• Jacob Moorman

  • Applied Math Ph.D. Candidate at UCLA

Education

Ph.D. in Mathematics

2016 - Present

M.A. in Mathematics

June 2018
University of California, Los Angeles (UCLA)
Los Angeles, CA

B.S. in Mathematical Sciences

May 2016

B.S. in Computer Science

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

Skills

Programming languages: Python, JavaScript, SQL, MATLAB, C++, Bash
Operating systems and other tools: Linux, macOS, Windows, SVN, Git, LaTeX
Research interests: optimization, machine learning, statistics, network analysis, numerical linear algebra

Experience

Graduate Researcher and Teaching Assistant

University of California, Los Angeles (UCLA)
Sept 2016 – Present
Los Angeles, CA
  • Completed independent and collaborative research projects resulting in conference and journal publications
  • Communicated research results and ideas in oral and poster presentations
  • Implemented experiments and algorithms in Python; used git for version control and collaboration
  • Completed a variety of courses in numerical analysis, statistics, optimization, and machine learning
  • Taught undergraduate courses in probability theory, mathematics of finance, and image processing

Research Intern

HRL Laboratories
Summer 2019
Malibu, CA
  • Created a calibration procedure for dynamic multi-sensor systems, implemented algorithms in Python
  • Established benchmark tests to objectively compare calibration accuracies
  • Integrated my calibration procedure into a hands-off sensor system

Data Science Research Intern

Neural Analytics
Summer 2017
Los Angeles, CA
  • Developed search algorithms for robotically performing TCD studies previously carried out by hand
  • Created simulations in Python for testing search algorithms to reduce the need for physical tests
  • Automated routine data visualization processes using Bash and Python

Software Engineering Intern

Trillium Labs
Jan 2015 – May 2016
New York, NY
  • Built an interactive data visualization web application with HTML and JavaScript to view detailed stock data
  • Implemented outlier detection methods in Python and C++ to identify anomalous stocks and transactions
  • Combined outlier detection and data visualization tools for generating market insights

Undergraduate Researcher

NJIT Department of Mathematics
Jan 2014 – Dec 2014
Newark, NJ
  • Applied a particle filtering approach to identify and track acoustic sources in 2 and 3 dimensions
  • Wrote simulations and benchmark tests in C++ and MATLAB to evaluate performance

Game Development Consultant

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