I accomplished a great deal during my undergraduate degree at Queen’s, however it does not compare to how much I learned, accomplished, and enjoyed my time spent completing my Masters of Engineering (M.Eng). I believe that my studies allowed me an excellent opportunity to explore a range of topics far greater than could have been accomplished through an Masters of Applied Science (MASc). This included opportunities to take classes in diverse and unrelated fields, including Machine Learning, High-Performance Computing, Software Re-Engineering, Software Design Recovery, Bioinformatics and Computer & Network security. Though taking M.Eng courses greatly contributed to my own knowledge, my MASc allowed me the ability to focus my efforts on the research of PROCAM systems, and through my PhD, contribute my own ideas to the academic community. My current research is in PROCAM Systems, under Dr. Michael Greenspan in the RCVLab, where it is our goal to enable a new generation of interactive projector technology. Due to the fast rate of innovation in our discipline, some ideas are no longer novel, but to the credit of our discipline there is always room for and new areas for innovation. It is my hope that our work in PROCAM system will contribute towards a more interactive and immersive world.
- Machine Vision
- Intelligent Systems
- Machine Learning
- High Performance Computing
- Malware Analysis and Network Security
- 2019 – Present >> Doctor of Philosophy
- 2016 – 2019 >> Masters of Applied Science
- 2014 – 2016 >> Masters of Engineering
- 2010 – 2014 >> Bachelors in Electrical & Computer Engineering
 I. J. Maquignaz. Imperceptible Pattern Embedding: Structured Light Steganography For Augmented Reality Applications. Queen’s University, 2019, QSpace, http://hdl.handle.net/1974/26263.
 I. J. Maquignaz, J. Malcolm, and M. Greenspan, Active Correspondences Projector-Camera (Procam) Sensors. OWCV, 2021.