CV

Education

  • New York University, Courant Institute - M.S. in Computer Science (Expected May 2028)
  • California Polytechnic State University, San Luis Obispo - B.S. in Computer Science, Minor in Mathematics (Mar 2026). Major GPA: 3.94; GPA: 3.86

Research Experience

  • Senior Research Assistant - UChicago, Argonne National Lab (Jun–Sep 2025)
    • Advised by Dr. Silvio Rizzi; U.S. Dept. of Energy lab
    • Kolmogorov-Arnold Networks for implicit neural representations of 3D scientific volumes; +2–15 dB PSNR over SIREN/MLP baselines
  • Undergraduate Research Assistant - Ventura Lab, Cal Poly (Jan–Jun 2025)
    • Advised by Prof. Johnathan Ventura; funded by the National Cancer Institute
    • Action segmentation from monocular video; Mean Squared Error < 1 repetition vs. clinician annotations
  • Undergraduate Research Assistant - AI for Search & Rescue Lab, Cal Poly (Sep 2023–Dec 2024)
    • Advised by Prof. Franz Kurfess; sponsored by Menlo Park Fire Protection District
    • Multimodal location prediction from 1M+ missing person case dataset

Industry Experience

  • ML Engineer Intern - LandingAI (Sep–Dec 2025)
    • VLM attention diagnostics, parameter-efficient fine-tuning, and large-scale data distillation
  • ML Engineer Intern - FemtoAI (Jun–Sep 2023)
    • Neural audio noise reduction; generative data augmentation; automated ML pipeline

Posters & Presentations

  • KAN INRs: Kolmogorov-Arnold Neural Networks for Scientific Volumetric Implicit Neural Representations. Charles O'Hanlon. Learning on the Lawn, Argonne National Laboratory, Aug 2025.
  • Neural Networks for Missing Persons Location Prediction. Charles O'Hanlon, Brandon Kim, Ameer Arsala. National Missing and Unidentified Persons Conference, Apr 2024.

Teaching

  • Teaching Assistant - CSC 480 Artificial Intelligence, Cal Poly (Sep–Dec 2025)
  • Curriculum Design Contributor - CSU AI Educational Innovations Challenge (Aug 2025–Present)

Skills

  • Languages: Python, C/C++, CUDA
  • ML: PyTorch, NumPy, Hugging Face Transformers, scikit-learn
  • Distributed/Infra: CUDA, vLLM, SGLang, Ray, Weights & Biases, Hydra
  • Vision: OpenCV, MediaPipe, OpenMMLab