Open-source work, side projects, talks and hackathon judging.
Scout
Side project
Describe a task and find model candidates on Hugging Face. Scout searches live repository records, reads model cards, and compares task fit, language metadata, licenses, estimated weight memory and available inference providers. Recommendations link to their evidence, with setup snippets and shareable searches.
A local app and CLI that watches what AI coding agents read and run, flags prompt injections and leaked secrets, and holds risky steps for an engineer's approval. It runs entirely on the user's machine and is open source (Apache-2.0). Lucas built its on-device model, Llama-Doorman-22M, and the research pipeline behind it.
A browser lab for comparing two open AI-text detectors: TMR RoBERTa and ModernBERT trained on RAID and MAGE. It runs models locally, maps scores passage by passage, exposes model disagreement and limitations, and presents every result as a screening signal rather than proof of authorship.
A browser lab for looking inside a language model: it runs a small story-writing model (TinyStories), or any GPT-Neo or GPT-2 model a visitor picks from Hugging Face, on a forward pass written in JavaScript with a WebAssembly SIMD kernel for its matrix multiplies, shows every MLP neuron and attention head firing token by token, and lets visitors cut, boost, invert or clamp them and compare the edited model's story with the original's. It's on this site's desktop (Dissector, or `app dissect` in its terminal).
A browser lab for the features inside a language model: a TopK sparse autoencoder splits TinyStories' residual stream into thousands of features, either a ready-made atlas or one a visitor trains on their own device for any layer. Visitors browse the features as a map, see the text that fires each one and the words it pushes the model toward, and clamp a feature on or cut it out while the model writes, next to the untouched original. It runs on Neuron Dissector's forward pass. It's on this site's desktop (Prism, or `app prism` in its terminal).
A browser lab for why a RAG system answered what it did: it follows every passage of a document set (the site's notes, or a visitor's own files, which never leave the page) through chunking, BM25 keyword search, embedding search, their hybrid, a cross-encoder reranker, the context window and the answer, on one chart. Answers come from Workers AI, which sees only the question and the passages that reached the context, or from a small model in the browser; citations, numbers no passage contains and weakly supported sentences are flagged. Visitors poison a passage (a swapped number, a planted instruction, a keyword decoy) and see whether retrieval or the model passes it on. It's on this site's desktop (Autopsy, or `app autopsy` in its terminal).
An AI that uses this site's desktop in plain sight: given a task, it searches notes and profile files, opens apps, clicks, picks options, types and reads, one step at a time, with a visible cursor and a persistent pause/resume control. Each step, the page sends a text snapshot of the desktop's controls to Llama 3.3 70B on Workers AI, which picks one action as schema-checked JSON; the page runs it on its own controls, blocks sending messages and leaving the site, and asks the visitor before any download. Every step is logged with what the model said it saw and what happened, unsupported numbers are flagged, and bundled tasks check their expected result. It's on this site's desktop (Intern, or `app intern` in its terminal).
An llms.txt generator for any link: it turns a website, docs section, article, GitHub repo or PDF into an llms.txt index and an llms-full.txt with the content. A model groups the links into sections and writes the descriptions, but refers to links only by number, so it can't add a URL that wasn't on the page.
A video downloader for any link: paste a YouTube, Instagram, X, TikTok or Bluesky link and get the video as MP4 (up to 1080p) or MP3, save it, or send the file itself to WhatsApp from a phone's share sheet; or put gimmeclip.com/ in front of any video link. Downloads run in Cloudflare Containers with yt-dlp and ffmpeg. It's on this site's desktop too (gimmeclip, in Tools).
An evidence-graded peptide reference library and wiki: 60+ peptides and blends tiered S–D by the strength of published evidence, with FDA and anti-doping (WADA) status and citations checked against PubMed.
StartupRIO 2017 (2017): Finalist with a platform helping cancer patients in the public health network start treatment within the 60 days required by state law.
Rio Oil & Gas Expo and Conference 2016 (Oct 2016): Presented the GasPipelineDesign Suite mobile app through a pipeline case study.
Rio Pipeline Conference & Exposition 2015 (Sep 2015): A methodology combining market pipeline simulators with the GasPipelineDesign Suite to optimize gas pipeline design.
Hackathons
Judge — Hacktech 2026 (Caltech, Apr 2026): Reviewed 60+ submissions and judged finalists' live demos.
Judge — HackMIT 2025 (MIT, Sep 2025): Read all 35+ submissions in the judging group and scored finalists.