Lab Members

The Neurocognitive Computing Lab has the lofty goal of reverse-engineering the brain. We want to explain behaviour and cognition in mechanistic terms. Here is the team that is making it happen (in alphabetical order for each category).

Director

Jeff Orchard

Associate Professor

Lab Director

jorchard@uwaterloo.ca

Postdoctoral Fellows

Dr. Madeleine Bartlett

Postdoctoral Fellow

Reinforcement Learning

m2bartle@uwaterloo.ca

Dr. Michael Furlong

Postdoctoral Fellow

TBD

michael.furlong@uwaterloo.ca

PhD Students

Nicole Dumont

PhD Candidate

Spatial Semantic Pointers, SLAM

ns2dumont@uwaterloo.ca

Ehsan Ganjidoost

PhD Candidate

Predictive coding networks

eganjido@uwaterloo.ca

webpage

Evangelia Kryoneriti

PhD Student
Lab-Meeting Manager

Vision, neural netowrks

ekryoner@uwaterloo.ca

Nolan Shaw

PhD Student

Neural learning in competitive environments

nolan.shaw@uwaterloo.ca

Jeremy Zheng

PhD Student

jeremy.zheng@uwaterloo.ca

Master’s Students

Brian Cechmanek

MMath Student (part-time)

GANs, camouflage

bcechmanek@uwaterloo.ca

Michael Karras

MMath Student

Vision
(co-supervised with Olga Veksler)

mekarras@uwaterloo.ca

Mallory Snow

MMath Student

Predictive-Coding Hopfield Networks

m5snow@uwaterloo.ca

Other Affiliates

Dr. Terry Stewart

Research Officer, National Research Council

Collaborator, and co-PI

Dr. Lin Wang

Professor, Univ. of Jinan, China

Collaborator, and past postdoctoral fellow at Waterloo

Past Members

• Alex van de Kleut, MMath (Computer Science), Winter 2021
  Thesis: Learning-Free Methods for Goal Conditioned Reinforcement Learning from Images

• Wei Sun, MMath (Computer Science), Spring 2020
  Thesis: Decay Makes Supervised Predictive Coding Generative

• Haris Zahid, Undergrad RA (Computer Science), Winter 2020
  Generative Predictive Coding networks

• Nolan Shaw, MMath (Computer Science), Fall 2019
  Thesis: The Computational Advantages of Intrinsic Plasticity in Neural Networks

• Neil Liu, Undergrad RA (Computer Science), Spring 2019
  Predictive Coding Networks

• Mike Bian, Undergrad RA (Computer Science), Fall 2018
  Bidirectional Equilibrium Propagation

• Ronak Predeep, Undergrad RA (Computer Science), Fall 2018
  High-Performance Neural Network Implementations

• Ahmed Khan, MMath (Computer Science), 2018
  Thesis: Bidirectional Learning in Recurrent Neural Networks Using Equilibrium Propagation

• Rey Wiyatno, Undergrad RA (Mechatronics Eng), Fall 2017
  Style Memory in Neural Networks

• Louis Castricato, Undergrad RA (Computer Science), Spring 2017
  Combatting Adversarial Inputs using a Predictive-Estimator Network

• Paulo Pacheco, PhD candidate (Computer Science)
  Interpretability of Neural Representations

• Dong Wang, Visiting Scholar
  Assistant Professor, University of Jinan, China
  Nonlinear Neuron Models

• Eric Hunsberger, PhD (Systems Design Engineering), 2017
  (Co-supervised with Chris Eliasmith, Systems Design Engineering)
  Thesis: Spiking Deep Neural Networks

• Peng Wu, Visiting Scholar, Feb-July 2017
  Assistant Professor, University of Jinan, China
  Using Flexible Neural Trees to Seed Backpropagation

• Oscar Yeung (Co-op student), May-Aug 2017
  Course Content Developer (CS 370, “Numerical Computation”)

• David Xu, MMath (Computer Science), 2016
  Thesis: Biologically Plausible Neural Learning using Symmetric Predictive Estimators

• Andrew Clappison, Summer Research Assistant, April-Aug 2016
  Symmetric Predictive Coding Networks

• Lin Wang, Postdoctoral Fellow, March 2015-Feb 2016
  The Evolution of Neural Learning

• Cameron Seth, Co-op Undergrad Research Assistant, May-Aug 2015
  Training Feedback Perception Networks

• Shahed Shahir, PhD (Electrical & Computer Engineering), 2015
  (Co-supervised with Safieddin Safavi-Naeini, E&CE)
  Thesis: Near-Field Scattering Tomography System for Object Imaging and Material Characterization

• Oliver Trujillo, MMath (Computer Science), 2014
  (Co-supervised with Chris Eliasmith, Systems Design Engineering)
  Thesis: A Spiking Neural Model of Episodic Memory Encoding and Replay in Hippocampus

• Patrick Ji, MMath (Computer Science), 2014
  Thesis: Generalized Strategies for Path Integration using Neural Oscillators

• Michael Yang, Undergraduate RA (Computer Science), Sept-Dec 2012
  Topic: Neural Oscillators

• Yanwei Wang, PhD (Applied Math), 2011
  Thesis: Efficient Stockwell Transform with Applications to Image Processing

• Michael Lam, MMath (Computer Science), 2011
  Thesis: Retinotopic Preservation in Deep Belief Network Visual Learning

• Hwa Young Kim, MMath (Computer Science), 2009
  Thesis: Registering a Non-Rigid Multi-Sensor Ensemble of Images

• Maja Omanovic, MMath (Computer Science), 2006
  Thesis: Matching of Dental X-rays for Human Forensic Identification

• Alexei Ramotar, MMath (Computer Science), 2006
  Thesis: General Geometry Computed Tomography Reconstruction