DICE Team

1. Peckham, T. and Hilderman, R.J. "Evaluation of a Model of Human-Computer Interaction and the Incidence of Repetitive Strain Injuries." Technical Report CS-03-01, Department of Computer Science, University of Regina, February, 2003, 32 pages.
2. Peckham, T. and McCalla, G. Mining Reading Comprehension Within Educational Objective Frameworks, 7th International Conference on Educational Data Mining (London, England 2014).
3. Peckham, T. and McCalla, G. Mining Student Behavior Patterns in Reading Comprehension Tasks. In Proceedings of the 5th International Conference on Educational Data Mining (Chiana, Greece 2012), Springer, 87-94.
4. Peckham, T. and McCalla, G. Modeling Cognitive Strategies. Workshop on Self Regulated Learning in 11th International Conference on Intelligent Tutoring Systems (Chiana, Greece 2012).
5. Peckham, T. Detection of Cognitive Strategies in Reading Comprehension. In Proceedings of 11th International Conference on Intelligent Tutoring, 2012.
6. Hilderman, R.J. and Peckham, T. "A Statistically Sound Alternative Approach to Mining Contrast Sets." Proceedings of the 4th Australasian Data Mining Conference (AusDM'05), Sydney, Australia, December, 2005, pp. 157-172.
7. Hilderman, R.J., Peckham, T., and Totten, E.C.A. "A Keyboard-Based Graphical Web Browser Interface." Proceedings of the 16th British Human Computer Interaction Conference (HCI'02) Volume 2, London, England, September, 2002, pp. 14-17.
8. Prystupa D., Peckham T., Eichendorf R., Chartrand B. Optical and Acoustic Characterizations of Grain Kernels. In proceedings of 2nd Canadian Wheat Symposium Saskatoon, Saskatchewan, June 2014.
9. Peckham T. Applied Research in Healthcare and Healthcare Instruction. Canadian Applied and Industrial Mathematics Society Symposium, Saskatoon Saskatchewan June 2014.

1. Hilderman, R.J., and Peckham, T. "Statistical Measures as Heuristics for Mining Potentially Interesting Contrast Sets." In Guillet, F. and Hamilton, H.J. (eds.), Quality Measures in Data Mining, Springer, 2006.

Profile

Dr. Cyril Coupal is a seasoned computer science professional with extensive teaching and research experience. He received his PhD in computer science with specialization in data science and machine learning.

Dr. Coupal taught computer science at the University of Saskatchewan and Computer Systems Technology program courses at Saskatchewan Polytechnic. In November 2016, he joined Digital Integration Centre of Excellence (DICE) as a research manager where he has worked on various projects, all of which contain strong data and machine learning components. He currently leads project management efforts and serves the principal investigator on multiple research projects.

Notably, Dr. Coupal has made significant contributions to the field of applied research.

1. Richard Dosselmann, Prakher, Nathaniel Vallee, Ying Ye, Roy Ampoloquio, Leigh Lamontagne, Vignesh Shankar, Syed Aamir Ali Shah, Divyesh Patel, Cyril Coupal (2024) “Detection of Lentil Grading Factors using Machine Learning,” Springer Agricultural Research journal (awaiting publication)
2. Premkumar MBBS MD M.Sc. (Med.Ed.) Ph.D., Kalyani and Coupal, Cyril (2008) 'Rules of engagement-12tips for successful use of "clickers" in the Classroom', Medical Teacher, 30:2, 146 – 149
3. "The Value of Agile in Experiential Learning of Software Development," 2007, Agile 2007 Conference Proceedings, Washington DC
4. "How an agile process had the right properties for a chemistry lab project," 2007, Agile Development, winter2007
5. "Introducing Agile into a Software Development Capstone Project," 2005, Agile 2005 Conference Proceedings, Denver Co.
6. "A Constraint-Driven Approach to Object-Oriented Design Representation," 1991, Artificial Intelligence InDesign '91 Conference, Edinburgh, Scotland
7. "Collaborative Documentation Using a Wiki", TLt Summit 2008, Joint Conference of Campus Saskatchewan and the Educational Technology Consortium, May 14-16, 2008http://www.tltsummit.ca/
8. "Student Response Systems: Pedagogical Principles for Learner Engagement," SLICE OFLIFE 2007 Conference Pre-workshops, Salt lake City, Utah http://slice.utah.edu/2007/schedule/preworkshop_wed.htm
9. "Open/UP and say Ahhh! Agile/Iterative Development meets PMO," CANHEIT 2007, May 27-30 Waterloo, Canada, https://fortuna.uwaterloo.ca/canheit/index.php
10. "Become Engaged With the Click of a Button," TLt-IT Summit, 2007, Saskatoon, SK, http://www.tlt-itsummit2007.ca/program/
11. "Experiences with Lecture Capture as a Learning Resource," TLt-IT Summit, 2007, Saskatoon, SK,   http://www.tlt-itsummit2007.ca/program/
12. "Elluminate-ing your learners," TLt 2006, Saskatoon, SK, http://www.campussaskatchewan.ca/tlt/program.asp

Profile

Dr. Reza Gharraei holds a PhD in Mechanical Engineering -  Energy Conversion, from the University of Tabriz, Iran (2011). He also holds an M.Sc. in Mechanical Engineering with a specialization in energy conversion from Amirkabir University of Technology (2004).

He has published more than 50 research papers in peer-reviewed journals and conference proceedings and holds two patents. Dr. Reza has supervised more than 50 graduate and undergraduate students

With over two decades of experience, Dr. Gharraei has served as a faculty member in the Department of Mechanical Engineering at Azarbaijan Shahid Madani University (2011–2019), worked as a scientific consultant for Alikan Farayand Co. (2016–2019), and as a mechanical engineer at Azarshimikaran Co. (2006–2010). Since October 2023, he has been contributing to advanced research initiatives at DICE.

Outside of work, Dr. Gharraei enjoys hiking and classical music.

Research interest

Dr. Gharraei's research interests include renewable energy systems, Improvement of energy systems' performance, reduction of water consumption in industrial processes and particulate flows. He is focused on developing innovative solutions to optimize energy systems and minimize environmental impact.

Selected awards

Outstanding faculty member - 2013-2014 Academic year at Azarhaijan Shshid Madani University.

1. Golestani, S., & Makaroff, D. (2024, September). Device-specific anomaly detection models for IoT systems. In Proceedings of the IEEE Conference on Communications and Network Security (CNS). Taipei, Taiwan.
2. Golestani, S., & Makaroff, D. (2024, April). Exploring unsupervised one-class classifiers for lightweight intrusion detection in IoT systems. In Proceedings of the 20th IEEE International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT). Abu Dhabi, UAE.
3. Amoozegar, M., & Golestani, S. (2024). Response surface methodology for behavior analysis and performance improvement of gravitational search algorithm. Journal of Electrical and Computer Engineering Innovations (JECEI).
4. Golestani Najafabadi, S., Naji, H. R., & Mahani, A. (2013, December). Sybil attack detection: Improving security of WSNs for smart power grid application. In Proceedings of the Smart Grid Conference (SGC). Tehran, Iran.
5. Golestani Najafabadi, S., Naji, H. R., & Mahani, A. (2012, December). A review on Sybil attack detection methods in wireless sensor networks [In Persian]. In Proceedings of the National Conference of New Ideas on Electrical Engineering (NCNIEE). Isfahan, Iran.
6. Karimi, M., Naji, H. R., & Golestani Najafabadi, S. (2013). A novel energy efficient clustering protocol for wireless sensor networks [In Persian]. Journal of Information Engineering (JIEng), 1(3–4), 195–208.
7. Karimi, M., Naji, H. R., & Golestani, S. (2012, May). Optimizing cluster-head selection in wireless sensor networks using genetic algorithm and harmony search algorithm. In Proceedings of the 20th Iranian Conference on Electrical Engineering (ICEE2012). Tehran, Iran.