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Accelerate AI Project Closing Plenary

August 11 @ 3:00 pm - 5:00 pm

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Closing Plenary Theme

Summary of proposals and recommendations from Challenges and Ideation stages of the Accelerate AI Project. All workstreams will get together in the Closing Plenary and present the work they completed over the summer.

 

Workstream Objectives

Legal & Compliance: Identify robust mechanisms to manage exposure to legal and compliance risk from AI initiatives involving multiple business units or organizations.

Technology & Operations: Identify tools, resources, and processes to enable effective and efficient collaboration to deliver AI solutions across business units and organizations.

Governance & Business: Identify principles and perspectives on how to deliver value from AI initiatives and expedite collaboration across business units and organizations.

 

AGENDA

3:00 PM   Welcome

3:10 PM    A Machine Learning System for Radiation Therapy from Lab to Lives

Chris McIntosh, Scientist, Techna Institute, Peter Munk Cardiac Centre, and the Joint Department of Medical Imaging at the University Health Network, Faculty Affiliate, Vector Institute

3:30 PM     Q&A

3:40 PM  Governance & Business Project Presentation and Q&A

Ryan Divigalpitiya, Project Management Intern, Vector Institute

4:05 PM   Legal & Compliance Project Presentation and Q&A

Diana Moyano, Project Management Intern, Vector Institute

4:30 PM  Technology & Operations Project Presentation and Q&A

Rex Ma, Project Management Intern, Vector Institute

4:55 PM Wrap Up

 

SPEAKERS

 

Chris McIntosh

Scientist, Techna Institute, Peter Munk Cardiac Centre, and the Joint Department of Medical Imaging at the University Health Network

Chris McIntosh is a Scientist at the Techna Institute, the Peter Munk Cardiac Centre, and the Joint Department of Medical Imaging (JDMI), at the University Health Network.  He is an Assistant Professor in the Departments of Medical Biophysics and Computer Science at the University of Toronto, and a Faculty Affiliate of the Vector Institute. He further holds a joint research Chair in Medical Imaging and Artificial Intelligence at JDMI and University of Toronto. His lab focuses on the theory and clinical application of AI in medicine for improving patient care including transfer learning, meta learning, computer vision, and explainable AI. Applications include deep learning for automated diagnosis, segmentation, quality assurance, and treatment planning. His past work on AI in radiation therapy has been approved for clinical use by regulatory bodies, commercialized, and deployed in hospitals around the world, using AI to deliver reproducible, high quality cancer care.

 

 

Ryan Divigalpitiya

Project Management Intern, Vector Institute

Ryan is a Computer Science Master’s candidate specializing in Vector’s Collaborative Specialization in Artificial Intelligence. He completed his undergrad in Biophysics and Computer Science. Ryan has worked on various end-to-end machine learning projects, both in academic training and in his professional life. He also has an entrepreneurial background where he has co-founded two startups, both with a focus on using technology and AI to combat climate change.

 

Diana Moyano

Project Management Intern, Vector Institute

Diana is a Project Management Intern at the Vector Institute and a consultant for small and medium-sized companies. She has over 7 years of experience in a variety of sectors including logistics, healthcare, non-profit and technology. She holds a Bachelor’s degree in Business Management from Los Andes University (Colombia) and a Master of Management in Artificial Intelligence from the Smith School of Business at Queen’s University.

 

Rex Ma

Project Management Intern, Vector Institute

Rex is a PhD student in Computer Science at the University of Toronto supervised by Vector faculty members Dr. Anna Goldenberg and Dr. Bo Wang. His research focuses on cancer genomic integration and using machine learning to advance the human understanding of medical biology. Rex has worked on various machine learning projects covering a wide range of topics, including (but not limited to) computer vision, natural language processing, time-series prediction and clinical risk stratification.

 

About the Accelerate AI Project

The Accelerate AI | Collaborative Strategies project will address common obstacles to AI implementation. Participants will co-create a framework of best practices and strategies for addressing challenges in AI projects including data sharing, legal & compliance requirements, coordinating resources, skills, and domain expertise, obtaining leadership buy-in, and investment.  As part of the Accelerate AI project, we’ll be offering several plenary sessions to discuss how organizations can prepare themselves to deliver AI solutions, from the perspective of facilitating collaboration across teams (both internally and between organizations).

 

This meeting is open to Vector Sponsors, Vector Researchers, and invited health partners only. Any registration that is found not to be a Vector Sponsor, Vector Researcher or invited health partner will be asked to provide verification and, if unable to do so, will not be able to attend the event. Please contact winnie.au (at) vectorinstitute.ai with any questions.

 

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Virtual

Organizer

Vector Institute Collaborative Projects
Email:
industry@vectorinstitute.ai
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