"In God we trust, others must provide data."


I received my PhD in the Graduate Group in Applied Mathematics at the University of California, Davis where I was advised by Professor Jesús A. De Loera. I work in optimization, applied convex geometry, and mathematical data science. I am currently a CAM Assistant Professor (post-doc) in the UCLA Mathematics Department where my mentor is Professor Deanna Needell. In July 2021, I will join the Harvey Mudd College Mathematics Department as a tenure-track assistant professor!



Email: j(lastname)@math.ucla.edu.
Office: MSB 7354

Mail: Department of Mathematics
University of California, Los Angeles
Box 951555
Los Angeles, CA 90095-1555, USA

Recent News:

[Oct. '20]

We (with student Sixian Li) submitted the paper Semi-supervised NMF Models for Topic Modeling in Learning Tasks! In this work, we propose several new semi-supervised NMF (SSNMF) models and show that these are naturally formulated as the maximum likelihood estimators given a generative factorization model and assumed distributions of uncertainty in the observed data. We develop training methods for the general forms of these models and illustrate how to apply them to the classification task; our experiments show that these methods are very promising and achieve high classification accuracy on the 20 Newsgroups data (while also developing a coherent topic model and classifying in a low-dimensional space)!

[Sep. '20]

We (with student Josh Vendrow) submitted the paper "Neural Nonnegative CP Decomposition for Hierarchical Tensor Analysis"! We propose a model for hierarchical tensor decomposition and a neural network-inspired technique for training the model. This model allows a user to decompose a tensor at different granularities (ranks) and to visualize the relationship between the learned topics at different levels of hierarchy!

[Sep. '20]

We submitted the paper Quantile-based Iterative Methods for Corrupted Systems of Linear Equations! In this paper, we propose iterative methods for solving large-scale and arbitrarily corrupted systems of equations. We provide both theoretical and empirical evidence of the promise of these methods; our theoretical results build upon new and classical results in high-dimensional probability.

[Sep. '20]

We submitted the paper "Weakly-Supervised Object Localization using Semi-supervised Nonnegative Matrix Factorization"! We combine a new form of semi-supervised nonnegative matrix factorization with convolutional neural network filters to produce a successful model for object localization in multi-class image datasets.

[Sep. '20]

Our paper On Large-Scale Dynamic Topic Modeling with Nonnegative CP Tensor Decomposition was accepted for publication in the Proceedings of the Women in Data Science and Mathematics (WiSDM) Workshop! This collaboration was begun at the Research Collaboration Workshop for Women in Data Science and Mathematics, July 2019 held at ICERM (funded by ICERM, AWM and DIMACS (NSF grant CCF1144502)).

[Aug. '20]

We (with student Josh Vendrow) submitted the paper Feature Selection on Lyme Disease Patient Survey Data! In this work, we use basic machine learning techniques to perform feature selection on a large-scale survey dataset from a private Lyme disease patient database, MyLymeData.


MATH 156: Machine Learning


I am speaking in the NYU Data Science Lunch Seminar on November 18, 2021 at 9:30 am PST (Zoom coordinates available on request)!

I am speaking in the HMC Mathematics Connections Seminar on November 20, 2021 at noon PST (Zoom coordinates available on request)!

I am participating in the focus program on “Data Science, Approximation Theory, and Harmonic Analysis’’ at the Fields Institute from May 17-June 11, 2021 and will be speaking during the Focus Week on “Computational Harmonic Analysis and Linear Algebra” (May 17-21).

I am speaking in the "Moving Randomized Linear Algebra from Theory to Practice" minisymposium at the SIAM Conference on Applied Linear Algebra (LA21) in New Orleans, LA from May 17-21.

I am participating in the AMS MRC Finding Needles in Haystacks: Approaches to Inverse Problems using Combinatorics and Linear Algebra which is rescheduled for June 6-12, 2021 in West Greenwich, RI.

Useful Links:

HMC Mathematics
UCLA Mathematics
UCLA Women in Math
UC Davis Mathematics