Dr. Farzad Khalvati, PhD, is a Senior Scientist and Endowed Chair in Medical Imaging and Artificial Intelligence at The Hospital for Sick Children (SickKids) and University of Toronto. He is an Associate Professor in the Department of Medical Imaging and Institute of Medical Science, with cross appointments to the Department of Computer Science and Department of Mechanical and Industrial Engineering at the University of Toronto. He is also a Faculty Affiliate at Vector Institute.

Dr. Farzad Khalvati, Principal Investigator

Dr. Khalvati is an accomplished and visionary research leader with extensive expertise in advancing medical innovation through Artificial Intelligence, multidisciplinary collaboration, and strategic funding, securing over $3.8M in research grants. Dr. Khalvati is a prolific contributor to the field with 115 research articles with 70 scientific abstracts, demonstrating a proven track record of driving impactful discoveries in medicine. Experienced in mentoring and managing diverse teams of over 75 individuals and fostering strategic partnerships across academia, industry, and healthcare organizations. With specialized expertise in clinical validation and regulatory frameworks for medical devices and Artificial Intelligence tools, Dr. Khalvati is committed to leveraging scientific advancements and facilitating clinical deployment and commercialization to advance precision medicine, improve patient outcomes, and promote equitable, compassionate healthcare.

EXPERTISE
• Precision Medicine and Precision Child Health, leveraging advanced AI techniques to deliver personalized diagnostics and treatment strategies tailored to individual patients, including pediatric populations.
• Development of optimized and multimodal AI solutions that integrate diverse data sources such as medical imaging, pathomics, genomics, and health informatics to enhance healthcare outcomes.
• Pioneering efforts in Explainable AI (XAI) to ensure transparency, trust, and interpretability in AI models, empowering clinicians to make informed decisions.
• Focused on designing AI for equitable healthcare, addressing biases to ensure fair access and outcomes for diverse populations.
• Emphasis on clinician-centered AI tools that seamlessly integrate into clinical workflows, enhancing usability and reducing barriers to adoption.
• Dedicated to the clinical translation of AI models, bridging the gap between research and real-world implementation, and ensuring robust validation, regulatory compliance, and impactful deployment in healthcare settings.

Dr. Khalvati received his PhD in Electrical and Computer Engineering from University of Waterloo and before joining University of Toronto, he worked as an imaging and AI scientist in biomedical industry and then as a Postdoctoral Research Associate at Sunnybrook Research Institute. Dr. Khalvati is a recipient of several awards from NSERC, OCE, and CIHR and his dissertation was selected and patented by the University of Waterloo Commercialization Office.