Research Group
Research Group
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Our research group focuses broadly on the mathematics of information, data, and signals. The group designs new models and methods for data representation, inference, learning, and generalization capabilities of algorithms, always aiming to provide theoretical guarantees on the performance. Our work is often geometric in nature, focusing on preserving local or global geometry of the data while allowing for efficient computation and storage. We specifically work with methods in deep learning, optimal transport, kernel methods, and spectral graph theory. Much of our work is motivated by a range of scientific applications, which can lead to tailored algorithms for the application as well as raise new mathematical questions.
We have weekly seminar talks, topics can be found here: https://sites.google.com/ucsd.edu/ucsd-minds
If you're a grad student or postdoc at UCSD interested in this work, please drop in.
We're always looking for highly qualified and motivated PhD students and postdocs. Email acloninger@ucsd.edu if interested.
Current Group Members
Alex Cloninger, PI
Dhruv Kohli, PhD 2021-present,
Manifold Learning and Optimization
Sawyer Robertson, PhD 2021-present,
Spectral Graph Theory and Machine Learning
Yimeng Zhang, PhD 2021-present,
Deep Learning in Differential Equations
Yiming Zhang, PhD 2022-present,
Theoretical Foundatoins of Deep Learning
Nick Karris, PhD 2023-present, Optimal Transport and Time Series
Tianxiang (Sophia) Wang, Masters 2025-present, Optimal Transport and Single Cell Data
Cheyenne Ward, Undergraduate (CSUSB) 2023-present,
Nonlinear Dimension Reduction
Haohan Zou, Undergraduate 2024-present, Streaming Kernel Methods
Paola Campos, Undergraduate (CSU Stanislaus) 2024-present, Graph Machine Learning
Yingtong Ke, Undergraduate 2025-present, Optimal Transport and Signle Cell Data
Past Group Members
Caroline Moosmueller, SEW Assistant Professor 2019-2022, Currently Asst. Prof. at UNC Chapel Hill
Timo Klock, Postdoc 2020-2021, Currently Co-Founder DeepTech Consulting
Srinjoy Das, Postdoc 2019-2021, Currently Asst. Prof. at West Virginia University
Varun Khurana, PhD 2021-present,
Currently RTG Postdoc at Brown University
Andreas Oslandsbotn, PhD (Simula Labs) 2019-2024,
Currently ML Engineer at OptoScale
Scott Mahan, PhD 2018-2023,
Currently at Pacific Northwest National Lab
Sami Ortoleva, PhD 2018-2023,
Tensors and Graphs for Machine Learning
Jinjie Zhang, PhD 2019-2023,
Currently AI Engineer at GSK.ai
Teresa Rexin, MS 2021-2023, Currently Data Scientist at Microsoft
Huye Zhou, MS 2019-2020, Currently Data Scientist at Amazon
Jun Linwu, Undergraduate 2023-2024, Learning on Point Clouds
Huiwen Lu, Undergraduate 2022-2023, Currently PhD student at CalTech
Winston Yu, Undergraduate 2022-2023, Currently PhD student at Columbia
Andrew Dennehy, Undergraduate 2020-2022, Currently PhD student and NSF Grad Fellow at U of Chicago
Yuliang Cai, Undergraduate 2021-2022, Currently PhD student at USC
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