Farzad Khalvati

AI Associate, Department of Diagnostic Imaging

Scientist, Neurosciences and Mental Health, Research Institute

Dr. Khalvati received his PhD in Electrical and Computer Engineering from University of Waterloo and before joining SickKids Hospital, he worked in industry, and Sunnybrook and Mount Sinai hospitals as imaging and AI Scientist. At SickKids, Dr. Khalvati is a Scientist and Endowed Chair in Medical Imaging and Artificial Intelligence, and his research focuses on Artificial Intelligence solutions in Medicine.

Research

Dr. Khalvati’s Intelligent Medical Image Computing Systems (IMICS) Lab focuses on developing Artificial Intelligence solutions for Medical Imaging and Precision Medicine. His research goal is to design and develop AI-based diagnostic and prognostic algorithms and tools to improve the quality of care for patients.

To Learn more about his Lab

Education

• 2009: PhD, Electrical and Computer Engineering, University of Waterloo, Waterloo, ON
• 2003: M.A.Sc., Electrical and Computer Engineering, University of Waterloo, Waterloo, ON
• 1998: BSc., Electrical and Computer Engineering, University of Tehran, Tehran, Iran

Experience

• 2020-present: Scientist, Neurosciences & Mental Health, Hospital for Sick Children, Toronto, ON
• 2017-2020: Staff Scientist, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON
• 2014-2017: Junior Scientist, Imaging Research, Sunnybrook Research Institute, Toronto, ON
• 2013-2014: Postdoctoral Research Associate, Imaging Research, Sunnybrook Research Institute, Toronto, ON
• 2009-2012: NSERC Industrial R&D Fellow, Toronto, ON

Achievements

• Derek Harwood-Nash Annual Lecture in Neuroradiology Award, The Hospital for Sick Children, Department of Diagnostic Imaging, Toronto, Ontario, Canada.
• 2020: Chair in Medical Imaging and Artificial Intelligence, The Hospital for Sick Children and University of Toronto
• 2015: Careers in Cancer Research Development New PI Award, CIHR-Institute of Cancer, Research (CIHR-ICR)
• 2011: Industrial Research and Development Fellowship Award, NSERC
• 2010: First Job Award, Ontario Centres of Excellence (OCE)
• 2007: NSERC Postgraduate Scholarship, University of Waterloo
• 2007: President's Graduate Scholarship, University of Waterloo
• 2007: President's Graduate Engineering Scholarship, University of Waterloo

1. Motamed, S., Rogalla, P., Khalvati, F. Data augmentation using generative adversarial networks (GANs) for GAN-based detection of pneumonia and COVID-19 in chest X-Ray images (2021). Informatics in Medicine Unlocked. Impact Factor 3.373. (Trainee publication, Motamed, S., primary supervisor). Senior Responsible Author.
2. Wagner, M.W., Namdar, K., Biswas, A., Monah, S., Khalvati, F., Ertl-Wagner, B.B. Radiomics, machine learning, artificial intelligence – What the neuroradiologist needs to know (2021) Neuroradiology. Impact Factor 3.00. (Trainee publication, Namdar, K., primary supervisor). Co-Senior Responsible Author.
3. Hao, R., Namdar, K., Liu, I.L., Haider, M.A., Khalvati, F. A comprehensive study of data augmentation strategies for prostate cancer detection in diffusion weighted MRI using convolutional neural networks (2021) Journal of Digital Imaging. Impact Factor 3.977 (Trainee publication, Hao, R., Namdar, K., primary supervisor). Senior Responsible Author.
4. Motamed, S., Rogalla, P., Khalvati, F.  RANDGAN: Randomized generative adversarial network for detection of covid-19 in chest X-Ray (2021) Scientific Reports. Impact Factor 5.133. (Trainee publication, Motamed, S., primary supervisor). Senior Responsible Author.
5. Zhang, Y., M. Lobo-Mueller, E., Karanicolas, P., Gallinger, S., Haider, M.A., Khalvati, F. Improving prognostic performance in resectable pancreatic ductal adenocarcinoma using radiomics and deep learning features fusion in CT images (2021) Scientific Reports. Impact Factor 5.133. (Trainee publication, Zhang, Y., primary supervisor). Co-Senior Responsible Author.

See a full list of Farzad Khalvati's Publications