PODCAST/VIDEO INTERVIEWS by Stephen Ibaraki
Alexander Wong, P.Eng.: Canada Research Chair in Artificial Intelligence and Medical Imaging, co-director of the Vision and Image Processing Research Group, associate professor in the Department of Systems Design Engineering at the University of Waterloo, and Chief Scientist at DarwinAI
This week, Stephen Ibaraki has an exclusive interview with Alexander Wong.
Alexander
Wong,
P.Eng.,
is
currently
the
Canada
Research
Chair
in
Artificial
Intelligence
and
Medical
Imaging,
Member
of
the
College
of
the
Royal
Society
of
Canada,
co-director
of
the
Vision
and
Image
Processing
Research
Group,
an
associate
professor
in
the
Department
of
Systems
Design
Engineering
at
the
University
of
Waterloo,
and
Chief
Scientist
at
DarwinAI.
He
had
previously
received
the
B.A.Sc.
degree
in
Computer
Engineering
from
the
University
of
Waterloo,
Waterloo,
ON,
Canada,
in
2005,
the
M.A.Sc.
degree
in
Electrical
and
Computer
Engineering
from
the
University
of
Waterloo,
Waterloo,
ON,
Canada,
in
2007,
and
the
Ph.D.
degree
in
Systems
Design
Engineering
from
the
University
of
Waterloo,
ON,
Canada,
in
2010.
He
was
also
an
NSERC
postdoctoral
research
fellow
at
Sunnybrook
Health
Sciences
Centre.
He
has
published
over
520
refereed
journal
and
conference
papers,
as
well
as
patents,
in
various
fields
such
as
computational
imaging,
artificial
intelligence,
computer
vision,
and
multimedia
systems.
In the area of computational imaging, his focus is on integrative computational imaging systems for biomedical imaging (inventor/co-inventor of Correlated Diffusion Imaging, Compensated Magnetic Resonance Imaging, Spectral Light-field Fusion Micro-tomography, Compensated Ultrasound Imaging, Coded Hemodynamic Imaging, High-throughput Computational Slits, Spectral Demultiplexing Imaging, and Parallel Epi-Spectropolarimetric Imaging).
In the area of artificial intelligence, his focus is on operational artificial intelligence (co-inventor/inventor of, Generative Synthesis, evolutionary deep intelligence, Deep Bayesian Residual Transform, Discovery Radiomics, and random deep intelligence via deep-structured fully-connected graphical models).
He has received numerous awards including three Outstanding Performance Awards, a Distinguished Performance Award, an Engineering Research Excellence Award, a Sandford Fleming Teaching Excellence Award, an Early Researcher Award from the Ministry of Economic Development and Innovation, a Best Paper Award at the NIPS Workshop on NIPS Workshop on Transparent and Interpretable Machine Learning (2017), a Best Paper Award at the NIPS Workshop on Efficient Methods for Deep Neural Networks (2016), two Best Paper Awards by the Canadian Image Processing and Pattern Recognition Society (CIPPRS) (2009 and 2014), a Distinguished Paper Award by the Society of Information Display (2015), three Best Paper Awards for the Conference of Computer Vision and Imaging Systems (CVIS) (2015,2017,2018), Synaptive Best Medical Imaging Paper Award (2016), two Magna Cum Laude Awards and one Cum Laude Award from the Annual Meeting of the Imaging Network of Ontario, CIX TOP 20 (2017), Technology in Motion Best Toronto Startup (2018), Top Ten Startup at AutoMobility LA (2018), AquaHacking Challenge First Prize (2017), Best Student Paper at Ottawa Hockey Analytics Conference (2017), and the Alumni Gold Medal.
TO WATCH THE VIDEO INTERVIEW, CLICK ON THIS MP4 file link