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Amir Shabani

Lecturer, P.Eng.
Sustainable Energy Engineering

Education

  • Ph.D., System Design Engineering, University of Waterloo, 2011
  • M.Sc., Electrical and Electronics Engineering, Iran University of Science and Technology, 2004
  • B.Sc., Electrical and Electronics Engineering, Iran University of Science and Technology, 2001

Industrial and research interests

  • Artificial Intelligence, Machine Learning, Computer Vision
  • Sustainable Interactive Intelligent System Design
  • Affective Computing, Interactive Robotics
  • Smart City, Smart Connected Buildings, Smart Homes
  • Internet of Things (IoT, Industry 4.0 and Industry 5.0)

Teaching interests

  • System Design and Computing: Artificial Intelligence, Machine Learning, Computer Vision, Data Analytics, Robotics, Data Structure, Algorithm Design, and Programming
  • Electronics and Embedded Systems: Data Communnication, Networking, Internet of Things, Embedded Systems, Signals and Systems, Image Processing, Electronic Circuits and Systems, Instrumentation and Control, Mechatronic Systems

Recently taught courses

  • SEE 231 - Electronic Devices and Systems
  • SEE 332 - Power Systems Design and Analysis
  • SEE 333 - Network and Communication Systems
  • SEE 431 - Signals and Systems

Selected recent publications

  • T. Anjum, S. Lawrence, A. Shabani, â€� Augmented Reality and Affective Computing on the Edge Makes Social Robots Better Companions for Older Adults â€œ, International Conference on Robotics, Computer Vision, and Intelligent Systems, Valletta, Malta, 2021. 
  • T. Anjum, S. Lawrence, A. Shabani, â€� Efficient Data Augmentation within Deep Learning Framework to Improve Cross-Dataset Facial Emotion Recognitionâ€�, 25th International Conference on Image Processing, Computer Vision, Pattern Recognition, Las Vegas, USA, 2021.
  • S. Lawrence, T. Anjum, A. Shabani, â€�Improved Deep Neural Network with Age Augmentation for Facial Emotion Recognition in Social Companion Roboticsâ€�, Journal of Computational Vision and Imaging Systems, 2020.
  • S. Latif, A. Shabani, A. Esser, A. Martkovich, “Analytics of Residential Electrical Energy Profileâ€�, IEEE Canadian Conference on Electrical and Computer Eng., Windsor, Canada, 2017.
  • C. Luppe, A. Shabani, “Towards Reliable Intelligent Occupancy Detection for Smart Building Applicationsâ€�, IEEE Canadian Conference on Electrical and Computer Eng. Windsor, Canada, 2017.
  • A. Forest, M. Dallard, A. Shabani, “An Optimized Platform for Performance Evaluation of Solar Battery Chargersâ€�, IEEE Canadian Conference on Electrical and Computer Eng., Windsor, Canada, 2017
  • A. Forest, A. Shabani, “A Novel Approach in Smart Ventilation Using Wirelessly Controllable Dampersâ€�, IEEE Canadian Conference on Electrical and Computer Eng., Windsor, Canada, 2017.
  • M. Dallard, A. Forest, A. Shabani, “Design of a Portable Smart Connected Solar-Powered Charger for Consumer Electronicsâ€�, IEEE Canadian Conference on Electrical and Computer Eng., Windsor, Canada, 2017.
  • A.H. Shabani, J.S. Zelek, D.A. Clausi, “Multiple scale-specific representations for improved action classificationâ€�, Journal of Pattern Recognition Letters, Jan. 2013.
  • A.H. Shabani, D.A. Clausi, J.S. Zelek, “Evaluation of local spatio-temporal salient feature detectors for human action recognitionâ€�, IEEE Conf. On Computer and Robot Vision, Toronto, May 2012.
  • A.H. Shabani, J.S. Zelek, D.A. Clausi, “Regularized gradient kernel anisotropic diffusion for better image filteringâ€�, IEEE Conf. On Computer and Robot Vision, Toronto, May 2012.
  • A.H. Shabani, P. Matsakis, “Efficient computation of objects’ spatial relations in digital imagesâ€�, IEEE Canadian Conf. On Electrical and Computer Engineering, Montreal, April 2012.
  • A.H. Shabani, D.A. Clausi, J.S. Zelek “Improved spatio-temporal salient feature detection for action recognitionâ€�, British Machine Vision Conference, Dundee, UK, Sep. 2011.
  • A.H. Shabani, J.S. Zelek, D.A. Clausi, “Robust local video event detection for action recognitionâ€�, Neural Information Processing Sys. (NIPS)–MLAT Workshop, Whistler, Canada, Dec. 2010.
  • M. H. Ghaeminia, A.H. Shabani, and S.B. Shokouhi, “Two-level parallel histogram of appearance for better human tracking in Videoâ€�, IEEE Machine Vision and Image Processing Conference, Isfahan, Oct. 2010.
  • A.H. Shabani, J.S. Zelek and D.A. Clausi, “Human action recognition using salient opponent-based motion featuresâ€�, IEEE Canadian Conference on Computer and Robot Vision, Ottawa, Canada, May 2010.
  • A.H. Shabani, M.H. Ghaeminia, and S.B. Shokouhi, “Human tracking using spatialized multi-level histogramming and mean shiftâ€�, IEEE Canadian Conf. on Computer and Robot Vision, Ottawa, Canada, 2010.
  • M.H. Ghaeminia, A.H. Shabani, and S.B. Shokouhi, “Adaptive motion model for human tracking using Particle Filterâ€�, International Conference on Pattern Recognition, Istanbul, Turkey, Aug. 2010.
  • M.J. Gangeh, A.H. Shabani, and M.S. Kamel, “Nonlinear scale-space theory in texture classification using multiple classifier systemsâ€�, International Conf. on Image Analysis and Recognition, Portugal, June 2010.
  • A.H. Shabani, D.A. Clausi, J.S. Zelek, “Towards robust 3D spatio-temporal interest point detection for human action recognitionâ€�, IEEE Canadian Conference on Computer and Robot Vision, Kelowna, Canada, May 2009.
  • A.H. Shabani, S.B. Shokouhi,â€� Self-recalibration of a 3D Laser Scannerâ€�, IEEE Conference in Electrical Engineering (ICEE), Zanjan, Iran, May 2005.
  • A.H. Shabani, S.B. Shokouhi,â€� Fuzzy thinning in 3D laser scanning using structured lightâ€�, IEEE Machine Vision, Image Processing and Application (MVIP), Tehran, Iran, Feb. 2005.
  • A.H. Shabani and S.B. Shokouhi, "A new automatic calibration algorithm for 3-D optical scanners", IEEE Machine Vision, Image Proc. and Application (MVIP), Tehran, Iran, Feb. 2005.
  • A.H. Shabani, M. Farrokhi, and S.B. Shokouhi, "A new method of edge detection based on the classical and fuzzy methods", IEEE Conference on Electrical Engineering (ICEE), Shiraz, Iran, May 2003.

Courses

Future courses may be subject to change.