Majid Komeili

I am an Assistant Professor in the School of Computer Science and Institute for Data Science at Carleton University. I perform fundamental and applied research in machine learning.

Prospective Students

I have a few different projects I’m looking to admit Ph.D. and Masters students. --Read more.

Biography

Before joining Carleton, I was a postdoctoral fellow at University of Toronto working jointly with Toronto Rehabilitation Institute and Vector Institute under supervision of Dr. Frank Rudzicz. I received my Ph.D. from Department of Electrical and Computer Engineering at University of Toronto under supervision of Dr. Dimitrios Hatzinakos.

Email

firstname.lastname@carleton.ca

Address

5436 Herzberg Laboratories, Carleton University
1125 Colonel By Drive, Ottawa
Ontario, Canada

Phone

613-520-2600 ext. 6098

Research Interests

My research interests are in Machine Learning and related areas in Speech/Language processing and Computer Vision. More specifically, I am interested in interpretable machine learning, deep neural networks and transfer learning.

Students

Grad Students

  • Abhijeet Chauhan, Master’s
  • Seyed Omid Davoudi, PhD
  • Mohammad Nokhbeh Zaeem, Master’s
  • Undergrad Students

  • Jacob Danovitch, Fall 2019, Honors Thesis.
  • Layne Koftinow-Mikan, Fall 2019, Honors Project.
  • Xiyi Liu, Fall 2019, Honors Project.
  • Past Students

  • Galen O'Shea, Summer 2019, Honors Project.
  • Lucas Colwell, Summer 2019, DSRI internship.
  • Kyle Causton, Summer 2019, Honors Project (with Oliver).
  • Yu Yamanaka, Winter 2019, Honors Project.
  • Selasi Kudolo, Winter 2019, Honors Project.
  • Luc Gruska, Winter 2019, Honors Project.
  • Liheng He, Winter 2019, Honors Project.
  • Joining/Volunteering

    Applying for MSc or PhD:

    MSc and PhD applicants who are interested in my research are encouraged to contact me via email.

    Prerequisites: A good candidate should have background in probability and linear algebra, and have had courses in Machine Learning or related areas including Computer Vision and Natural Language Processing.

    Prospective MSc and PhD students who are applying to the School of Computer Science at Carleton University and are interested in my research are encouraged to indicate my name as their Preferred Research Supervisor.

    Teaching

  • COMP 5900: Advanced Machine Learning - Fall 2019.
  • COMP 4900: Introduction to Machine Learning - Winter 2020.   (Topics).
  • DATA 5000: Introduction to Data Science - Winter 2020.
  • COMP 5900: Machine Learning for Healthcare - Winter 2019.   (Outlines, List of the suggested papers ).
  • Publications

    Peer-Reviewed Journal Papers

      M. Komeili, N. Armanfard, D. Hatzinakos, (2019), “Multiview Feature Selection for Single-view Classification”, Revision requested, IEEE Transactions on Pattern Analysis and Machine Intelligence.

      M. Komeili, C. Pou-Prom, D. Liaqat, K. C. Fraser, M. Yancheva, F. Rudzicz, (2019), “Talk2Me: Automated Linguistic Data Collection for Personal Assessment”, PLoS One, pdf, code.

      N Armanfard, M. Komeili, JP Reilly, J Connoly, (2019), “A Machine Learning Framework for Automatic and Continuous MMN Detection with Preliminary Results for Coma Outcome Prediction”, IEEE Journal of Biomedical and Health Informatics, vol. 23, issue 4, pp. 1794 -1804.

      S. J. Haghighi, M. Komeili, D. Hatzinakos, H. El-Beheiry, (2018), “40-Hz ASSR for Measuring Depth of Anaesthesia During Induction Phase”, IEEE Journal of Biomedical and Health Informatics, vol. 22, issue 6, pp. 1871 - 1882.

      M. Komeili, N. Armanfard, D. Hatzinakos, (2018), “Liveness Detection and Automatic Template Updating using Fusion of ECG and Fingerprint”, IEEE Transactions on Information Forensics & Security, vol. 13, issue 7, pp. 1810 - 1822. pdf.

      N. Armanfard, J. P. Reilly, M. Komeili, (2018), “Logistic Localized Modeling of the Sample Space for Feature Selection and Classification”, IEEE Transactions on Neural Networks and Learning Systems, vol. 29, issue 5, pp. 1396 - 1413.

      M. Komeili, W. Louis, N. Armanfard, D. Hatzinakos, (2017), “Feature Selection for Non-stationary Data: Application to Human Recognition using Medical Biometrics”, IEEE Transactions on Cybernetics, vol. 48, issue 5, pp. 1446 - 1459. pdf

      N. Armanfard, J. P. Reilly, M. Komeili, (2016), “Local Feature Selection for Data Classification”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 38, no. 6, pp. 1217-1227.

      W. Louis, M. Komeili, D. Hatzinakos, (2016), “Continuous Authentication using One Dimensional Multi-Resolution Local Binary Patterns”, IEEE Transactions on Information Forensics & Security, vol. 11, no. 12, pp 2818-2832.

      N. Armanfard, M. Komeili, E. Kabir, (2012), “TED: A Texture-Edge Descriptor for Pedestrian Detection in Video Sequences”, Pattern Recognition, vol. 45, no.3, pp. 983-992.

      N. Armanfard, M. Komeili, E. Kabir, (2010), “A Novel Descriptor for Pedestrian Detection in Video Sequences” , International Journal of Information & Communication Technology, vol.2, no.2, pp. 1-8.

      M. Komeili, N. Armanfard, E. Kabir, (2009), “A Fuzzy Approach for Measuring Features Reliabilities in Particle Filtering Framework”, International Journal of Information & Communication Technology, vol. 1, no. 4, pp. 107-115.

       

    Patents

      M. Komeili, N. Armanfard, D. Hatzinakos, “An Expert System for Fingerprint Spoof Detection” International application number CA2019050141, Patent Cooperation Treaty (PCT), Feb. 2019.

      N. Armanfard, M. Komeili, J. P. Reilly, John F. Connolly, “Expert System for Automatic, Continuous Coma Patient Assessment and Outcome Prediction” U.S. Provisional Patent, USPTO serial no. 62/509,986, May 2017.

       

    Peer-Reviewed Conferences Papers

      N. Armanfard, M. Komeili, A. Mihailidis (2018), “Development of a Smart Home Package for Unobtrusive physiological Monitoring”, IEEE. 40th International Engineering in Medicine and Biology Conference, United States.

      A. Kushki, M. Komeili, S. Panahandeh, E. Anagnostou, J. Lerch. (2018), “Examining Associations Between Brain Morphology and Social Function in ASD, ADHD, OCD, and typical development using Machine Learning: Analysis of POND Network Data”, INSAR 2018, International Society for Autism Research, Netherlands.

      M. Komeili, W. Louis, N. Armanfard, D. Hatzinakos, (2016), “Human Recognition using Electrocardiogram Signals: From Rest to Exercise”, Electrical and Computer Engineering (CCECE), IEEE 29th Canadian Conference on, Vancouver, Canada.

      N. Armanfard, M. Komeili, J. P. Reilly, John F. Connolly, (2016), “Automatic and continuous assessment of ERPs for Mismatch Negativity detection”, IEEE Engineering in Medicine and Biology Society (EMBC), 38th Annual International Conference of the, Orlando, FL, USA.

      S. J. Haghighi, M. Komeili, D. Hatzinakos, (2016), “Predicting the Depth of Anaesthesia with 40-Hz ASSR”, Electrical and Computer Engineering (CCECE), IEEE 29th Canadian Conference on, Vancouver, Canada.

      N. Armanfard, M. Komeili, J. P. Reilly, L. Pino, (2016), “Vigilance lapse identification using sparse EEG electrode arrays”, Electrical and Computer Engineering (CCECE), IEEE 29th Canadian Conference on, Vancouver, Canada.

      W. Louis, M. Komeili, D. Hatzinakos, (2016), “Real-time Heartbeat Outlier Removal in Electrocardiogram (ECG) Biometric System”, Electrical and Computer Engineering (CCECE), IEEE 29th Canadian Conference on, Vancouver, Canada.

      M. Komeili, N. Armanfard, D. Hatzinakos, A. N. Venetsanopoulos, (2015), “Feature Selection from Multisession Electrocardiogram Signals for Identity Verification”, Electrical and Computer Engineering (CCECE), 2015 IEEE 28th Canadian Conference on, Halifax, Canada.

      M. Komeili, N. Armanfard, M. Valizadeh, E. Kabir, (2009), “Robust Proposal Distribution for Adaptive Visual Tracking in a Particle Filtering Framework”, IEEE International Conference on Advances in Computational Tools for Engineering Applications, Zouk Mosbeh, Lebanon.

      M. Komeili, N. Armanfard, M. Valizadeh, E. Kabir, (2009), “Feature Integration for Adaptive Visual Tracking in a Particle Filtering Framework”, IEEE 14th International CSI Computer Conference, Tehran, Iran.

      M. Komeili, M. Valizadeh, N. Armanfard, E. Kabir, (2009), “An Optimal Fuzzy System for Feature Reliability Measuring in Particle Filter-Based Object Tracking”, IEEE 14th International CSI Computer Conference, Tehran, Iran.

      N. Armanfard, M. Komeili, M. Valizadeh, E. Kabir, (2009), “Effective Hierarchical Background Modeling and Foreground Detection in Surveillance Systems”, IEEE 14th International CSI Computer Conference, Tehran, Iran.

      M. Valizadeh, M. Komeili, N. Armanfard, E. Kabir, (2009), “Degraded Document Image Binarization Based on Combination of Two Complementary Algorithms”, IEEE International Conference on Advances in Computational Tools for Engineering Applications, Zouk Mosbeh, Lebanon.

      M. Valizadeh, M. Komeili, N. Armanfard, E. Kabir, (2009), “A Contrast Independent Algorithm for Adaptive Binarization of Degraded Document Images”, IEEE 14th International CSI Computer Conference, Tehran, Iran.

      N. Armanfard, M. Komeili, M. Valizadeh, E. Kabir, S. Jalili, (2009), “A Non-Parametric Pixel-Based Background Modeling for Dynamic Scenes”, IEEE International Conference on Advances in Computational Tools for Engineering Applications, Zouk Mosbeh, Lebanon.

      N. Armanfard, M. Valizadeh, M. Komeili, E. Kabir, (2009), “Document Image Binarization by Using Texture-Edge Descriptor”, IEEE 14th International CSI Computer Conference, Tehran, Iran.

      M. Valizadeh, N. Armanfard, M. Komeili, E. Kabir, (2009), “A Novel Hybrid Algorithm for Binarization of Badly Illuminated Document Images”, IEEE 14th International CSI Computer Conference, Tehran, Iran.

      N. Armanfard, M. Komeili, E. Kabir, (2008), “TED: A Texture-Edge Descriptor Based on LBP for Pedestrian Detection”, IEEE International Symposium on Telecommunications (IST2008), Tehran, Iran, This Paper Was Awarded as the Best Paper of IST2008.

      M. Komeili, N. Armanfard, E. Kabir, (2008), “A Fuzzy Approach for Multi-Feature Pedestrian Tracking with Particle Filter”, IEEE International Symposium on Telecommunications (IST2008), Tehran, Iran.

      M. Komeili, N. Armanfard, E. Kabir, (2008), “Adaptive Visual Tracking by Decision Level Fusion of Features in A Particle Filter Framework”, 5th Iranian Conference on Machine Vision and Image Processing, Tabriz, Iran.

      N. Armanfard, M. Komeili, E. Kabir, (2008), “Efficient Nonparametric Background Modeling of Dynamic Scenes”, 5th Iranian Conference on Machine Vision and Image Processing, Tabriz, Iran.

      M. Komeili, E. Kabir, (2008), “Robust Color-Based Pedestrian Tracking in Varying Illumination Environments”, 16th Iranian Conference on Communication, Thran, Iran.

    Contact

    Address:
    5436 Herzberg Laboratories,
    Carleton University
    1125 Colonel By Drive, Ottawa
    Ontario, Canada

    Phone: 613-520-2600 ext. 6098

    Email: firstnameDOTlastname@carleton.ca