You are now in the main content area

Dr. Naimul Khan

Naimul Khan
Assistant Professor
BSc, MSc, PhD, PEng
416-979-5000 ext. 6479

Areas of Academic Interest

Machine learning

Medical imaging


Computer vision

Augmented reality

Virtual reality


Year University Degree
2014 Toronto Metropolitan University PhD
2010 University of Windsor MSc
2008 Bangladesh University of Engineering and Technology BSc

Courses Taught

Course Code Course
ELE 725 Basics of Multimedia Systems
COE 318 Software Systems
DG 8002 Digital Media Environments


Where Naimul Khan is today is a product of chance, beginning during his master’s studies. It was then that he attended a professor’s dinner party and happened to overhear a conversation about a research chair who was running a large-scale multimedia lab at Ryerson. Khan hadn’t considered graduate studies at Ryerson, but that research chair would become his PhD supervisor. “He invited me to visit his virtual reality lab, which he uses to wow his PhD students,” says Khan, laughing. “I was sold right away.”

During Khan’s first year at Ryerson, yet another chance encounter charted the path of his research. A five-minute conversation about manual image processing techniques used in cranial drilling sparked something in the PhD candidate. “I was still scratching my head about what topic to do. That’s where I got the idea that we can actually automate this process using machine learning and artificial intelligence.”

Now co-director of the very lab that brought him to Ryerson, Khan’s research in the areas of augmented reality, virtual reality and machine learning speaks to his interest in practical implementation. “I can not only develop the algorithms but also demonstrate them. Augmented reality and virtual reality work as the medium to show what algorithms can do.”

 Naimul's LinkedIn Profile

 Naimul's Twitter Profile (external link) 

Professor Naimul Khan looks at a piece of equipment in the Ryerson Multimedia Research Laboratory.

“I’ve always been interested in the practical aspect of industry collaboration and making an immediate impact, not just blue skies research.”

  • Best Paper Award, IEEE International Symposium on Multimedia, 2017
  • OCE TalentEdge Postdoctoral Fellowship, 2014-2016
  • Ontario Graduate Scholarship, 2013-2014
  • Queen Elizabeth II Scholarship in Science & Technology, 2012-2013
  • B. Courtney, N.M. Khan, N.A, Kotzev. Systems and Methods for Noise Reduction in Imaging. US Patent 62/463,431, 2019.
  • N.M. Khan, M. Hon, and N. Abraham. Transfer Learning with Intelligent Training Data Selection for Prediction of Alzheimer’s Disease. IEEE Access, 2019.
  • N.M. Khan, R. Ksantini, and L. Guan. A Novel Image-centric Approach Towards Direct Volume Rendering. ACM Transactions on Intelligent Systems and Technology, 9(4):2-18, 2018.
  • N.M. Khan, M. Kyan, and L. Guan. Intuitive Volume Exploration through Spherical Self-Organizing Map and Color Harmonization. Neurocomputing,147:160-173, 2015.
  • N.M. Khan, R. Ksantini, I.S. Ahmad, and L. Guan. Covariance-guided One Class Support Vector Machine. Pattern Recognition, 47(6):2165-2177, 2014.
  • Senior Member, IEEE
  • Local Arrangements Chair, International Humanitarian Technology Conference (IHTC) 
  • Program Committee Member, ACM Multimedia, ICME and ICANN