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Shahryar Rahnamayan

Shahryar Rahnamayan
BSc, MSc, PhD (Waterloo), PEng, SMIEEE

Associate Professor

Department of Electrical, Computer and Software Engineering

Faculty of Engineering and Applied Science

Contact information

2000 Simcoe Street North
Oshawa, Ontario L1H 7K4
Office: ACE 20236

905.721.8668 ext. 5730
905.721.3370 (fax)

shahryar.rahnamayan@uoit.ca
http://www.rahnamayan.ca


Research topics

  • Software Engineering
  • Machine Intelligence
  • Opposition-Based Computation
  • Metaheuristics
  • Image Processing and Computer Vision
  • Parallel Processing
  • Multi-Objective and Large-Scale Optimization
  • Simulation of Discrete and Continuous Systems

Education

  • PhD (Systems Design Engineering), University of Waterloo, Canada, 2007
  • MSc (Software Engineering),  2001
  • BSc (Software Engineering),  1998

Courses

Undergraduate-level

  • Introduction to Artificial Intelligence
  • Data Structures
  • Design and Analysis of Algorithms
  • Software Design II
  • Computer and Software Security
  • Software Engineering Systems Design I
  • Software Engineering Systems Design II
  • C++ Programming for Engineers

Graduate-level

  • Advanced Optimization 
  • Opposition-based Soft Computing

Research and expertise

Publications and presentations

  • Selected publications and presentations

    Journal publications

    • F. Khalvati, A. Salmanpour, S. Rahnamayan, H.R. Tizhoosh, “Registration-Based Volume Segmentation of Prostate Gland in T2W MR Images,” Journal of Medical Physics, Sept. 2013 (in press).
    • H. Wang, W. Wang, H. Sun, S. Rahnamayan,“ Firefly Algorithm with Random Attraction,” International Journal of Bio-Inspired Computation, Sept. 2013 (in press).
    • A. Ibrahim, F. Bourennani, S. Rahnamayan, “ Optimization of Photovoltaic Arrays Using Multi-objective Evolutionary Algorithms,” International Journal of Applied Metaheuristic Computing, March 2013 (in press).
    • H. Mushtaq, S. Rahnamayan, A. Siddiqi,“ Color Separation in Forensic Image Processing Using Interactive Differential Evolution,” Journal of Forensic Sciences, Aug. 2013 (in press).
    • H. Wang, H. Sun, C. Li, S. Rahnamayan, J.-S. Pan, “ Diversity Enhanced Particle Swarm Optimization with Neighborhood Search ,” Journal on Information Sciences - Elsevier, Vol. 223, Feb. 2013, pp. 119-135.
    • H. Wang, S. Rahnamayan, Hui Sun, Mahamed G.H. Omran,“ Gaussian Barebones Differential Evolution,” IEEE Transactions on Systems, Man and Cybernetics, Part B, Vol. 43, April 2013, pp. 634-647.
    • A.Darvish, S. Rahnamayan,“Optimal Parameter Setting of Active-Contours Using Differential Evolution and Expert-Segmented Sample Image,” Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol. 16, No. 6, 2012, pp. 677-686.
    • H. Wang, S. Rahnamayan, and S. Zeng, “Generalized Opposition-Based Differential Evolution: An Experimental Study,” International Journal of Computer Applications in Technology (IJCAT), Vol. 43, No. 4, June 2012, pp. 311-319.
    • S. Rahnamayan, G.G. Wang, M. Ventresca, “An Intuitive Distance-Based Explanation of Opposition-Based Sampling,” Journal on Applied Soft Computing - Elsevier, Vol. 12, Issue 9, Sept. 2012, pp. 2828-2839.
    • F. Bourennani, S. Rahnamayan, G. F. Naterer, “Optimal Design Methods for Hybrid Renewable Energy Systems,” International Journal of Green Energy - Taylor & Francis Group (IJGE), 2013 (in press).
    • H.Wang, S. Rahnamayan, “Parallel Differential Evolution with Self – Adapting Control Parameters and Generalized Opposition-Based Learning for Solving High-Dimensional Optimization Problems,”Journal of Parallel and Distributed Computing - Elsevier, 73(1), 2013, pp. 62-73. F. Bourennani, S. Rahnamayan, G. F. Naterer, “OGDE3: Opposition- Based Third Generalized Differential Evolution,” Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol. 16 No. 3, 2012, pp. 469-480.
    • H. Wang, Z. Wu, S. Rahnamayan, C. Lic, S. Zeng, D. Jiang, “Particle Swarm Optimization with Simple and Efficient Neighborhood Search Strategies,” International Journal of Innovative Computing and Applications (IJICA), Vol. 3, No. 2, 2011, pp. 97-104.
    • M. Kazemi, G.G. Wang, S. Rahnamayan, Kamal Gupta, “Metamodel- Based Optimization for Problems With Expensive Objective and Constraint Functions,” ASME Journal of Mechanical Design, Vol. 133, Issue 1, Jan. 2011.
    • W. Wang, H. Wang, S. Rahnamayan, “Improving Comprehensive Learning Particle Swarm Optimizer Using Generalized Opposition-based Learning,” International Journal of Modelling, Identification and Control (IJMIC), Vol. 14, No. 4, 2011, pp. 310-317.
    • H. Wang, Z. Wu, S. Rahnamayan, and Y. Liuc, M. Ventresca, “Enhancing Particle Swarm Optimization by Using Generalized Opposition-based Learning,” Journal on Information Sciences - Elsevier, Vol. 181, Issue 20, Oct. 2011, pp. 4699-4714.
    • H. Wang, Z. Wu, and S. Rahnamayan, “Enhanced Opposition-Based Differential Evolution for Solving High-Dimensional Continuous Optimization Problems,” Special Issue of Soft Computing on Scalability of Evolutionary Algorithms and other Metaheuristics for Large Scale Continuous Optimization Problems, Springer Verlag, Sept. 2010, pp. 1-14.
    • M. Ventresca, S. Rahnamayan, H.R. Tizhoosh, “A Note on Opposition versus Randomness in Soft Computing Techniques,” Journal on Applied Soft Computing - Elsevier, Vol. 10, Mar. 2010, pp. 956-957.
    • S. Rahnamayan, G.G. Wang, “Toward Effective Initialization for Large-Scale Search Spaces,” World Scientific and Engineering Academy and Society, Transactions on Systems, Vol. 8, Issue 3, Mar. 2009, pp. 355-367, ISSN: 1109-2777.
    • S. Rahnamayan, H.R. Tizhoosh, M.M.A Salama, “Automatic Acquisition of Image Filtering and Object Extraction Procedures from Ground-Truth Samples,” Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol. 13, No. 2, Mar. 2009, pp. 115-127.
    • S. Rahnamayan, G.G. Wang, “Solving Large Scale Optimization Problems by Opposition-Based Differential Evolution (ODE),” World Scientific and Engineering Academy and Society, Transactions on Computers, Vol. 7, Issue 10, Oct. 2008, pp. 1792-1804.
    • S. Rahnamayan, H.R. Tizhoosh, M.M.A Salama, “Opposition-Based Differential Evolution,” IEEE Transactions on Evolutionary Computation, Vol. 12, Issue 1, Feb. 2008, pp. 64-79.
    • S. Rahnamayan, H.R. Tizhoosh, M.M.A Salama, “Opposition versus Randomness in Soft Computing Techniques,” Journal on Applied Soft Computing - Elsevier, Volume 8, Mar. 2008, pp. 906-918.
    • S. Rahnamayan, H.R. Tizhoosh, M.M.A Salama, “A Novel Population Initialization Method for Accelerating Evolutionary Algorithms,” Journal on Computers and Mathematics with Applications - Elsevier, Vol. 53, Issue 10, May 2007, pp. 1605-1614

    Books

    • S. Rahnamayan, The Power of Oppositeness in Optimization: Toward Accelerating of Evolutionary Algorithms, Verlag Dr. Muller, May 2009, ISBN: 978-3-639-15511-2; and
    • S. Rahnamayan, Optic Physics Lab Software: Concepts and Applications, Dibagaran Publication, Tehran, Iran, 1997, ISBN: 964-5613-33-7.

    Book chapters

    • F. Bourennani, S. Rahnamayan, Heterogeneous Text and Numerical Data Mining with Possible Applications in Business and Financial Sectors, Semantic Technologies for Business and Information Systems Engineering: Concepts and Applications, IGI Global Publisher, pp. 60-80, 2012.
    • M. Ventresca, S. Rahnamayan, H.R. Tizhoosh, The Structure and Use of Opposition for Decreasing Function Evaluations in Population-based Search, Computational Intelligence in Expensive Optimization Problems, Springer-Verlag, pp.49-71, 2009.
    • S. Rahnamayan, H.R. Tizhoosh, M.M.A Salama, Opposition-Based Differential Evolution, Advances in Differential Evolution, Series: Studies in Computational Intelligence, Springer-Verlag, ISBN: 978-3-540-68827-3, pp. 155-171, 2008.
    • S. Rahnamayan, H.R. Tizhoosh, M.M.A Salama, Differential Evolution via Exploiting Opposite Populations, Oppositional Concepts in Computational Intelligence, Series: Studies in Computational Intelligence, Springer-Verlag, ISBN: 978- 3-540-70826-1, pp. 143-160, 2008.
    • H.R. Tizhoosh, M. Ventresca, S. Rahnamayan, Opposition-Based Computing, Oppositional Concepts in Computational Intelligence, Series: Studies in Computational Intelligence, Springer-Verlag, ISBN: 978-3-540-70826-1, pp. 11-28, 2008.
    • S. Rahnamayan, H.R. Tizhoosh, M.M.A Salama, Automated Snake Initialization for the Segmentation of the Prostate in Ultrasound Images, Springer Lecture Notes in Computer Science Series, ISSN: 0302-9743, pp. 930-937, 2005.

    Conference Papers

    • F. Bourennani, S. Rahnamayan, G. F. Naterer, “Leaders and Speed Constraint Multi-objective Particle Swarm Optimization,” IEEE Congress on Evolutionary Computation, Cancun, Mexico, June 20-23, 2013, pp. 908-915.
    • H. Wang, Z. Wu, X. Zhou, S. Rahnamayan,“Artificial Bee Colony Algorithm with External Archive,” IEEE Congress on Evolutionary Computation, Cancun, Mexico, June 20-23, 2013, pp. 517-521.
    • A. Darvish, S. Rahnamayan, Z. Salami Mohamad, “Interactive Evolutionary- Based Image Thresholding,” Genetic and Evolutionary Computation Conference (GECCO, ACM), July 7-11, 2012, Philadelphia, USA, pp. 501-508.
    • S. Rahnamayan, “Teaching Quality Improvement Based on Data Analysis of Students’ Teaching Evaluations,” 120th Annual Conference & Exposition of American Society for Engineering Education (ASEE), June 23 - 26, 2013 Atlanta, Georgia, USA (submitted).
    • A. Esmailzadeh, S. Rahnamayan, “Center-Point-Based Simulated Annealing,” Canadian Conference on Electrical and Computer Engineering (CCECE, IEEE), April 29 - May 2, 2012, Montreal, Quebec, Canada.
    • S.-M. Mousavi, S. E. Hoque, S. Rahnamayan, I. Dincer, G.F. Naterer, “Optimal Design of Air-Cooling System for Li-Ion Battery in an Electric Vehicle Using Genetic Algorithm,” IEEE Congress on Evolutionary Computation (CEC), June 5-8, 2011, New Orleans, USA, pp. 1848 - 1855.
    • F.S. Al-Qunaieer, H.R. Tizhoosh, S. Rahnamayan, “Multi-resolution Level Set Image Segmentation Using Wavelet,” IEEE International Conference on Image Processing (ICIP), Sept. 11-14, 2011, Brussels, Belgium, pp. 269 - 272.
    • A. Esmailzadeh, S. Rahnamayan, “Enhanced Differential Evolution using center-based sampling,” IEEE Congress on Evolutionary Computation (CEC), June 5-8, 2011, New Orleans, USA, pp. 2641 - 2648.
    • A. Esmailzadeh, S. Rahnamayan, “Opposition-Based Differential Evolution with Protective Generation Jumping,” Symposium Series on Computational Intelligence (SSCI), April 11-15, 2011, Paris, France, pp. 1-8.
    • Z. Salami Mohamad, A. Darvish, S. Rahnamayan, “Eye Illusion Enhancement Using Interactive Differential Evolution,” IEEE Symposium Series on Computational Intelligence (SSCI), April 11-15, 2011, Paris, France, pp. 1-7.
    • H. Wang, S. Rahnamayan, Z. Wu, “Adaptive Differential Evolution with Variable Population Size for Solving Large-Scale Problems,” IEEE Congress on Evolutionary Computation (CEC), June 5-8, 2011, New Orleans, USA, pp. 2626 - 2632.
    • F. Zhu, H. Wang, S. Rahnamayan, Z. Wu, “Accelerating Opposition-Based Differential Evolution Using Graphics Processing Units for Solving Large-Scale Problems,” IEEE Symposium Series on Computational Intelligence (SSCI), April 11- 15, 2011, Paris, France, pp. 2618-2625.
    • H. Wang, Z. Wu, S. Rahnamayan, J. Wang, “Diversity Analysis of Opposition- Based Differential Evolution - An Experimental Study,” 5th International Symposium on Intelligence Computation and Applications (ISICA), October 22-24, 2010, Wuhan, China. LNCS 6382, pp. 95-102.
    • F. Bourennani, R. Rizvi, S. Rahnamayan, “Optimal Photovoltaic Solar Power Farm Design Using Differential Evolution Algorithm,” 10th International Conference on Clean Energy (ICCE), September 15-17, 2010, Famagusta, N. Cyprus, ref. 7-20, pp. 1-8.
    • F. Bourennani, S. Rahnamayan, G. F. Naterer, “Applications of Multi-Objective Optimization to Energy System Design,” the 10th International Conference on Clean Energy (ICCE), September 15-17, 2010, Famagusta, N. Cyprus, ref. 6-05, pp. 1-8.
    • S. Rahnamayan, Zaid S. Mohamad, “Breast Ultrasound Segmentation Based on Evolutionary Optimization of Image Processing Chain,” IEEE International Workshop on Real-Time Measurement, Instrumentation and Control (RTMIC), June 25-26, 2010, Oshawa, Canada, pp. 9.1-9.9.
    • A. Esmailzadeh, S. Rahnamayan, “Fighting Noise with Noise: DE with Individuals Shaking to Tackle Noisy Problems,” IEEE World Congress on Computational Intelligence (WCCI), July 18-23, 2010, Barcelona, Spain, pp. 2514-2522.
    • F.S. Al-Qunaieer, H.R. Tizhoosh, S. Rahnamayan, “Opposition Based Computing - A Survey,” IEEE International Joint Conference on Neural Networks (IJCNN), July 18-23, 2010, Barcelona, Spain, pp. 3183-3189.
    • H. Wang, Z. Wu, S. Rahnamayan, and D. Jiang, “Sequential DE Enhanced by Neighborhood Search for Large Scale Global Optimization,” IEEE Congress on Evolutionary Computation, Special Session: Large Scale Global Optimization (CEC), July 18-23, 2010, Barcelona, Spain, pp. 4056-4062.
    • F.S. Al-Qunaieer, H.R. Tizhoosh, S. Rahnamayan, “An Oppositional Fuzzy Image Thresholding,” IEEE International Conference on Fuzzy Systems (FUZZIEEE), July 18-23, 2010, Barcelona, Spain, pp. 2513-2519.
    • F. Bourennani, S. Rahnamayan, G. F. Naterer, “Methods of Optimization Based Design and Controls for Renewable Energy Systems,” 10th International Conference on Clean Energy (ICCE), September 15-17, 2010, Famagusta, N. Cyprus, ref. 7-08, pp. 1-8.
    • Kazemi, G.G. Wang, S. Rahnamayan, Kamal Gupta, “Constraint Importance Mode Pursuing Sampling for Continuous Global Optimization,” ASME Design Automation Conference (DAC), August 15-18, 2010, Montreal, Quebec, Canada, pp. 1-10.
    • H. Wang, Z. Wu, S. Rahnamayan, “Differential Evolution Enhanced by Neighborhood Search,” IEEE World Congress on Computational Intelligence (WCCI), July 18-23, 2010, Barcelona, Spain, pp. 1-8.
    • S. Rahnamayan, “Towards Specialized Engineering Majors Based on Distributed e-Learning,” Canadian Engineering Education Association’s First Annual Conference (CEEA), June 7-9, 2010, Queens University - Kingston, Ontario, Canada.
    • S. Rahnamayan, “Quizzes or Exams, Which one Should be More Challenging?” Canadian Engineering Education Association’s First Annual Conference (CEEA), June 7-9, 2010, Queens University - Kingston, Ontario, Canada.
    • H. Wang, Z. Wu, S. Rahnamayan, and L. Kang, “A Scalability Test for Accelerated DE Using Generalized Opposition-Based Learning,” 9th International Conference on Intelligent Systems Design and Applications (ISDA-2009), Pisa, Italy, Nov. 2009, pp. 1090 - 1095.
    • S. Rahnamayan, G.G. Wang, “Center-Based Sampling for Population-Based Algorithms,” IEEE Congress on Evolutionary Computation (CEC-2009), Trondheim, Norway, 18-21 May, 2009, pp. 933 - 938.
    • S. Rahnamayan, G.G.Wang, “ Center-Based Initialization for Large-Scale Black-Box Problems,” 8th International Conference on Artificial Intelligence, Knowledge Engineering, and Data Bases (AIKED-2009), Cambridge, UK, 21-23 Feb., 2009, pp. 531-541.
    • S. Rahnamayan, G.G. Wang, “Investigating in Scalability of Opposition-Based Differential Evolution,” 8th International Conference on Simulation, Modeling and Optimization (SMO-2008), Santander, Cantabria, Spain, September 23-25, 2008, pp. 105-111.
    • S. Rahnamayan, H.R. Tizhoosh, “Image Thresholding Using Micro Opposition-Based Differential Evolution (Micro-ODE),” IEEE World Congress on Computational Intelligence (WCCI-2008), Hong Kong, June 2008, pp. 1409-1416.
    • S. Rahnamayan and Paul Dieras, “Efficiency Competition on N-Queen Problem: DE vs. CMA-ES,” IEEE Canadian Conference on Electrical and Computer Engineering (CCECE-2008), Niagara Falls, Canada, May 2008, pp. 33-36.
    • S. Rahnamayan, H.R. Tizhoosh, M.M.A Salama, “Quasi-Oppositional Differential Evolution,” IEEE Congress on Evolutionary Computation (CEC-2007), Singapore, Sep. 2007, pp. 2229-2236.
    • S. Rahnamayan, H.R. Tizhoosh, M.M.A Salama, “Opposition-Based Differential Evolution (ODE) With Variable Jumping Rate,” IEEE Symposium on Foundations of Computational Intelligence, Honolulu, Hawaii, USA, April 2007, pp. 81-88.
    • S. Rahnamayan, H.R. Tizhoosh, M.M.A. Salama, “Weighted Voting-Based Robust Image Thresholding,” 13th IEEE International Conference on Image Processing (ICIP-2006), Atlanta, GA, USA, Oct. 2006, pp. 1129-1132.
    • S. Rahnamayan, “A New Initialization Scheme for Evolutionary Optimization Methods,” 10th World Multi Conference on Systems, Cybernetics and Informatics (WMSCI-2006), Orlando, USA, July 2006.
    • N.N. Kachouie, P. Fieguth, S. Rahnamayan, “An Elliptical Level Set Method for Automatic TRUS Prostate Image Segmentation,” 6th IEEE International Symposium on Signal Processing and Information Technology (ISSPIT-2006), Vancouver, Canada, Aug. 2006, pp. 191-196.
    • E. Jonasson and S. Rahnamayan, “Differential Evolution with Fittest Individual Local Tuning,” 10th World Multi Conference on Systemics, Cybernetics and Informatics (WMSCI-2006), Orlando, USA, July 2006.
    • S. Rahnamayan, H.R. Tizhoosh, M.M.A Salama, “Opposite of Random Number Instead of Second Random Number,” Abstract in 6th Annual MOPTA Conference, Modeling and Optimization: Theory and Applications, University of Waterloo, Waterloo, Canada, July 2006 (abstract).
    • S. Rahnamayan, H.R. Tizhoosh, M.M.A Salama, “Opposition-Based Evolutionary Algorithms,” Abstract in 6th Annual MOPTA Conference, Modeling and Optimization: Theory and Applications, University of Waterloo, Waterloo, Canada, July 2006 (abstract).
    • S. Rahnamayan, H.R. Tizhoosh, M.M.A. Salama, “Image Thresholding Using Differential Evolution,” International Conference on Image Processing, Computer Vision, and Pattern Recognition (IPCV-2006), Las Vegas, USA, June 2006, pp. 244-249.
    • S. Rahnamayan, H.R. Tizhoosh, M.M.A. Salama, “Opposition-Based Differential Evolution Algorithms,” IEEE Congress on Evolutionary Computation (CEC-2006), Vancouver, July 2006, pp. 2010-2017.
    • S. Rahnamayan, H.R. Tizhoosh, M.M. A. Salama, “Opposition-Based Differential Evolution for Optimization of Noisy Problems,” IEEE Congress on Evolutionary Computation (CEC-2006), Vancouver, July 2006, pp. 1865-1872.
    • S. Rahnamayan, H.R. Tizhoosh, M.M.A Salama, “Recognition of Subjective Objects Based on One Gold Sample,” 5th WSEAS International Conference on Signal, Speech and Image Processing, Corfu, Greece, Aug. 2005, pp. 309-314.
    • S. Rahnamayan, H.R. Tizhoosh, M.M.A Salama, “Optimization of Object Extraction Based on One User-Prepared Sample,” Abstract in 5th Annual MOPTA Conference, Modeling and Optimization: Theory and Applications, University of Windsor, Windsor, Canada, July 2005 (abstract).
    • S. Rahnamayan, H.R. Tizhoosh, M.M.A Salama, “Robust Object Segmentation Using Genetic Optimization of Morphological Processing Chains,” 5th WSEAS International Conference on Signal, Speech and Image Processing, Corfu, Greece, Aug. 2005, pp. 248-253.
    • S. Rahnamayan, H.R. Tizhoosh, M. Salama, “Learning Image Filtering from a Gold Sample Based on Genetic Optimization of Morphological Procedure,” 7th International Conference on Adaptive and Natural Computing Algorithms (ICANNGA-2005), SpringerComputerScience, Coimbra, Portugal, March 2005, pp. 478-481.

    Patent

    • A Modality-Independent, Self-Adaptive Segmentation System for Extraction of One Object of Interest in Medical Images. Nov., 2007 (US provisional patent).
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