
Jacob D. Moorman, Thomas K. Tu, Denali Molitor, Deanna Needell, "Randomized Kaczmarz with Averaging." Proc. Information Theory and Applications Workshop, La Jolla, CA, Feb. 2019.

Jacob D. Moorman, Qinyi Chen, Thomas K. Tu, Zachary M. Boyd, Andrea L. Bertozzi, "Filtering Methods for Subgraph Matching on Multiplex Networks." Proc. GTA³ 2.0: The 2nd workshop on Graph Techniques for Adversarial Activity Analytics, IEEE International Conference on Big Data, Seattle, WA, Dec. 2018.
Subgraph Matching for Multichannel Networks
UCLA Department of Mathematics
May 2018
– Present
Los Angeles, CA
 Implemented subgraph matching algorithms using Python, PySpark, and GraphFrames
 Funded by DARPA for the Modeling Adversarial Activity program
 Worked with a team of students in a summer research program
Randomized Iterative Methods for Least Squares
UCLA Department of Mathematics
April 2018
– Present
Los Angeles, CA
 Computed the greedily optimal step size for the relaxed randomized Kaczmarz algorithm
 Proved linear convergence of the algorithm using the optimal step size
 Found a short recurrence for updating the step size
Reddit Profanity Analysis
UCLA Departments of Mathematics and Statistics
Jan 2017
– Dec 2017
Los Angeles, CA
 Quantified structural differences between threads with and without profanity
 Performed topic modeling on comments and threads, analyzed the sentiment of the topics
 Found structure and sentiment of threads with profanity tend to be different from those without profanity
Particle Filtering for Uncertainty Quantification in Tracking
NJIT Department of Mathematics
Jan 2014
– Dec 2014
Newark, NJ
 Applied a particle filtering approach to identifying and tracking acoustic sources in 2 and 3 dimensions
 Wrote simulations and benchmark tests in C++ and MATLAB to evaluate performance