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Domain Adaptation and Few-Shot Learning

Domain Adaptation and Few-Shot Learning

198 faculty research Domain Adaptation and Few-Shot Learning on GradNova.

C
Domain Adaptation and Few-Shot Learning
Machine Fault Diagnosis Techniques
Reinforcement Learning in Robotics
Reliability and Maintenance Optimization
+1
F
Computational Fluid Dynamics
Propulsion
Turbomachinery
Topic Modeling
+4
A
Control, Robotics and Dynamical Systems
Reinforcement Learning in Robotics
Machine Learning and Algorithms
Robotic Path Planning Algorithms
+2
S
Domain Adaptation and Few-Shot Learning
Remote Sensing and Lidar Applications
Remote Sensing in Agriculture
Smart Agriculture and AI
+1
N
Domain Adaptation and Few-Shot Learning
Model Reduction and Neural Networks
Smart Grid Energy Management
Sparse and Compressive Sensing Techniques
+1
F
Advanced Image and Video Retrieval Techniques
Chromatography in Natural Products
Domain Adaptation and Few-Shot Learning
Phytochemicals and Antioxidant Activities
+1
D
Advanced Control Systems Optimization
Advanced Neural Network Applications
Domain Adaptation and Few-Shot Learning
Reinforcement Learning in Robotics
+1
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
T
Tom McCoy

Secondary Faculty, Assistant Professor

Computer Science

Yale University

Domain Adaptation and Few-Shot Learning
Language, Metaphor, and Cognition
Multimodal Machine Learning Applications
Natural Language Processing Techniques
+1
K
Domain Adaptation and Few-Shot Learning
Natural Language Processing Techniques
Neural Networks and Applications
Speech Recognition and Synthesis
+1
A
Anthony Sicilia

Tenure Track Faculty - Assistant Professor

Computer Science

West Virginia University

Domain Adaptation and Few-Shot Learning
Multimodal Machine Learning Applications
Natural Language Processing Techniques
Speech and Dialogue Systems
+1
N
AI for Healthcare
Computer Vision
Multimodal Machine Learning Applications
Surgical Simulation and Training
+3
C
Collaborative Machine Learning
Large Language Models
Learning From Limited Data
Machine Learning
+5
J
Deep Learning
Deep Reinforcement Learning
Machine Learning
Neural Networks
+6
R
Robin Jia

Assistant Professor of Computer Science

Computer Science

University of Southern California

Adversarial Robustness in Machine Learning
Domain Adaptation and Few-Shot Learning
Multimodal Machine Learning Applications
Natural Language Processing Techniques
+1
R
Advanced Neural Network Applications
Domain Adaptation and Few-Shot Learning
Generative Adversarial Networks and Image Synthesis
Parallel Computing and Optimization Techniques
+1
H
Computer Vision
Data Mining
Deep Learning
Machine Learning
+5
F
Optimization and Graph Theory
Out-Of-Distribution Generalization
Trustworthy Machine Learning
Domain Adaptation and Few-Shot Learning
+4
U
The Philosophical and Technical Differences Between AI-Generated and Human-Generated Content
Generative Adversarial Networks and Image Synthesis
Advanced Image and Video Retrieval Techniques
Domain Adaptation and Few-Shot Learning
+2
A
Algorithmic Fairness
Bio-Inspired Neural Architectures
Deep Learning Theory
Lifelong Learning
+8
Y
Advanced Neural Network Applications
Adversarial Robustness in Machine Learning
Anomaly Detection Techniques and Applications
Domain Adaptation and Few-Shot Learning
+1
P
Pei Zhang

Associate Professor, EECS – Electrical and Computer Engineering

Department of Electrical and Computer Engineering

University of Michigan

"structures as Sensors," Which Utilizes the Physical Properties of Devices and Structures (e.g. Cars, Buildings, Rooms) as a Sensor to Discover Physical Information That Surrounds Them (e.g. People, Roads, Animals)
Remote-Sensing Image Classification
Domain Adaptation and Few-Shot Learning
Advanced Neural Network Applications
+2
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
G
Grant Van Horn

Assistant Professor (On leave through Spring 2027)

Computer Science

University of Massachusetts Amherst

Machine Learning
Species Distribution and Climate Change
Domain Adaptation and Few-Shot Learning
Advanced Image and Video Retrieval Techniques
+2
2

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