Curriculum Vitae
Education
Ph.D. in Computing | Boise State University
Focus: Machine Learning & Graph Representational Learning
December 2025
- Dissertation: Advanced Zero-Shot Learning and Temporal Dynamic Analysis on Graphs.
- Key Coursework: Large Scale Data Analysis, Machine Learning, Data Structures, Advanced Algorithms.
B.S. in Computer Science | Boise State University
2016 – 2020
Technical Skills
| Domain | Tools & Technologies |
|---|---|
| Languages | Python, C++, Java, C, SQL, LaTeX |
| ML & AI | PyTorch, TensorFlow, DGL, NetworkX, Jupyter, Ollama, HuggingFace |
| Infrastructure | Docker, Unraid, KVM, Linux (Bash), Cloudflare Tunnels, HPE Servers |
| Data Analysis | Pandas, SciPy, Matplotlib, Structural Node Representation |
Research Experience
Graduate Research Assistant | Boise State University
December 2020 – December 2025
Lead researcher focusing on Graph Neural Networks (GNNs) and Temporal Graph Learning.
- Zero-Shot Learning: Developed LLM-GMP, a framework utilizing Large Language Models for message passing on graphs without training data.
- Temporal Dynamics: Engineered Temporal SIR-GN, an algorithm for structural representation learning on dynamic temporal graphs.
- Scalability: Created 2FWL-SIRGN, implementing graph partitioning to scale Folklore Weisfeiler-Lehman isomorphism tests to massive datasets.
- Botnet Detection: Designed structural node representation models to detect botnet traffic patterns with high efficiency and low computational cost.
Teaching Experience
Graduate Teaching Assistant | Boise State University
2020 – 2024
Instructed and mentored undergraduate and graduate students in core computer science concepts.
- CS 535 - Large Scale Data Analysis: Guided students through big data frameworks and distributed computing concepts.
- CS 534 - Machine Learning: Assisted in teaching fundamental and advanced ML algorithms, grading projects, and providing technical support.
- CS 321 - Data Structures: Tutored students on algorithmic efficiency, data organization, and debugging complex Java/C++ code.
Computer Science Lab Assistant | Boise State University
January 2020 – May 2020
- Provided critical debugging support and development strategies for CS 121 students.
- Facilitated the department's transition to remote learning environments, ensuring student continuity during the shift to online classes.
Publications
2025 (Accepted)
- LLM-GMP: Large Language Model-Based Message Passing for Zero-Shot Learning on Graphs.
- Accepted at IEEE Big Data 2025.
2024
- 2FWL-SIRGN: A Scalable Structural 2-dimensional Folklore Weisfeiler-Lehman Graph Representation Learning Approach Via Structural Graph Partitioning.
- Authors: Justin Carpenter, Edoardo Serra.
2023
- Temporal SIR-GN: Efficient and Effective Structural Representation Learning for Temporal Graphs.
- Authors: Janet Layne, Justin Carpenter, Edoardo Serra, Francesco Gullo.
2021
- Botnet Detection: Detecting Botnet Nodes via Structural Node Representation Learning.
- Authors: Justin Carpenter, Janet Layne, Edoardo Serra, Alfredo Cuzzocrea.