Bio
I am an PhD (CS) student here at UWaterloo. In 2001 I graduated from UBC with
a BASc in Computer Engineering. While I was there, I worked with VLSI cad
design and robotics. One cool project I worked on was a remote surgical device
with force feedback capabilities. I have a couple of years of working
experience, where I worked as the head of the IT department for a company that
deals with providing accurate and realistic real-time battlefield simulation
for the military. The core of the system involved a sophisticated laser
engagement system (similar in concept to laser tag), and this is coupled with
a real-time location and status tracking system.
For my Master's project, I designed a spiking neuron model that modelled human serial
working memory that replicated typical human recall behaviours like primacy and recency
(remembering items at the start and end of a list better than the middle of the list).
Between my Master's and PhD programs, I worked on integrating various models built by
other members of the lab into one gigantic model called Spaun.
My Research Interests
I have a rather wide set of research interests.
Memory (Working & Long-term)
How does the brain remember things, and what sorts of representations are used
to do so. How does the brain integrate the different sensory inputs in working
memory, and what is the underlying structure? How does the brain "decide" what
to put into long-term memory and how does it do it?
General Cognition and Large-scale Model Design
I am interested to study and model how the brain performs tasks like concept
generalization and problem solving. I am also interested in the problem of
integration - to build a system that seamlessly melds sensory input, with
decision making and problem solving, with motor output, in order to perform
highly complex tasks.
Language Learning, Representation, and Processing
Languages come in many forms:
- Written languages: which can be further broken down into logographic (pictorial languages, like Chinese, Japanese), and syllabic (languages like English, French, etc).
- Spoken languages
- Sign languages
And yet the brain is able to make sense of it all. Is there an underlying
general framework that the brain uses to represent these different forms of
languages, or does each form have its own specific framework? Additionally,
how does the brain learn languages? Are multiple sensory inputs required to
learn a language, or is just one sensory input enough?
Previous Projects
A biologically plausible model of memory for serial-order information
Spaun: A large-scale model of the functioning brain
Current Project
General instruction following in a large-scale biologically plausible brain model
Recommended Readings
In search of memory: The emergence of a new science of mind - Eric Kendel
How to build a brain: A neural architecture for biological cognition - Chris Eliasmith
Publications
Theses
Journal Articles
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Yexin Yan,
Terrence Stewart,
Xuan Choo,
Bernhard Vogginger,
Johannes Partzsch,
Sebastian Hoeppner,
Florian Kelber,
Chris Eliasmith,
Steve Furber,
Christian Mayr
(2021)
Comparing Loihi with a SpiNNaker 2 Prototype on Low-Latency Keyword Spotting and Adaptive Robotic Control.
Neuromorphic Computing and Engineering.
Abstract
DOI
External link
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Aaron R. Voelker,
Peter Blouw,
Xuan Choo,
Nicole Sandra-Yaffa Dumont,
Terrence C. Stewart,
Chris Eliasmith
(2021)
Simulating and Predicting Dynamical Systems With Spatial Semantic Pointers.
Neural Computation, 33(8):2033-2067.
Abstract
PDF
DOI
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Peter Duggins,
Terrence C. Stewart,
Xuan Choo,
Chris Eliasmith
(2017)
Effects of Guanfacine and Phenylephrine on a Spiking Neuron Model of Working Memory.
Topics in Cognitive Science.
Abstract
PDF
DOI
External link
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Trevor Bekolay,
James Bergstra,
Eric Hunsberger,
Travis DeWolf,
Terrence C Stewart,
Daniel Rasmussen,
Xuan Choo,
Aaron R. Voelker,
Chris Eliasmith
(2014)
Nengo: A Python tool for building large-scale functional brain models.
Frontiers in Neuroinformatics.
Abstract
PDF
DOI
External link
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Chris Eliasmith,
Terrence C. Stewart,
Xuan Choo,
Trevor Bekolay,
Travis DeWolf,
Yichuan Tang,
Daniel Rasmussen
(2012)
A large-scale model of the functioning brain.
Science, 338:1202-1205.
Abstract
PDF
Poster
DOI
External link
Conference and Workshop Papers
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Trevor Bekolay,
Terrence C. Stewart,
Xuan Choo,
Travis DeWolf,
Yichuan Tang,
Daniel Rasmussen,
Jan Gosmann,
Chris Eliasmith
(2015)
Spaun: A biologically realistic large-scale functional brain model.
In Ontario and Canada Research Chairs Symposium. Council of Ontario Universities.
Abstract
PDF
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Terrence C. Stewart,
Xuan Choo,
Chris Eliasmith
(2014)
Sentence processing in spiking neurons: A biologically plausible left-corner parser.
In 36th Annual Conference of the Cognitive Science Society, 1533–1538. Cognitive Science Society.
Abstract
PDF
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Xuan Choo,
Chris Eliasmith
(2013)
General Instruction Following in a Large-Scale Biologically Plausible Brain Model.
In 35th Annual Conference of the Cognitive Science Society, 322–327. Cognitive Science Society.
Abstract
PDF
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Trevor Bekolay,
Terrence C. Stewart,
Xuan Choo,
Travis DeWolf,
Yichuan Tang,
Daniel Rasmussen,
Chris Eliasmith
(2013)
Spaun: A Large-Scale Model of the Functioning Brain.
In Cheriton Symposium. David R. Cheriton School of Computer Science.
Abstract
PDF
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Terrence C. Stewart,
Xuan Choo,
Chris Eliasmith
(2012)
Spaun: A Perception-Cognition-Action Model Using Spiking Neurons.
In Cognitive Science Society, 1018-1023.
Abstract
PDF
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Terrence C. Stewart,
Xuan Choo,
Chris Eliasmith
(2010)
Symbolic Reasoning in Spiking Neurons: A Model of the Cortex/Basal Ganglia/Thalamus Loop.
In Stellan Ohlsson and Richard Catrambone, editors, 32nd Annual Meeting of the Cognitive Science Society, 1100–1105. Portland, Oregon. Cognitive Science Society.
Abstract
PDF
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Terrence C. Stewart,
Xuan Choo,
Chris Eliasmith
(2010)
Dynamic Behaviour of a Spiking Model of Action Selection in the Basal Ganglia.
In 10th International Conference on Cognitive Modeling.
Abstract
PDF
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Xuan Choo,
Chris Eliasmith
(2010)
A Spiking Neuron Model of Serial-Order Recall.
In Richard Cattrambone and Stellan Ohlsson, editors, 32nd Annual Conference of the Cognitive Science Society. Portland, OR. Cognitive Science Society.
Abstract
PDF
Technical Reports and Preprints