Resume.
Updated June 2026
I've always been interested in space, evolution, and how people learn, and engineering has kept turning out to be the most direct way to actually work on those kinds of problems.
Right now I'm spending most of my time on applied AI at the edge, time-series forecasting and AutoML, and multimodal agentic systems with memory layers that persist across sessions. What I enjoy most is the messy, practical end of it, where the model itself is only part of what you have to figure out.
- GPA 3.97.
- TA for Using AI in Industrial Applications (49-734).
- GPA 3.86. Graduated with Distinction.
- VP of Badger Rail Club. Head Tutor at the Undergraduate Learning Center. TA for Statics.
- Published SCOPE at HRI '26: a benchmark and evaluation harness for modular vision-language pipelines, built around PTZ camera control. GitHub ↗ Paper ↗
- Time-series forecasting for the SD-WAN and Starlink workstreams; iteratively shrinking models to fit smaller hardware footprints.
- Multimodal and agentic prototypes for edge deployment; memory layers for long-running agents.
- Quantized models served via vLLM and Ollama for on-device inference.
- Replaced reduced-order simulation components with ML models (LSTMs, NNs) for full-system engine simulations. Matched higher-order accuracy at lower latency.
- Cut a workflow from 200 to 20 engineer-hours, ~3,600 hours saved annually. Removed proprietary-tool license dependencies.
- Trained in Python/PyTorch; deployed inference into Simulink via cross-language plumbing.
- Automated training pipeline with Bayesian hyperparameter search. Feature engineering targeted specific failure modes (masking, synthetic features for thermal inertia).
- Presented to VP and cross-departmental leadership. Wrote up the integration patterns so the team could repeat the process.
- New and improved features in Ansys Mechanical (Workbench). Cross-team work to fit company-wide standards.
- Debugging and tracing through legacy systems with COM principles; cross-language changes across C++, JavaScript, Python, HTML/CSS, C#.
- Centralized standalone HTML worksheets into the main app, added CAD pre-solve checks, expanded the tooltip system.
- Tutored students across the engineering and CS curriculum — math, programming, statics, dynamics, physics, mechanics of materials, and a few others depending on who walked in. Led a team of ~15-20 tutors while still taking sessions of my own.
- Led the discussion section (full class of ~20) and TA'd Statics across multiple semesters.
- SCOPE — evaluation harness for modular multimodal pipelines — HRI '26, 2025
- Fine-tuning LLaVA for web agents — CMU MMML, 2024
- Waste classification on a Raspberry Pi 5 — CMU, 2024
- Directional buckling for in-pipe locomotion — CMU, 2024
- Refueling satellite — UW senior design, 2023
Python, TypeScript, MATLAB, C++, Java, JavaScript, SQL.
PyTorch, TensorFlow, LoRA fine-tuning, ONNX, INT8 quantization, multimodal systems (LLaVA, Qwen-VL, Moondream), time-series forecasting.
vLLM, Ollama, MLflow, Databricks, Spark, AWS, Google Cloud, Git.
SolidWorks, ANSYS, Blender, Unity / VR.
Intro ML/AI, Deep Learning I & II, Multimodal ML, Generative AI, Trustworthy AI, Systems and Tool Chains for AI, CS Fundamentals, UX Development, VR, Multi-Variable and Vector Calculus, Linear Algebra and Differential Equations, Statistics, Applied Math Analysis.
Advanced Mechanics of Materials, Fracture Mechanics, Thermodynamics, Heat Transfer, Fluid Dynamics, Statics, Advanced Dynamics, Robotic Dynamic Analysis, Aerodynamics, Heterogeneous and Multiphase Materials, Tissue Mechanics, Advanced Materials Testing, Circuits, Advanced Controls Systems Integration.
This page is generated from site data, it isn't a real document I keep in sync. For a one-pager I'll send the current version, just email me.
Older PDF (master's-era, 2024) for reference: archived resume ↗ .