FEATURE
Fields CQAM Interdisciplinary Thematic Program
January 1-June 30, 2019 • Fields Institute
Organizers: Matt Davison (Western University), James Green (Carleton University), Huaxiong Huang
(Fields Institute), Kim McAuley (Queen's University), Robert McCann (University of Toronto), Ian Milligan
(University of Waterloo), Shirley Mills (Carleton University), and Jianhong Wu (York University)
The 2019 Fields CQAM
Interdisciplinary
Thematic program
united academic
researchers with
industry professionals
in deploying advanced
mathematics, as they
explored innovative
solutions to a wide
variety of challenges.
It offered two
graduate courses,
two seminars, four
special lectures and
seven workshops
that aimed to address long-standing problems in
the fields of economics and finance, energy and
sustainability, advanced manufacturing, public
health, and social science and humanities in the
digital age. These events engaged more than 1200
participants from around the world, nearly 20% of
whom were industry experts seeking to further their
careers with relevant professional development.
Professor Geoffrey Hinton leads a
Machine Learning module
at Fields Institute on March 7, 2019.
6
Among the
highlights was a
Machine Learning
Graduate Course,
attracting guest
lecturer Geoffrey
Hinton (University
of Toronto) as well
as experts from
the Vector Institute
and the University
of Toronto (U of T)
Computer Science
Department. The
Program also offered
a sold-out public lecture by Kang Lee, who discussed
methods by which AI developers can improve
the emotional quotient of intelligent systems.
Robert McCann’s semester-long graduate course,
Mathematical Problems in Economics, opened the
Interdisciplinary Thematic Program. It surveyed
a range of topics in which mathematicians are
currently contributing to important advances,
including theory of matching and pricing,
problems of asymmetric information, the
principle-agent framework, auction theory, and
mechanism design. Other topics discussed were
matching with unobservable heterogeneity and
imperfectly transferable utility, and equilibrium
in situations of non-linear price response. The
course aimed to prepare students for research
on related topics as well as to maximize their
benefit from other components of the Program. In
total, nine graduate students enrolled and roughly
double that number attended, attracting several PhD
candidates from the Departments of Mathematics
and Economics from York University and the U of T.
Huaxiong Huang organized the Machine Learning
Graduate Course, the first course of its kind to be
offered through the Fields Institute. It began with
three sessions on the fundamentals of machine
learning led by David Duvenaud and Roger Grosse
(U of T), which were followed by a series of
modules directed by expert guest lecturers from
around the globe, including Geoffrey Hinton.
Professor Huang also organized a special lecture on
Affective Artificial Intelligence and its Applications,
which featured speakers Kang Lee, Xin Gao, Aziz
Guergachi, David Uminsky, and Marc Thiriet from
the Fields CQAM lab on Health Analytics and
Multidisciplinary Modelling. Professor Lee’s session
on emotional intelligence proved particularly
popular and sold-out so quickly that a larger venue