Cyber-Physical Systems Internet of Things Performance Energy Informatics
Academic Employment
Education
My research focuses on the design and implementation of intelligent networked systems using control theory, optimization, and machine learning. I use these techniques to address systems challenges in different domains, from sensor networks and IoT to smart buildings and energy systems.
For more information please visit my website.
This is part 2 of a 2 sequence intensive introduction to Computing Science. Part 2 expands to add object-oriented programming, a higher level language (Python), and more complex algorithms and data structures such as shortest paths in graphs; caching, memoization, and dynamic programming; client-server style computing; recursion; and limited distributed of computation tasks between the Arduino platform and the traditional desktop in order to explore design tradeoffs. Prerequisite: CMPUT 274. Note: this course is taught in studio-style, where lectures and labs are blended into 3 hour sessions, twice a week. Enrollment is limited by the capacity of the combined lecture/lab facilities. Credit cannot be obtained for CMPUT 275 if one already has credit for any of CMPUT 174, 175, or 201, except with permission of the Department.
Winter Term 2022This topics course is designed for new course offerings that may be offered in a given term. Prerequisites are determined by the instructor in the course outline. See Note (3) above.
Fall Term 2021