Curriculum Vitae

  • Jacob Moorman

  • Applied Math Ph.D. Student at UCLA

Education

Ph.D. Mathematics

M.A. Mathematics

University of California, Los Angeles (UCLA)
2016 – Present
2016 – 2018
Los Angeles, CA

B.S. Computational Mathematics

B.S. Computer Science

New Jersey Institute of Technology (NJIT)
2012 – 2016
2012 – 2016
Newark, NJ

Research

Publications

  • 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

Technical Skills

Languages and Tools

  • Proficient: Python (NumPy, SciPy, PySpark, GraphFrames, Networkx, Matplotlib), Matlab, JavaScript, git
  • Working knowledge: C++, SQL, WebGL

Work

Data Science Intern

Neural Analytics
April 2017 – Sept 2017
Los Angeles, CA
  • Developed quality metrics for transcranial doppler ultrasound data to improve search algorithms
  • Created simulations for testing search algorithms to reduce the need for physical tests
  • Automated routine data visualization processes

Software Engineering Intern

Trillium Labs
Jan 2015 – May 2016
New York, NY
  • Built an equity market data visualization web app to allow interactive access to millisecond resolution records
  • Implemented outlier detection methods to help identify interesting stocks and transactions
  • Combined outlier detection and data visualization tools into a workflow for generating market insights

Game Development Consultant

Mission Critical Studios
Sept 2012 – Nov 2014
Farmingdale, NJ
  • Designed and prototyped levels for 2D puzzle game published on Steam
  • Added custom physics mechanics to 3D action game in Unity using C#

Teaching

Teaching Assistant

UCLA Department of Mathematics
Sept 2016 – May 2018
Los Angeles, CA
  • Math 174E: Mathematics of Finance (S'18)
  • Math 171: Stochastic Processes (S'18, W'18, F'17)
  • Math 170B: Probability Theory (S'17)
  • Math 170A: Probability Theory (F'16)
  • Math 155: Mathematical Imaging (W'18)
  • Math 142: Mathematical Modeling (F'17)