CIM PROGRAMS AND ACTIVITIES

October 16, 2018

2014-15
Working Lunch Seminar Series

at the Fields Institute, 222 College St., Toronto

Tuesday, June 23, 2015
11 - 1 p.m.
Stewart Library, Fields Institute

To confirm your attendance at the June 23 Working Lunch Seminar, please register online.

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Sports Analytics

Part I: Timothy Chan

In this talk, Professor Timothy Chan will discuss some of his recent sports analytics research in hockey and baseball. In hockey, he and his students have developed a player classification system for both NHL and junior hockey players. This system can be used to estimate the contribution of different players to their team and to predict future performance. In baseball, he and a collaborator have developed a method to quantify the value of "flexible" players – those who can play multiple positions – which provides insight into which teams are more resilient to injury risk.

Part II: Ming-Chang Tsai
Sport analytics is a rapid-growing field that is changing the way athletes train, prepare, and compete. Many professional sports (NBA, NFL, and soccer) are undergoing a "Moneyball period" in which technologies such as GPS, accelerometry, heart rate (HR) and video are used to monitor player positioning, movement, and physiological responses. Rugby has recognized the benefit of incorporating sport analytics to gain competitive edge over other teams and have been collecting speed, acceleration, and HR data in real-time with physiological data already being measured using standard laboratory and field-based methodologies. Discriminant analysis was used to identify performance indicators between winning and losing in basketball, while clustering and regression methods were used to characterize individual player's contribution to team's overall performance in hockey. At the recent Fields big data analysis workshop, researchers identified indicators that contribute to winning/losing/performance, athlete types based on their offensive and defensive behaviors, and athlete behavior within game. Preliminary insights in connecting physiological to tactical/technical data are being investigated as well.

 

Timothy Chan

Timothy Chan is an Associate Professor in the Department of Mechanical and Industrial Engineering at the University of Toronto and Director of the Centre for Research in Healthcare Engineering. He received his BSc in Applied Mathematics from the University of British Columbia (2002), and his PhD in Operations Research from the Massachusetts Institute of Technology (2007). Professor Chan was an Associate in the Chicago office of McKinsey and Company, a global management consulting firm (2007-2009). During that time, he advised leading companies in the fields of medical device technology, travel and hospitality, telecommunications, and energy on issues of strategy, organization, technology and operations.

Professor Chan’s primary research interests are in optimization under uncertainty and the application of optimization methods to problems in healthcare, medicine, global engineering, sustainability, and sports. He received the George B. Dantzig Dissertation Award from INFORMS (2007), an Early Researcher Award from the Ministry of Economic Development and Innovation of Ontario (2012), an Early Career Teaching Award from both the U of T Department of Mechanical and Industrial Engineering (2012) and the U of T Faculty of Applied Science & Engineering (2013), second place in the INFORMS Section on Public Programs, Service and Needs best paper competition (2012), and first place in the MIT Sloan Sports Analytics Conference research paper competition (2013). His research has been featured by the CBC, CTV News, the Toronto Star, and Canadian Business magazine.

Ming-Chang Tsai

Ming-Chang Tsai is a researcher in the Faculty of Kinesiology and Physical Education at the University of Toronto and a data analyst/sport scientist at the Canadian Sport Institute Pacific. He received his BASc in Engineering Science from the University of Toronto (1995) and his PhD in Exercise Sciences from University of Toronto (2015).

Ming has been coaching for 20 years in rowing, cycling, running, and triathlon. He was an elite rower competed around the world with the Chinese Taipei national team at World Cups, World Championships, Asian Championships, and Asian Games. After his elite rowing career was over, he started racing multisport and has represented Canada on several Age Group World Championship teams in Duathlon and Triathlon.

Friday June 12, 2015
11 - 12:30
Room 210 at the Fields Institute

 

Special Workshop: Optimization of a novel purification process of solar grade silicon

We have developed a novel technique for purifying silicon that does not require the conventional chemical treatment of the Siemens process. Instead, we treat metallurgical grade silicon wafers in solid state with
microwave radiation. This technique has been experimentally shown to be effective in forcing the migration of transition metals, which radically harm the performance of semiconductor devices. We are trying to optimize the process for mass production of solar grade silicon.

Mohammad Samani, Prised Solar Inc.

Tuesday April 28, 2015
12 - 2 p.m.
Stewart Library, Fields Institute

 

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OpenCL: The Hardware Evolution and the Software Revolution

Computer hardware is evolving in ways that prompt changes to how software is written for performance. The era of a single increasingly fast processor in a system gave way to the homogeneous parallel programming era, with multiple cores and processors from the same vendor in a system. The next evolutionary step upon us is the heterogeneous parallel programming era, with multiple cores and processors from different vendors in the same system. Heterogeneous compute systems can be faster than homogeneous systems and may require a fraction of the energy.

The Khronos OpenCL specification is a standard for parallel heterogeneous computing that enables software to leverage CPUs, GPUs, FPGAs, or other accelerators detected in a system. It provides a set of abstractions that can obtain peak performance on physical hardware across processor architectures. OpenCL standardizes a common device programming language so that developers can write software to run on any supported processor. Today, OpenCL is available on everything from a mobile device to a supercomputer, opening a world of opportunities for business and researcher.

This talk will motivate the OpenCL standard and present its opportunities and challenges. A survey of performance gains and energy savings will be provided so that the potential of the parallel heterogeneous compute era can be understood. The recent announcements from Khronos at GDC 2015, including Vulkan and OpenCL 2.1, will be echoed.

AJ Guillon

AJ Guillon is a Khronos member and actively contributed to the new OpenCL C++ kernel language, provisionally released as part of OpenCL 2.1. He has dedicated himself to solving the hardest problems in parallel programming and software engineering. AJ is the founder and CTO of YetiWare Inc, a local startup company that is commercializing a distributed heterogeneous compute operating system for next-generation cloud analytical platforms.

AJ is an alumni of the University of Toronto where he completed his Honors Bachelor of Science with a strong focus on mathematics, operating system design, and computer science theory. His passions include big, fast computers and the mathematics that powers them. AJ is a masters swimmer, water polo player, and enjoys rock climbing when time permits.

 

February 24, 2015
12:30 - 2 p.m.
Stewart Library, Fields Institute
Brain-CODE - Ontario Brain Institute's Data Integration Platform: Opportunities for Complex Data Analytics

As the production and use of data in research and healthcare increase we are faced with a big data challenge and an array of opportunities to make the most of this data. Not only is the size, volume, variety, and potential privacy issues of this multi-dimensional data present some unique challenges but our ability to efficiently standardize, collect, store, manage, and process this data ultimately determines its utility and the efficacy of the resulting analysis. It is an exciting time for big data analytics for brain health and medicine which holds promise for improved and faster diagnosis and discovery!

Francis Jeanson
Program Lead, Informatics, Ontario Brain Institute

Francis has joined OBI in the spring of 2013 to help design and implement the Brain-CODE neuroscience informatics platform. Francis first pursued an Honours Bachelors of Science at the University of Toronto in Cognitive Science and Artificial Intelligence and developed a passion for embodied cognition and robotics. After gaining experience as a software developer, Francis pursued a Masters in Evolutionary and Adaptive Systems at the University of Sussex which he completed in 2008. There, he honed his skills in neural modelling and evolutionary robotics. He finally moved on to pursue a PhD in Cognitive Science with a focus in neural coding theory and application at Carleton University which he completed in the winter of 2014. Francis possesses a long standing interest in complex systems, cognitive robotics, artificial intelligence, computational analysis, and modelling. He is excited to work with OBI and hopes to see flourish the enormous potential that the Brain-CODE neuroinformatics platform can offer for multidimensional brain research.

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