I build production ML systems and I’m especially interested in the intersection of: LLMs / multimodal ↔ hardware + signals ↔ real-world decision-making.
- 🔭 Current focus: ML for diagnostics / reliability / repair recommendations, plus modern NLP on messy log data (ranking, calibration, uncertainty, cost-sensitive decisions).
- 🌱 Learning: multimodal foundation models, LLM finetuning, and practical evaluation/guardrails.
- 🛰️ Background: PhD EE (electromagnetics / metamaterials). Deep experience with RF modeling, phased arrays, and EM simulation.
- 👯 Open to collaborating on: applied ML projects involving RFID, wireless, phased arrays, signal + text fusion, or high-signal evaluation.
- 💬 Ask me about: PyTorch, transformers for ranking/classification, ML for hardware systems, EM/RF simulation, phased-array modeling.
Python • PyTorch • Hugging Face • scikit-learn • Polars • Jupyter
AWS (SageMaker / Athena-ish workflows) • Docker • Git • Linux
MATLAB • HFSS / CST / FEKO / ADS (and friends)
- Phased-Array-Antenna-Model
Phased-array antenna pattern modeling and analysis — practical, engineering-first code and examples. - phased-array-systems
Systems-level phased-array concepts and implementation notes/tools for real-world arrays. - ☕ BeanBench (iOS) — an iPhone app for specialty coffee nerds: log brews, rate beans, and build better cups over time.
- PyTorch-Vision-Transformers-ViT
Vision Transformer work in PyTorch — experiments, implementation details, and learning artifacts.
If you’re working on any of these, I’d love to chat:
- Multimodal (text + sensors/signals) modeling
- RFID / wireless inference problems
- Phased arrays + ML (surrogates, optimization, generative design)
- LinkedIn: https://linkedin.com/in/jhodge007
- GitHub: https://github.com/jman4162
- Email: jah70 at vt dot edu
🏀 Duke basketball • 🥾 hiking • ☕ specialty coffee (V60 life)