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
Rishabh Dixit, SEW Math Fellow 2024-present, Optimization for Machine Learning,
Yiming Zhang, PhD 2022-present, Theoretical Foundations of Deep Learning
Tongtong Liang, PhD 2024-present, Theoretical Foundations of Deep Learning
Yidan Mao, PhD 2025-present, Generative Models and Graphs
Lorenzo Beronilla, PhD 2026-present, Nonlinear Data Representation
Allyson Ybarra, Undergraduate 2025-present, Hypergraphs and Mathematical Biology
Past Group Members
Caroline Moosmueller, SEW Assistant Professor 2019-2022, Next job: Asst. Prof. at UNC Chapel Hill
Timo Klock, Postdoc 2020-2021, Next job: Co-Founder DeepTech Consulting
Srinjoy Das, Postdoc 2019-2021, Next job: Asst. Prof. at West Virginia University
Sawyer Robertson, PhD 2021-2026, Next job: Postdoc at Columbia University
Nick Karris, PhD 2023-2026, Next job: Postdoc at University of Michigan
Yimeng Zhang, PhD 2021-2026, Deep Learning in Differential Equations
Dhruv Kohli, PhD 2021-2025, Next job: Postdoc at Princeton University
Varun Khurana, PhD 2021-present, Next job: RTG Postdoc at Brown University
Andreas Oslandsbotn, PhD (Simula Labs) 2019-2024, Next job: ML Engineer at OptoScale
Scott Mahan, PhD 2018-2023, Next job: Pacific Northwest National Lab
Sami Ortoleva, PhD 2018-2023, Tensors and Graphs for Machine Learning
Jinjie Zhang, PhD 2019-2023, Next job: AI Engineer at GSK.ai
Tianxiang (Sophia) Wang, Masters 2025-2026, Next job: PhD student at UC Santa Cruz
Teresa Rexin, Masters 2021-2023, Next job: Data Scientist at Microsoft
Huye Zhou, Masters 2019-2020, Next job: Data Scientist at Amazon
Paola Campos, Undergraduate (CSU Stanislaus) 2024-2025, Next job: PhD student at UC Davis
Yingtong Ke, Undergraduate 2025-2026, Next job: Masters at U of Chicago
Haohan Zou, Undergraduate 2024-2025, Next job: PhD student at UCSD
Cheyenne Ward, Undergraduate (CSUSB) 2023-2025, Nonlinear Dimension Reduction
Jun Linwu, Undergraduate 2023-2024, Learning on Point Clouds
Huiwen Lu, Undergraduate 2022-2023, Next job: PhD student at CalTech
Winston Yu, Undergraduate 2022-2023, Next job: PhD student at Columbia
Andrew Dennehy, Undergraduate 2020-2022, Next job: PhD student and NSF Grad Fellow at U of Chicago
Yuliang Cai, Undergraduate 2021-2022, Next job: PhD student at USC
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