GradNova

Machine Learning and Algorithms

208 faculty research Machine Learning and Algorithms on GradNova.

J

Jamie Morgenstern

Associate Professor

Computer Science

University of Washington

Ethics & Fairness

Human-Centered AI

Machine Learning

Auction Theory and Applications

+4

K

Associate Professor

Computer Science

University of Washington

Machine Learning

Advanced Bandit Algorithms Research

Machine Learning and Algorithms

Reinforcement Learning in Robotics

+2

S

Simon Shaolei Du

Associate Professor

Computer Science

University of Washington

Machine Learning

Theoretical Computer Science

+5

B

Professor

Computer Science

University of Washington

Computer Vision

Machine Learning

Reinforcement Learning in Robotics

+4

P

Professor; Associate Director for Facilities

Computer Science

University of Washington

Quantum Computing

Theoretical Computer Science

Complexity and Algorithms in Graphs

Formal Methods in Verification

+3

N

Associate professor; data science advisor

Computer Science

University of Victoria

Machine Learning Theory

Advanced Bandit Algorithms Research

Machine Learning and Algorithms

Statistical Methods and Inference

+2

Z

Assistant professor

Computer Science

University of Victoria

Computational Complexity Theory

Complexity and Algorithms in Graphs

Computability, Logic, AI Algorithms

Cryptography and Data Security

+2

B

Lecturer, Computer Science

Computer Science

University of Vermont

Parameterized Algorithms and Complexity

Structural Graph Theory

Advanced Graph Theory Research

Complexity and Algorithms in Graphs

+3

D

Assistant Professor

School of Computing

University of Utah

Human-Computer Interaction

Machine Learning

Robotics (autonomous Systems and Learning, Human/medical Robotics)

Reinforcement Learning in Robotics

+4

A

Aditya Bhaskara

Associate Professor

School of Computing

University of Utah

Algorithms (approximation / Online Algorithms, Graph Algorithms)

Artificial Intelligence (ml: Theory and Modeling)

Complexity and Algorithms in Graphs

Machine Learning and Algorithms

+3

M

Mahdi Soltanolkotabi

Andrew and Erna Viterbi Early Career Chair and Professor of Electrical and Computer Engineering, Computer Science, and Industrial and Systems Engineering

Ming Hsieh Department of Electrical and Computer Engineering

University of Southern California

Domain Adaptation and Few-Shot Learning

Machine Learning and Algorithms

Privacy-Preserving Technologies in Data

Sparse and Compressive Sensing Techniques

+1

V

Assistant Professor of Computer Science

Computer Science

University of Southern California

Adversarial Robustness in Machine Learning

Domain Adaptation and Few-Shot Learning

Machine Learning and Algorithms

Machine Learning and Data Classification

+1

M

Mukund Raghothaman

Associate Professor of Computer Science

Computer Science

University of Southern California

Formal Methods in Verification

Machine Learning and Algorithms

Software Engineering Research

Software System Performance and Reliability

+1

W

Willie Neiswanger

Assistant Professor of Computer Science

Computer Science

University of Southern California

Advanced Bandit Algorithms Research

Gaussian Processes and Bayesian Inference

Machine Learning and Algorithms

Machine Learning and Data Classification

+1

J

Associate Professor of Computer Science and of Electrical and Computer Engineering

Computer Science

University of Southern California

Formal Methods in Verification

Machine Learning and Algorithms

Reinforcement Learning in Robotics

Software Reliability and Analysis Research

+1

D

Dr. Lucas Lehnert

Assistant Professor

Computer Science

University of Saskatchewan

Adaptive Dynamic Programming Control

Evolutionary Algorithms and Applications

Machine Learning and Algorithms

Neural Dynamics and Brain Function

+1

H

Assistant Professor of Computer Science and Data Science

Computer Science

University of Rochester

Machine Learning

Natural Language Processing

+4

D

Professor

Computer Science

University of Oregon

Machine Learning

Bayesian Modeling and Causal Inference

Adversarial Robustness in Machine Learning

+2

D

Dimitrios Diochnos

Associate Professor

Computer Science

University of Oklahoma

Adversarial Learning

Imbalanced Data

Randomized Search Heuristics

Semi-Supervised Learning

+6

J

Lecturer

Computer Science

University of Minnesota

AI-Based Problem Solving and Planning

Artificial Intelligence in Law

Clinical Reasoning and Diagnostic Skills

Machine Learning and Algorithms

+1

A

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

Computer Science and Engineering

University of Michigan

AI for Chemistry

AI for Psychiatry

Machine Learning

Advanced Bandit Algorithms Research

+4

M

Michał Dereziński

Assistant Professor, EECS – Computer Science and Engineering

Computer Science and Engineering

University of Michigan

Dimensionality Reduction

Machine Learning and Statistical Learning Theory

Randomized Numerical Linear Algebra

Scalable Stochastic and Distributed Optimization

+5

H

Lecturer III, EECS – Computer Science and Engineering

Computer Science and Engineering

University of Michigan

Data Stream Mining Techniques

Data Visualization and Analytics

Gaussian Processes and Bayesian Inference

Machine Learning and Algorithms

+1

J

Associate Chair, Professor

Computer Science

University of Kentucky

Bayesian Modeling and Causal Inference

Computability, Logic, AI Algorithms

Data Management and Algorithms

Game Theory and Voting Systems

+1

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