Tuesday, May 29, 2018

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• Attendees visit campus for True North @ Waterloo
• HR hosted Lean seminar and projects fair for employees
• $3.7M in funding for AI and medical imaging project

Attendees visit campus for True North @ Waterloo

Attendees of the True North Waterloo conference at the Lot 42 event space in Kitchener will be visiting the University of Waterloo today for a special interactive event.

Organized by Communitech, True North is billed as an event that "will focus on how to reaffirm tech as a force for good in the world— and give innovators, entrepreneurs, academics and policymakers a renewed sense of mission to ensure it remains so."

The University will welcome 125 guests for a multi-session event entitled "Beyond Impact: True North @ Waterloo" at the Mike and Ophelia Lazaridis Quantum-Nano Centre and the Sedra Student Design Centre in Engineering 5.

Activities include a panel discussion, networking break, and interactive experience in the Sedra Student Design Centre that includes a student team and startup hardware showcase as well as the University's latest research innovations. Participants will connect with cutting-edge researchers and startups in areas including AI, quantum, autonomous vehicles and more.

Panellists include:

• Ryan Gariepy, Clearpath Robotics
• Katarina Ilic, Voltera
• Alex Wong, Canada Research Chair, University of Waterloo

The event is intended to highlight the University of Waterloo's historic and ongoing contribution to the region’s innovation ecosystem and the importance of Waterloo’s research and entrepreneurial spirit that has been a unique catalyst for the continued growth of the community.

The University of Waterloo is a proud sponsor of #TrueNorth18.

HR hosted Lean seminar and projects fair for employees

On Wednesday, May 9, Human Resources hosted a Lean seminar titled “Creating a Culture of Daily Continuous Improvement in Higher Education” and a Lean projects fair for employees. A Lean workshop for leaders and executives was held on Thursday, May 10. The seminar and workshop were led by Karyn Ross, co-author of The Toyota Way to Service Excellence: Lean Transformation in Service Organizations.

Ross presented on the importance of creating a deliberate culture of daily continuous improvement by using creativity and divergent thinking. “Hope is not a strategy,” said Ross. To address problems for daily continuous improvement, organizations need to identify gaps between their current state and their goals.

The Lean Projects Fair was attended by more than 100 employees interested in learning about Lean initiatives happening in other departments at Waterloo. Departments who showcased Lean projects included the Sustainability Office, Plant Operations, Housing and Residence, Office of the Provost, Human Resources, IST, Registrar’s Office, St. Jerome’s, and the Library. The University of Guelph also attended to demonstrate how Lean has been applied in other higher education institutions.

On Thursday, May 10, representatives from the University and other organizations, including Bell Canada, Big Brothers Big Sisters of Canada, McMaster University, St. Mary’s General Hospital, and many more, attended the “Leading Lean in Higher Education” workshop for leaders.

To read the full article, view the event photos and to learn more about Lean, please visit the Waterloo Lean website. 

Pictured above (from L-R) are Kimberley Snage, Director HR Projects, Technology Analytics, Karen Ross, co-author of The Toyota Way to Service Excellence, Kenton Needham, Executive Director HR.

$3.7M in funding for AI and medical imaging project

The University of Waterloo's Laboratory for Knowledge Inference in Medical Image Analysis (Kimia Lab) recently announced that its AI project for digital pathology has been awarded a grant by the Ontario Research Fund – Research Excellence program (ORF-RE). The project aims to develop an intelligent search engine for digital pathology that can retrieve relevant cases from large archives, auto-caption the images, and facilitate consensus building.

“Digital pathology has opened new horizons in medical diagnosis” says Professor Hamid Tizhoosh, the director of Kimia Lab and the Principal Investigator of the project. “At the same time, we have been witnessing the rise of artificial intelligence technologies in recent years that could be applied to discover and exploit the collective wisdom in the big image data”. The project, entitled “Computational Peer Review through Identification and Captioning of Gigapixel Digital Pathology Scans” is entirely focused on using, fine-tuning and designing AI algorithms for whole-slide imaging.

The Ontario government will fund the 5-year project with a grant in amount of $3.2M. Huron Digital Pathology, as the industrial partner of Kimia Lab, will contribute $500k to the project. The company is the only Canadian manufacturer of digital scanners for pathology. Four professors from the University of Waterloo (Mark Crowley, Ali Ghodsi, Oleg Mikhailovich, and Hamid Tizhoosh), together with the machine learning group at the University of Guelph led by professor Graham Taylor (Vector Institute), and professor Shahryar Rahnamayan (UOIT) will collaborate with three hospitals to design and test an advanced search engine for large pathology archives. Grand River Hospital (Kitchener, ON), Southlake Regional Health Centre (Newmarket, ON) and University of Pittsburgh Medical Center (PA, USA) will not only provide data but also validate the results of the project.

“We regard this as an exciting and historic opportunity to contribute to the improvement of the healthcare system in such a sensitive and significant field as pathology” adds Tizhoosh, “specially at this point of time when the research in artificial intelligence has started to yield practical results.”

The Laboratory for Knowledge Inference in Medical Image Analysis (Kimia Lab for short), a member of Waterloo Artificial Intelligence Institute, conducts research at the forefront of mass image data in medical archives using machine learning schemes with ultimate goal of extracting information that cannot only support a more speedy and accurate diagnosis and treatment of many diseases but also establish new quality assurance based on mining of existing evidence.