Jacob Gardner

Jacob Gardner

Assistant Professor
Computer and Information Science (CIS)

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Research Expertise: Machine Learning | Artificial Intelligence

Jacob Gardner is interested in all areas of machine learning. His work recently has focused on developing probabilistic machine learning methods that scale to the large and complex datasets encountered in machine learning today. His recent work has focused on scalable Gaussian processes, deep Gaussian processes, Bayesian optimization and deep learning. He maintains a popular open source platform for Gaussian processes, GPyTorch.

Education:
PhD - 2018 - Computer Science - Cornell University
MS - 2017 - Computer Science - Cornell University
BS - 2013 - Washington University in St. Louis

Recent Publications


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