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Computer Science

Computer Science

University of Toronto

Computer Science at University of Toronto has 123 faculty on GradNova.

Faculty

R
Autonomous Vehicles
Computer Vision
Machine Learning
Robotics
K
Assistive Technology
Context-Aware Computing
Human-Computer Interaction
Input Sensors
+9
S
Distributed Computing: Algorithms and Lower Bounds for Distributed Computing Problems
Theoretical Computer Science
Distributed Systems and Fault Tolerance
Optimization and Search Problems
+3
R
Circuit Complexity
Complexity Theory
Pseudorandomness and Derandomization
Theoretical Computer Science
+5
L
Statistical Genetics
S
Bilingualism
Cognitive Modelling of Language Acquisition and Processing
Computational Linguistics and Natural Language Processing
Cross-Linguistic Semantic Typology
+6
A
Cryptography
Foundations of Cryptography
Pseudorandomness
Secure Multiparty Computation
+6
R
Civic Technology
Computer Supported Cooperative Work (cscw)
Crisis Informatics
Critical Design
+9
K
Ar/vr
Artistic Rendering and Fabrication
Character Animation
Computer Graphics
+7
F
Active Semi-Supervised Learning
Computer Vision
Decision-Making Under Uncertainty
Field Robotics
+12
O
Theory and Machine Learning
N
Computational Economics
Fair Algorithmic Decision-Making
Game Theory & Social Choice
Incentives in Multi-Agent Systems Including Blockchain and Machine Learning Environments
+8
K
Mathmatical Analysis
Numerical Analysis
Numerical Linear Algebra
Partial Differential Equations
+8
B
Applied Machine Learning
Computer Systems
Field Studies
File and Storage Systems
+8
S
Algebraic Complexity Theory
Complexity Theory
Discrete Geometry
Error Correcting Codes
+6
G
Computer Architecture
Fault-Injection Attacks
Fuzzing
Hardware Security
+12
S
Algorithmic Problems From Statistics and Machine Learning
Approximation Algorithms
Design of Fast Algorithms, Particularly for Graph Problems and Optimization
Numerical Linear Algebra
+7
T
Systems
Cryptography and Data Security
Advanced Malware Detection Techniques
Cryptographic Implementations and Security
+2
C
Collaborative Machine Learning
Large Language Models
Learning From Limited Data
Machine Learning
+5
T
Complexity Theory
Differential Privacy and Fairness
Machine Learning Theory
Proof Complexity
+6
G
Computational Linguistics and Natural Language Processing
Mathematical Linguistics
Spoken Language Processing
Natural Language Processing Techniques
+4
G
Approximate Computing
Cloud Computing
Compilers
Computer Architecture
+11
C
Active Learning
Crowdsourced User Studies for Visualization
Human-Computer Interaction
Information Visualization
+7
A
Combinatorial Optimization
Computational High-Dimensional Geometry
Discrepancy Theory
Privacy
+6
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