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Alex Cloninger
Assistant Professor

Alex Cloninger is an Assistant Professor in Mathematics and the Halıcıoğlu Data Science Institute at UC San Diego. He received his PhD in Applied Mathematics and Scientific Computation from the University of Maryland in 2014, and was then an NSF Postdoc and Gibbs Assistant Professor of Mathematics at Yale University until 2017, when he joined UCSD.  Alex researches problems in the area of geometric data analysis and applied harmonic analysis.  He focuses on approaches that model the data as being locally lower dimensional, including data concentrated near manifolds or subspaces.    The techniques developed have led to research in a number of machine learning and statistical algorithms, including deep learning, network analysis, signal processing, and measuring distances between probability distributions.  This has also led to collaborations on problems in several scientific disciplines, including imaging, medicine, and artificial intelligence.

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Gal Mishne
Assistant Professor

Mishne’s research is at the intersection of signal processing and machine learning for graph-based modeling, processing and analysis of large-scale high-dimensional real-world data. She develops unsupervised and generalizable methods that allow the data to reveal its own story in an unbiased manner. Her research includes anomaly detection and clustering in remote sensing imagery, manifold learning on multiway data tensors with biomedical applications, and computationally efficient application of spectral methods. Most recently her research has focused on unsupervised data analysis in neuroscience, from processing of raw neuroimaging data through discovery of neural manifolds to visualization of learning in neural networks.

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Rayan Saab
Associate Professor

Rayan’s work is on the mathematics of information, data, and signals. His research is broadly motivated by problems in the acquisition, digitization, and processing of data. For example, he is interested in sampling and quantization, compressed sensing, sparse  and low-dimensional representations of data, as well as inverse problems like phase retrieval and blind source separation.

Before joining UCSD as an assistant professor in 2013, he was a visiting assistant professor and a Banting postdoctoral fellow at Duke University (2011-2013). Before that, he completed his PhD at the University of British Columbia in 2010, where he was a member of the Institute of Applied Mathematics.