University of Toronto and Toronto Rehabilitation Institute
Pervasive Computing, Smart Homes, Machine Learning, Optimization, Internet of Things
Raisul’s research interests include the areas of machine learning, optimization, computer vision, and affective computing. He has about 10 years of research experience of developing algorithms for smart homes. He investigated the methods proposed for smart homes to provide users context-aware automated or assistive services. He developed an algorithm, named SPEED, which incorporates smartness into the smart homes, provisioning a better control of the home appliances to ensure comfort, safety, to improve indoor environment and energy efficiency, and to provide in-home healthcare support. His research also addressed developing the exact and heuristic algorithms to optimize energy cost in smart homes. Raisul received his Ph.D. in Electrical and Computer Engineering from Carleton University. He obtained his M.Sc. in Microengineering and Nanoelectronics from the National University of Malaysia (UKM) and B.Sc. in Computer Science and Engineering from Shahjalal University of Science and Technology, Bangladesh. Currently, he is conducting research on emotionally intelligent prompting systems for smart homes and smart workplaces for the individuals with cognitive disabilities.
- Ubiquitous robotics to support older adutls with dementia
- An Emotionally Intelligent Prompting System for the Employees with Intellectual and Development Disabilities
- Alam, M. R., St-Hilaire, M., and Kunz, T. (2017). An optimal P2P energy trading model for smart homes in the smart grid. Energy Efficiency. Accepted on May 2017, 19 pages.
- Alam, M. R., St-Hilaire, M., and Kunz, T. (2016). Computational methods for residential energy cost optimization in smart grids – A survey. ACM Computing Surveys. 49 (1). Article 2. 34 pages.
- Alam, M. R., Reaz, M. B. I., and Ali, M. A. M. (2012). A review of smart homes – past, present, and future. IEEE Transactions on Systems, Man, and Cybernetics -Part C: Applications and Reviews. 42 (6):1190–1203. (Currently among the top 50 most popular and most cited papers of this journal)
- Alam, M. R., Reaz, M. B. I., and Ali, M. A. M. (2012). SPEED: An inhabitant activity prediction algorithm for smart homes. IEEE Transactions on Systems, Man, and Cybernetics – Part A: Systems and Humans. 42 (4): 985–990. (Currently among the top 50 most popular and most cited papers of this journal)
- Alam, M. R., Reaz, M. B. I., and Ali, M. A. M. (2011). A spatiotemporal model of human circadian rhythm in smart homes. Artificial Intelligence Review. 25 (9): 788–798.