University of Waterloo
University of Waterloo has 261 faculty across 3 departments on GradNova.
Departments
Faculty
M
Research Assistant Professor
Cognitive Management in Wired and Wireless Networks
Machine/deep Learning for Networking, Including Network Security, Encrypted Traffic Classification, and Resource Management in Emerging Networks
Network Softwarization, Including Network Virtualization, Software-Defined Networking, and Network Function Virtualization
Network Security and Intrusion Detection
+4
V
Associate Professor, Teaching Stream and Director, Software Engineering
Identifying Valuable Tools for Teaching, Learning and Assessment
Investigating Innovative Creativity Fostering Techniques for Requirement Elicitation
Some of the Possible Techniques Worth Investigating Are Project-Based Learning, One-On-One Mentoring, Industrial Practicum That Is Designed to Give Students Supervised Practical Application of Concurrently Studied Theories and Concepts, and Simulations to Demonstrate Newly Learned Concepts
Testing and Validation of Educational Techniques to Enhance the Transfer Between the Academic Learning Environment and the Students' Professional Practice
+5
C
Assistant Professor, Teaching Stream and Academic Advisor
G
Associate Professor, Teaching Stream
Gradual Typing: Languages Which Combine Typed and Untyped Code
Just-In-Time Compilation: Compilers Which Compile Code While It's Running, Allowing for Advanced Profiling
Languages and Systems, in Particular Cs442 (programming Languages) and Cs241 (foundations of Sequential Programming)
Security and Verification in Computing
+4
D
Associate Professor, Electrical and Computer Engineering
Applications of Machine Learning in Natural Language Processing (conversational Agents, Grammar Error Correction, Automated Text Editing) and Material Design (bayesian Optimization of Catalysts, Oxygen Carriers and Other Materials to Facilitate Desirable Chemical Reactions for Co2 Conversion and Co2 Capture)
Machine Learning, Including Reinforcement Learning, Federated Learning, Continual Learning, Self-Supervised Learning, Meta Learning, Few Shot Learning, Causal Learning, Uncertainty Quantification and Calibration
Reinforcement Learning in Robotics
Topic Modeling
+3