, Efficient, and Ethical Practice Learning Lab
Presented by Pouria Rouzrokh, MD, MPH, MHPE, Bardia Khosravi, MD, MPH, MHPE Jun 10, 2026 | 4:00 PM.
Modern AI has the potential to dramatically accelerate clinical research and peer review—but when used imprecisely or without safeguards, it can introduce ethical risks, reproducibility gaps, and credibility issues. Many clinicians and researchers are already experimenting with AI tools, yet lack clear guidance on when to use them, how to use them responsibly, and how…
Enhancing Medical Education with Artificial Intelligence: How to Achieve Personalized Learning in Practice
Presented by Mahan Mathur, MD, Michael Recht, MD, Pouria Rouzrokh, MD, MPH, MHPE, Bradley Erickson, MD, PhD, CIIP, FSIIM, Bardia Khosravi, MD, MPH, MHPE Jun 11, 2026 | 10:00 AM.
Artificial intelligence (AI) is rapidly reshaping medical education by enhancing curriculum design, content development, assessment, and learner support. With no-code, widely accessible tools now available, AI can be used effectively by trainees, faculty, and program directors when applied transparently and responsibly. This session provides practical guidance for integrating AI across Harden’s 10-step curriculum development framework, using examples…