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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. Details can be found at the project pages that will be updated frequently.

Current Lab Members

Our newest lab member.

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

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

Rohan Bhargava [Researcher]
Machine Learning and Robotics

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

Hassan Nikoo [MCS]
Deep learning

Michal Lisicki [MCS]
Image mining, deep learning

Vignesh Babu [MCS]
Adaptive object tracking, robotics

Ranga Rankaduwa [MSC]
Computational Neuroscience and Synaptic Plasticity

Marjan Zamani [MACS]
Application of Deep Learning

Bassey Etim [MACS]
Application of Deep Learning

Luyao Zhan [MCS]
Application of Deep Learning to Bioinformatics

Chun Kwang Tan (Master Exchange Student)
Cognitive Robotics

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Continuing Members

Dr. Dominic Standage
Dr. Jason Satel
Dr. Patrick Connors

Past Lab Members

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