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Machine Learning and Data Classification

Machine Learning and Data Classification

85 faculty research Machine Learning and Data Classification on GradNova.

O
Omar Montasser

Secondary Faculty, Assistant Professor

Computer Science

Yale University

Adversarial Robustness in Machine Learning
Domain Adaptation and Few-Shot Learning
Imbalanced Data Classification Techniques
Machine Learning and Algorithms
+1
S
Hepatitis B Virus Studies
Hepatitis C Virus Research
Machine Learning and Data Classification
Natural Language Processing Techniques
+1
C
Bayesian Inference
Deep Learning
Machine Learning
Optimization
+5
C
Advanced Graph Theory Research
Complexity and Algorithms in Graphs
Machine Learning and Algorithms
Machine Learning and Data Classification
+1
C
Clayton D Scott

Professor, EECS – Electrical and Computer Engineering; Professor (courtesy), Statistics

Department of Electrical and Computer Engineering

University of Michigan

Machine Learning Theory, Methods, and Applications
Machine Learning Theory, Methods, and Applications.
Machine Learning and Algorithms
Machine Learning and Data Classification
+3
S
Samet Oymak

Associate Professor, EECS – Electrical and Computer Engineering

Department of Electrical and Computer Engineering

University of Michigan

Principled Methods and Theories for Data Science and Machine Learning to Enable Resource Efficiency and Trustworthy Decision-Making
Sparse and Compressive Sensing Techniques
Stochastic Gradient Optimization Techniques
Domain Adaptation and Few-Shot Learning
+2
M
Advanced Bandit Algorithms Research
Complexity and Algorithms in Graphs
Imbalanced Data Classification Techniques
Machine Learning and Algorithms
+1
B
Adversarial Robustness in Machine Learning
Bayesian Modeling and Causal Inference
Machine Learning and Data Classification
Reinforcement Learning in Robotics
+1
S
Machine Learning and Data Classification
Protein Structure and Dynamics
Sparse and Compressive Sensing Techniques
Tensor Decomposition and Applications
+1
R
Experimental Learning in Engineering
Fuzzy Logic and Control Systems
Machine Learning and Data Classification
Neural Networks and Applications
+1
P
Domain Adaptation and Few-Shot Learning
Machine Learning and Data Classification
Multimodal Machine Learning Applications
Natural Language Processing Techniques
+1
B
Bo Liu

Associate Professor, School of Electrical, Computing, and Software Engineering

School of Electrical, Computing, and Software Engineering

University of Arizona

Domain Adaptation and Few-Shot Learning
Face and Expression Recognition
Machine Learning and Data Classification
Machine Learning and Elm
+1
P
Pascal Germain

Département d'informatique et de génie logiciel

Computer Science

Université Laval

Apprentissage Machine
Intelligence Artificielle (ia)
Machine Learning and Algorithms
Domain Adaptation and Few-Shot Learning
+3
A
Adam Klivans

Director of AI Initiatives for the School of Computing, Professor, Admiral B. R. Inman Centennial Chair in Computing Theory #2

Computer Science

The University of Texas at Austin

Machine Learning
Theoretical Computer Science
Machine Learning and Algorithms
Complexity and Algorithms in Graphs
+3
U
Advanced Statistical Methods and Models
Advanced Statistical Modeling Techniques
Control Systems and Identification
Machine Learning and Data Classification
+1
Y
Machine Learning and Data Classification
Scientific Computing and Data Management
Software Engineering Research
I
Human-Computer Interaction
Topic Modeling
Explainable Artificial Intelligence (xai)
Machine Learning and Data Classification
+2
S
Cooperative Communication and Network Coding
Domain Adaptation and Few-Shot Learning
Machine Learning and Data Classification
Privacy-Preserving Technologies in Data
+1
J
Jennifer Dy

COE Distinguished Professor, jointly appointed in Electrical and Computer Engineering & Khoury College of Computer Sciences

Department of Electrical and Computer Engineering

Northeastern University

Computer Vision and Image Processing
Data Mining
Machine Learning
Statistical Pattern Recognition
+5
A
Advanced Neural Network Applications
Adversarial Robustness in Machine Learning
Domain Adaptation and Few-Shot Learning
Machine Learning and Data Classification
+1
A
Andrew Gordon Wilson

Professor of Computer Science and Data Science

Computer Science

New York University

Bayesian Statistics
Machine Learning
Numerical Linear Algebra
Gaussian Processes and Bayesian Inference
+4
D
Dennis Shasha

Silver Professor of Computer Science

Computer Science

New York University

And Puzzles
DNA Computing
Finding Patterns in Time Series
Network Inference and Protein Design for Biology
+5
L
Lisa Hellerstein

Professor of Computer Science and Engineering

Computer Science

New York University

Algorithms and Data Compression
Complexity and Algorithms in Graphs
Machine Learning and Algorithms
Machine Learning and Data Classification
+1
E
Computer-Aided Decision Making
Data Mining
Data Mining Discrete Optimization
Discrete Optimization
+7
2

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