Pouya Mehrannia is a Lecturer in the Electrical and Computer Engineering department at the University of Waterloo. He received his Ph.D. in Electrical and Computer Engineering from the University of Waterloo working in the Centre for Pattern Analysis and Machine Intelligence (CPAMI), and his M.Sc. and B.Sc. in Electrical and Computer Engineering from University of Tehran. He has done two industrial postdocs at the University of Waterloo working on Automatic Speaker Recognition (ASR) and Driver Behavior Learning (DBL). Pouya’s research focusses on applications of artificial intelligence (AI) in Autonomous Vehicles, Road Traffic Safety, Natural Language Processing, and Smart Environments.
Courses:
- ECE457A - Adaptive and Cooperative Algorithms
- This course addresses search algorithms, game playing, constraints satisfaction, meta-heuristics, evolutionary computing methods, swarm intelligence, ant-colony algorithms, particle swarm methods, adaptive and learning algorithms and the use of these algorithms in solving continuous and discrete problems that arise in engineering application
- Taught in Spring 2019, Fall 2020, Fall 2021, Spring 2022, Fall 2022
- This course addresses search algorithms, game playing, constraints satisfaction, meta-heuristics, evolutionary computing methods, swarm intelligence, ant-colony algorithms, particle swarm methods, adaptive and learning algorithms and the use of these algorithms in solving continuous and discrete problems that arise in engineering application
- ECE457B - Fundamentals of Computational Intelligence
- This course introduces novel approaches for computational intelligence based techniques including knowledge-based reasoning, expert systems, fuzzy inferencing and connectionist modeling based on artificial neural networks. The focus is on the use of soft computing approaches to deal effectively with real world complex systems for which their mathematical or physical models are either non-tractable or are difficult to obtain
- Taught in Winter 2023
- This course introduces novel approaches for computational intelligence based techniques including knowledge-based reasoning, expert systems, fuzzy inferencing and connectionist modeling based on artificial neural networks. The focus is on the use of soft computing approaches to deal effectively with real world complex systems for which their mathematical or physical models are either non-tractable or are difficult to obtain
- ECE659 - Intelligent Sensors & Wireless Sensor Networks
- This course is concerned with recent developments in intelligent sensors and wireless sensor networks. It covers theoretical models, and design principles; and explores the latest development and open research issues in wireless sensor network algorithms, protocols, architectures, and applications. By taking this course, students will learn the fundamental issues encountered in designing and analyzing intelligent sensors and sensor networks (mobile and stationary), with emphasis on mission critical application
- Taught in Spring 2023
- This course is concerned with recent developments in intelligent sensors and wireless sensor networks. It covers theoretical models, and design principles; and explores the latest development and open research issues in wireless sensor network algorithms, protocols, architectures, and applications. By taking this course, students will learn the fundamental issues encountered in designing and analyzing intelligent sensors and sensor networks (mobile and stationary), with emphasis on mission critical application
- ECE493 - Special Topics in ECE: IoT signal processing
- This course is intended to introduce the importance of IoT in our society, the current components of typical IoT devices and trends for the future. Students will learn various IoT applications of signal processing and how design considerations, constraints, and interfacing between the physical world and the devices are dealt with. They will also learn how design trade-offs between hardware and software are managed. The course will also cover other important topics such as device management and networking, security, dependability and maintainability.
- Taught in Spring 2023
- This course is intended to introduce the importance of IoT in our society, the current components of typical IoT devices and trends for the future. Students will learn various IoT applications of signal processing and how design considerations, constraints, and interfacing between the physical world and the devices are dealt with. They will also learn how design trade-offs between hardware and software are managed. The course will also cover other important topics such as device management and networking, security, dependability and maintainability.
