At Intelligent Medical Image Computing Systems (IMICS) Lab at The Hospital for Sick Children and University of Toronto we investigate and develop Artificial Intelligence solutions for precision medicine using medical imaging. Our goal is to design and develop AI-based diagnostic and prognostic tools to improve the quality of care for patients.
Dr. Farzad Khalvati, Principal Investigator: Farzad Khalvati, PhD, is the Endowed Chair in Medical Imaging and Artificial Intelligence at The Hospital for Sick Children (SickKids) and University of Toronto. He is Associate Professor in the Department of Medical Imaging and Institute of Medical Science, with a cross appointment to the Department of Mechanical and Industrial Engineering at the University of Toronto. He is also a Faculty Affiliate at Vector Institute. He is actively engaged in bridging the gap between AI researchers and clinicians to design and implement AI solutions that can be integrated into clinical workflows with a tangible impact on the quality of patient care. One important aspect of Dr. Khalvati’s research is to design and implement joint clinician-AI decision making solutions, which will significantly advance our understanding of how AI algorithms findings can be translated from mere information to practical meaning, and how that meaning can be properly communicated to clinicians in order to significantly improve the accuracy of final diagnoses, prognoses, and treatment planning with a direct impact on the quality of care given to patients.
Dr. Khalvati has published over 115 peer-reviewed publications as journal papers (37), patents (3), book chapter (1), and conference full papers (36) and abstracts (38). He has also co-authored a book. He has received ~$1.7M in peer-reviewed research grants as PI ($950K), Co-PI ($75K), Co-I ($620K), and collaborator ($50K). Dr. Khalvati has supervised 36 trainees as Primary Supervisor at different levels, including 21 undergraduate students, 11 graduate students, 2 postdoctoral fellow, and 4 Research Associates.
Dr. Khalvati received his PhD in Electrical and Computer Engineering from University of Waterloo in 2009 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.
Dr. Khalvati’s research is funded by:
- Canadian Cancer Society/CIHR/Brain Canada Foundation
- AMS Healthcare
- Chair in Medical Imaging and Artificial Intelligence, a joint Hospital-University Chair between the University of Toronto, The Hospital for Sick Children, and the SickKids Foundation
- Huawei Technologies Canada
- Astellas Pharma
- Cancer Care Ontario
- Department of Medical Imaging, University of Toronto
Ernest (Khashayar) Namdar, MASc, MEng, Machine Learning Researcher
Saman Motamed, MSc Candidate, Institute of Medical Science, University of Toronto
Kareem Kudus (with Dr. Birgit Ertl-Wagner), MSc Candidate, Institute of Medical Science, University of Toronto
Partoo Vafaeikia, MSc Candidate, Institute of Medical Science, University of Toronto
Sajith Rajapaska, MSc Candidate, Institute of Medical Science, University of Toronto
Maryam Taheri-Shirazi, MASc (with Dr. Matt Wagner), Machine Learning Researcher
Zilun Zhang, MEng Student, Department of Mechanical and Industrial Engineering, University of Toronto
Jay Yoo, BSc, Machine Learning Researcher
Yue Tong Leung, MEng Student, Department of Mechanical and Industrial Engineering, University of Toronto
Vicky Chan, Undergraduate Thesis Student, Engineering Science, University of Toronto
Capstone Projects, Department of Mechanical and Industrial Engineering
- Artificial Intelligence-based pediatric-specific solution for touchless interaction using voice control during image guided surgeries. Christina Seo, Bayaan Shalaby, Sheree Zhang, Litong Zheng, 2020-2021
- A front-end graphical user interface module design and implementation for Radiomics analytics pipeline in medical imaging using PyQt. Ines Gomes, Samuel McCulloch, Gabriella Tolnai, Lora Tyufekchieva, 2020-2021.
Ruqian Hao, Visiting PhD Scholar (2019-2020) (Now PhD Candidate at School of Optoelectronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan, China)
Yucheng Zhang (with Dr. Masoom Haider) (2017-2019), MSc, (Now Medical Student at University of Toronto)
Junjie Zhang (with Dr. Masoom Haider) (2015-2017), Postdoctoral Fellow (Now Research Data Scientist at RBC Capital Markets)
Undergraduate Research Assistants
Kevin Wang (2020-2021), BSc Thesis, Engineering Science, University of Toronto. Project: Variational Autoencoders for Dimension Reduction of Radiomic Data
Julia Le (2018) (Now MSc student at University of Toronto)
Saman Motamed (2018-2019) (Now MSc student at University of Toronto)
Jacob Yoo (2017, 2019) (Now MSc student at York University)
Yucheng Zhang (2015-2017) (Now Medical Student at University of Toronto)
Tyler Clark (2016-2017)
Harry Kim (2018)
Jeffrey Francis (2017)
Dylan Clark (2017)
Steve Ming (2015)
Derek Jedral (2015)
Nilaan Gunabalachandran (2015)
IMICS Lab is located on the 8th floor at Peter Gilgan Centre for Research and Learning (PGCRL) building on SickKids campus: 686 Bay St, Toronto, ON M5G 0A4.
Email: farzad dot khalvati at utoronto dot ca