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Education, experience, publications, projects, and skills. A PDF copy is available from the icon at the top right.

Basics

Name Benjamin Cobb
Label Incoming HPC Engineer, Citadel Securities
Email benjamincobb00@gmail.com
Url https://www.ben-cobb.com
Summary PhD in Computer Science from the Georgia Institute of Technology (August 2026), with research in numerical linear algebra, tensor decompositions, and high-performance computing. Joining Citadel Securities as an HPC Engineer in November 2026.

Work

  • 2026.11 - Present
    HPC Engineer
    Citadel Securities
    Incoming role, starting November 2026.
  • 2024.06 - 2025.05
    Discrete Algorithms Intern
    Oak Ridge National Laboratory
    Worked on discrete algorithms during internships at ORNL.
  • 2020.06 - 2020.08
    Computer Science Research Intern
    Sandia National Laboratories
    Internship during the pandemic, conducted virtually.
  • 2019.01 - 2026.08
    Graduate Research Assistant
    Georgia Institute of Technology
    Researched numerical linear algebra, tensor decompositions, and high-performance computing.
  • 2016.01 - 2019.01
    Resident Advisor
    Wake Forest University
    Served as RA during undergraduate studies.

Education

  • 2019.01 - 2026.08

    Atlanta, GA

    PhD
    Georgia Institute of Technology
    Computer Science
    • Minor in Mathematics
    • Advisors: Richard Vuduc and Haesun Park
  • 2015.01 - 2019.01

    Winston-Salem, NC

    B.S.
    Wake Forest University
    Computer Science and Mathematical Business
    • Minor in Chinese
    • Graduated Magna Cum Laude

Publications

Skills

High-Performance Computing
MPI
CUDA
Kokkos
OpenMP
cache aware programming
Programming
C/C++
MATLAB
Python
Machine Learning
Deep Learning
Neural Nets
PyTorch
Matrix and Tensor Factorizations
Software Development
Git
CMake
Unit Tests
Vim
Slurm
Tmux
Linux Command Line
Scripting
Performance Analysis and Debugging
Roofline Bandwidth Analysis
VTune
GDB

Projects

  • - Present
    PLANC
    Distributed MPI software package for large-scale matrix and tensor factorizations used in data analysis and compression.
  • - Present
    GenTen Portable Tensor Decompositions
    Performance portable software package for tensor factorizations used in data compression.
  • - Present
    MATLAB Tensor Toolbox
    Implemented minimum cost bipartite matching algorithm for least-squares cosine differences.