Computer Science Graduate | Deep Learning Researcher
Marine Corps Veteran | Texas
I recently graduated with a B.S. in Computer Science from the University of Texas at San Antonio (May 2025) and will begin my M.S. in Computer Science at UTSA in August 2025, with plans to pursue a Ph.D. starting in Fall 2026. My focus is on deep learning, distributed systems, and edge computing. I conduct research in the Vision and AI Lab (VAIL) under Dr. Amanda Fernandez, where I am researching a new deep learning architecture, and in the CloudSys Lab under Dr. Palden Lama, where I research edge AI applications. Recent work includes a submitted paper to IEEE EdgeCom 2025: "Where to Split? A Pareto-Front Analysis of DNN Partitioning for Edge Inference."
- Distributed ML Research: Optimizing AI model inference on Jetson and Pi clusters.
- Fracture Detection CNN: Trained a model to analyze X-ray images.
- ML Experimentation Server: Running JupyterLab on a dedicated ML rig (RTX 4080).
- Self-Hosted DevOps Stack: Managing cloud infrastructure and databases with Docker.
**Current Projects**
- DeepLabv3-VOS: Researching video object segmentation for CloudSys Lab at UTSA.
- Deeplabv3-Pi-Test: Optimizing DeepLabV3 for Raspberry Pis.
- YOLOv8-Vehicle-Analysis: Deep learning project analyzing vehicle detection and tracking.
- raspberrypi-lab-setup: Ansible playbooks to automate lab setup, installations, and configurations.
**Education**
University of Texas at San Antonio – B.S. in Computer Science, May 2025
University of Texas at San Antonio – M.S. in Computer Science, starting August 2025
Upcoming Courses (Fall 2025):
- Machine Learning (graduate level)
- Analysis of Algorithms (graduate level)
- Independent Study for research in VAIL
Completed Courses (Relevant):
- Deep Learning
- Distributed Systems
- Artificial Intelligence
- Machine Learning
- Data Mining
- Data Science
- Embedded Systems
GitHub: github.com/Foley-ops
LinkedIn: linkedin.com/in/nicholasmfoley