Main Page
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
Dr. Thomas Trappenberg [Prof]
tt@cs.dal.ca http://cs.dal.ca/~tt
Computational Neuroscience, Machine Learning, Cognitive Robotics
Dr. Hossein Parvar [Postdoctoral Fellow]
Machine Learning and Intelligent Systems
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 Traynor [MCS]
Machine Learning for Natural Language Processing
Francesco Usai [PhD psych comprehensive]
Deep learning of brain imaging data
Junliang Luo [Honors student]
Deep learning of 3D microscopic data
Peter Lee [Honors student]
Deep learning of medical 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
