Professionally, I have over nineteen years of experience as a software engineer. Academically, I have a master’s degree in computer science. Recreationally, I have been coding since I was in grade school. Seven publications. Three-time JupyterCon presenter.
As a Staff Software Engineer and AI Architect, I lead the development of distributed platforms and agentic AI tools for the scientific community:
- GenePattern Copilot: An agentic AI assistant utilizing hallucination-resistant RAG & MCP pipelines to guide users through complex bioinformatics workflows.
- GenePattern Module AI Toolkit: A toolkit leveraging Pydantic AI and structured LLM outputs for zero-shot schema compliance and automated code generation.
- GenePattern MCP: Model Context Protocol (MCP) server designed to safely expose GenePattern's RESTful API to LLM agents.
- g2nb: A platform integrating the research narrative capabilities of JupyterLab with popular open-source computational genomics tools.
- AI & ML: Agentic AI, MCP, RAG, LLMs, Multi-Agent Orchestration, Pydantic AI, LangChain, LangGraph, Vector Databases, Embeddings, Prompt Engineering, Logfire, OpenTelemetry, Model Evaluation, LoRA Fine-Tuning, Synthetic Data Generation, Hugging Face, vLLM, Scikit-Learn, Pandas, NumPy
- Infrastructure: Python, Django, FastAPI, RESTful APIs, JavaScript, TypeScript, SQL, Docker, AWS, GCP, Linux, Distributed Systems, Celery, RabbitMQ, Git, CI/CD, OAuth, MongoDB, Kubernetes
- Scientific Computing: Jupyter, HPC, Bioinformatics Tooling, Genomics Pipelines, NGS Data Analysis, Single-Cell Transcriptomics, Multiomics, Open-Source Software