Hi, I’m Daniel 👋
I’m a computer scientist with experience in software engineering, high-performance computing, machine learning, DevOps, and much more. Where there are interesting problems to solve or pretty graphs to be made, you’ll find me. On the side, I love fighting games, music, and random tech stuff. Have a look around!
Interests
- High-Performance Computing
- Machine Learning
- Compilers & Interpreters
Education
Ph.D. in Computer Science, 2026 - Present
University of Kansas
M.S. in Computer Science, 2024
University of Kansas, GPA: 4.0/4.0
B.S. in Computer Science, 2022
University of Kansas, GPA: 3.74/4.0
Projects
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MatProp is a compact backpropagation engine and neural network framework that provides a PyTorch-like interface for defining and training neural networks using autograd-supported matrix operations. It has been thoroughly tested against PyTorch to ensure that its calculations of values and gradients are correct, and despite its capabilities, it has a codebase of only about 300 lines of code with ample documentation.
Glimmer is a fully statically-typed scripting language which aims to have clean and simple syntax while drawing some inspiration from each of my favorite languages and topics. This implementation of Glimmer comes with a complete Read-Eval-Print-Loop (REPL), Read-Parse-Print-Loop (RPPL), and Read-Lex-Print-Loop (RLPL). Of course, you can also execute source files directly.
