Working Lunch Seminar Series
the Fields Institute, 222 College St., Toronto
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
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 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 Chans 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 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
Mohammad Samani, Prised Solar Inc.
Tuesday April 28, 2015
12 - 2 p.m.
Stewart Library, Fields Institute
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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
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 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
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
- 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!
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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