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  • Brigham Young University

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connerdrake98/README.md

Conner Drake @connerdrake98

  • 💻 Currently looking for my next ML / SWE / Data role
  • Past Roles: Software Engineer / Machine Learning Intern, Machine Learning Student Researcher,
  • ⌨️ Languages: Python, C/C++, Java, SQL, JavaScript/TypeScript, HTML/CSS
  • 🤖 AI / ML: PyTorch, ML research, Transformers, LLMs, RAG, NLP, computer vision, feature engineering, feature selection, Parquet, scikit-learn, OpenAI and Gemini APIs, loss function design, model testing and validation
  • 🗃️ Data: Pandas, Numpy/Parallelization, ETL, EDA (matplotlib, Nomic Atlas, etc.), JSON, Selenium, Data Scraping/BeautifulSoup
  • ⚙️ Systems: Git, Linux, BitBucket, AWS, Docker, React, unix shell, LLM tools, Jira, Motion, Microsoft Suite, Google Suite
  • 🏫: BYU - B.S. in Computer Science (Machine Learning) Status: Degree in progress; extended part-time enrollment (~3 courses/year). Selected Upper-Division Coursework: Advanced Software Construction; Deep Learning; Algorithm Design and Analysis; Undergraduate ML Research

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  1. neural-style-transfer-gatys2016-pytorch neural-style-transfer-gatys2016-pytorch Public

    Dockerized PyTorch neural style transfer (Gatys 2016) with VGG-16 feature extractor. Computes content loss and Gram-matrix style loss across selected VGG16 layers; performs Adam-based pixel descent…

    Python

  2. BYU-PCCL/scam-call-identification BYU-PCCL/scam-call-identification Public

    Novel ML-powered real-time scam call identification data pipeline and model (in development) that analyzes phone call transcripts using LLM-derived and NLP-based features to indicate scam risk.

    Python 2

  3. attention-from-scratch-PyTorch attention-from-scratch-PyTorch Public

    A PyTorch implementation of decoder‑only transformers (based on ‘Attention Is All You Need’ paper), focused on clear code, deterministic tests, and reproducible training with Docker and CI.

    Python 1