01
Owned the outcome
Founded and scaled Grantease to $100K ARR, then led AI engineering and product delivery at Aligrade, translating expert research workflows into production systems.
I turn complex expert workflows into reliable AI products.
01
Proof in production
02
Embedded with experts
Biostatisticians, life-sciences research teams, NIH-funded researchers, and scientific grant writers.
03
Translated work into product
Turned those workflows into retrieval and reuse tools, content review, literature search, citations, and reviewable document editing.
04
Engineered for production
Built multi-agent orchestration, hybrid retrieval and reranking, structured validation, resilient model routing, editing APIs, and end-to-end evaluations.
02
Selected work
Public engineering artifact
Editor MCP Public repository · Demo-ready
A collaborative document workspace for people and their AI agents.
I built a TypeScript MCP server and Tiptap/Yjs editor where agents make atomic, reviewable document changes instead of pasting text into chat. People can inspect, navigate to, accept, reject, or rewrite every proposed edit.
View source and demo- 01
Versioned semantic tools with revision guards and atomic edit groups
- 02
Live shared state through Tiptap, ProseMirror, Yjs, and Hocuspocus
- 03
Authenticated Streamable HTTP with OAuth and fail-closed validation
More building
Proto-Town Hardware Incubator · 2024
Built the place where other founders could build.
I helped launch a hardware-focused startup ranch, secured its first startup tenants, and built the prototyping workshop.
Research & writing
First author · TPCTC 2024
Evaluation Considerations of Synthetic Natural Language Datasets for Question Answering Applications
Designed and ran an experimental pipeline that generated synthetic question-answer datasets with four open-source LLM configurations, fine-tuned the same base model on each, and tested which dataset signals predicted downstream QA performance.
Found that semantic similarity can indicate domain diversity and that short chain-of-thought answers may flag lower-quality training data.
Co-author · TPCTC 2023
Benchmarking Large Language Models: Opportunities and Challenges
Co-authored a Lenovo and AMD review of how to compare LLM systems across training and inference—not only on accuracy and throughput, but also cost, energy, bias, trust, and sustainability.
Published by Springer in Lecture Notes in Computer Science; the chapter has been cited in subsequent benchmarking work.
Lenovo Press · Three-part engineering series
Making LLMs Work for Enterprise
I co-authored a practical series for enterprise teams building domain-specific RAG systems, from model selection and evaluation through synthetic dataset creation, LoRA fine-tuning, hardware sizing, latency, and production tradeoffs. I also developed a containerized framework that customers could use to implement the approach.
Model training experiments
Graduate AI coursework · 2024
Transformers under noisy sequence data
Designed a card-shuffle simulator and trained encoder-only PyTorch transformers to test how model depth and increasing randomness affect ace-sequence prediction. Deeper models learned subtle structure in low-noise sequences; performance degraded as shuffle complexity increased.
- PyTorch
- Transformers
- Synthetic data
Graduate AI coursework · 2024
Imitation learning in a real-time game
Collected gameplay trajectories and trained PyTorch policies with behavioral cloning and DAgger for two-agent control. The strongest independent-policy pair scored 18 goals across 32 evaluation games and held the same scoring rate against unseen agents.
- PyTorch
- Imitation learning
- DAgger
03
Background
Education
University of Texas at Austin
M.S. in Artificial Intelligence · Part-time · 2024–Present
Duke University
B.S.E. in Electrical & Computer Engineering · Certificate in Decision Science · 2017–2021
Technical toolkit
- Languages
- Python, TypeScript, SQL
- AI & ML
- PyTorch, Hugging Face Transformers, Pydantic AI, MCP, Langfuse, scikit-learn, XGBoost
- Web & APIs
- FastAPI, Node.js, Next.js, React
- Data & infrastructure
- AWS, Docker, Redis, PostgreSQL, pgvector, Supabase
04
Beyond the work
I am from Philadelphia, PA. I studied at Duke University. I currently live in Denver, CO.
I like playing and designing strategy board games, running, and tennis. My most useless skill is Etch A Sketch.
On the nightstand
What I'm reading
Drag or use the arrows to browse the shelf.
05
Contact