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Welcome to the Laboratory for Hierarchical Anticipatory Learning (HAL Lab). We are a lab at Dalhousie University whose research interests are primarily in the fields of Computational Neuroscience and Machine Learning.

Current Lab Members


Dr. Thomas Trappenberg [Prof] 
tt@cs.dal.ca http://cs.dal.ca/~tt 
Computational Neuroscience, Machine Learning, Cognitive Robotics

Dr. Abraham Nunes [Research Associate]
Computational Psychiatry

Farzaneh Sheikhnezhad Fard [Ph.D] 
Cognitive Robotics

Paul Hollensen [Ph.D.]
Machine Learning and Computational Neuroscience

Yoshimasa Kubo [Ph.D.]
Machine Learning and Computational Neuroscience

Stuart Mcilroy [Ph.D.]
Machine Learning and Computational Neuroscience

Ranga Rankaduwa [MSC]
Computational Neuroscience and Synaptic Plasticity

Mike Trevenar [MCS]
Machine Learning and AI

Francesco Usai [PhD psych comprehensive]
Deep learning of brain imaging data

Past Lab Members


Chun Kwang Tan (Master Exchange Student)
Cognitive Robotics

Dr. Hossein Parvar [Adjunct Prof] 
Machine Learning and Intelligent Systems

Vignesh Babu [MCS 2015]
Adaptive object tracking, robotics

Hassan Nikoo [MCS 2015] 
Deep learning for Time Series

Marjan Zamani [MACS 2015]
Application of Deep Learning

Bassey Etim [MACS 2015]
Application of Deep Learning

Rohan Bhargava [MCS 2014] 
Robotics

Michal Lisicki [MCS, 2014] 
Image mining, deep learning

Dan Su [MACS, 2014]
Robotic coverage path planing

Karthik Damodaran [MACS, 2014]
Sublingual microcirculation analysis

Rohan Bhargava [MCS, 2014] 
Adaptive motion models for AUVs

Patrick Connor [Ph.D 2013]
Biological motivated learning with small data, Basal Ganglia, Reinforcement Learning

Rober Boshra [Honors, 2013] 
Machine learning in single trial EEG analysis

Jake Kroeker [Honors, 2013]
Reinforcement Learning

Jason Satel [Ph.D, 2013]
IOR, EEG, Neural Field Theory

Warren Connors [MCS, 2012]
Neural Fields and Cognitive Robotics

Leah Brown [NSERC USRA, 2011] 
lbrown@cs.dal.ca
Machine Learning and Robotics

Ian Graven [NSERC USRA, 2011]
Machine Learning and Robotics

Michal Lisicki [RA, 2011]
Machine Learning and Robotics

Paul Hollensen [BCS Honours, 2010]
Restricted Boltzmann Machines

Misha Denil [BCS Honours, 2010]
Machine Learning

Dr. Dominic Standage [Ph.D., 2007]
Mechanisms of short term and long term memory in cortex: neural fields and synaptic plasticity

Bijan Farhoudi [BCS Honours, 2007]
Point attractor networks with resetricted weights

Sajiya Jail [Guest Researcher, 2005-2006]
Spike-timimg dependent plasticity

Matthew Boardman [MCS, 2006]
Extrinsic regularization in parameter optimization for support vector machines

Jesse Rusak [BCS Honours, 2006]
Setup and analysis of a brain-computer interface using support vector machines for single-trial classification

Jason Satel [MCS, 2005]
Motivationally-based learning mechanisms and the dynamics of saccade initiation

Kan Yang [MCS, 2005]
An internet-based electronic voting system with balanced complexity and security

Jie Ouyang [MCS, 2004]
Improved ICAIVS algorithm with mutual information

Patrick Mahaux [MEC, 2004]
Client Profile Model: How to Identify Training Candidates with the least chance of Employment

Daniel Rogers [BCS Honours, 2004]
Exploration of the Techniques, Tools, and Requirements of Electronic Voting Systems

Alicia Grosvenor [MEC, 2004]
Elliptic Curve cryptography: A viable alternative for maintaining security in low precessing and low memory computing environments

Shelagh Gregory [EMEC, 2003]
Should Canada use biometric identifiers if implementing a national identification system?

Dr. Carrie Gates [MSC, 1995]
The application of neural networks to predicating the conductivity of water

George MacLennan [MSC, 1994]
Evolutionary Design of neural networks