Dr. Naimul Khan
Areas of Academic Interest
|2010||University of Windsor||MSc|
|2008||Bangladesh University of Engineering and Technology||BSc|
|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.”
“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