AI, Engineering & Systems
01
Problems solved
LLM outputs were entering a permanent record unverified.
I built an AI-operable research workspace — an MCP server and CLI that lets an AI agent search, ingest, and sync papers across Zotero, Obsidian, and NotebookLM — with references that cannot be verified quarantined under an explicit failure taxonomy rather than silently accepted. Shipped and maintained publicly as research-hub-pipeline on PyPI.
Generative agents entered consequential simulation with no governance standard.
I co-authored the Water Resources Research (2026) study substituting LLM agents into a human-water simulation, and now build the evaluation methods that test whether such agents reproduce empirically measured human decisions — with ground truth I collected myself (a 937-household survey).
Catastrophe loss estimates are only as good as their validation.
I built a flood-loss pipeline that publishes its validation honestly — a 52,141-household coupled agent-based and catastrophe model with NFIP financial mechanics, validated against observed insurance claims — and worked on a team-built Hazus-based seismic bridge-loss pipeline validated at three levels against the 1994 Northridge earthquake, with failures reported, not hidden.
02
Systems
research-hub
Maintained open-source tool
AI-operable research workspace: a CLI, MCP server, REST API, and dashboard that drive repeatable literature workflows across Zotero, Obsidian, and NotebookLM.
PyPI research-hub-pipeline v1.1.1; listed in the Awesome MCP Servers catalog; tested on Windows, macOS, and Linux; an automated test suite that checks retrieval quality.
Case study →Repo↗
FLOODABM
Research prototype · Archived companion code
52,141-household coupled ABM × catastrophe flood model, Passaic River Basin, NFIP mechanics, calibrated on a 937-household survey I designed and fielded.
Public repo; Zenodo archive with CITATION.cff and published seed lists; known-limitations register.
Case study →Repo↗
Cat_framework
Research prototype · Team capstone
Team-built Hazus 6.1 seismic bridge-loss pipeline (hazard → exposure → fragility → EP/AAL).
Public repo; three-level Northridge validation with honestly reported failures.
Case study →Repo↗
codex-delegate
Maintained open-source tool
Cross-platform agent-delegation wrapper whose completion claims are verified from git state.
Public repo; Ubuntu/Windows CI; regression test pinning a real upstream stdin hang.
Case study →Repo↗
awesome-agentic-ai-zh
Maintained open-source tool
Trilingual agentic-AI curriculum (community/education line).
4.7k+ GitHub stars, 622 forks (July 2026); external contributors; automated checks keep all three languages in sync.
Case study →Repo↗
WAGF — a governance framework for LLM agents in human–water simulation, keeping coupled behavioral outcomes stable and physically sensible; research software in preparation for release.
03
Evaluation & validation record
- research-hubIn-repo retrieval-recall evaluation suite against golden fixtures; observed failures recorded as explicit audit baselines.
- research-hubA fail-closed anti-fabrication module with a transient-vs-permanent failure taxonomy.
- codex-delegateA regression test that reproduces a real upstream failure mode and fails without the fix.
- Cat_frameworkMulti-level hazard-model validation with honestly reported misses.
- FLOODABMSimulation validation against observed insurance-claims data.
Systems designed so that failure is visible — no silent passes.
04
Open-source contributions
18 merged pull requests in third-party open-source projects.
05
Capabilities
Python · Testing and CI · Evaluation design · MCP and agent tooling · Git · Cross-platform (Windows/POSIX) engineering · Catastrophe-risk stack: FEMA Hazus, fragility functions, exceedance-probability curves, NFIP mechanics