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Rekin226/README.md

Abdoul Rachid Ouédraogo (韋正)

Typing SVG

Applied AI Researcher @ Taiwan Polar Institute · Founder of POUK YAM

LinkedIn Hugging Face Website Location


Building agentic AI platforms for national agencies: MCP servers, tool-calling analysts, data collectors, forecasting models, dashboards.

Background: 6+ years across R&D, application development, and research, including LLM agents with RAG and ML shipped in a commercial product.


🚀 Featured projects

AquaScope ⭐ 30

PyPI DOI MCP

Explore river records and run reproducible water analyses in your browser or in Python, with an agent on top.

  • 37 global water-data sources behind one Pydantic schema: USGS, UK EA, Hub'Eau, GRDC, FAO, GEMStat, EU WFD
  • Every river on a globe: ~6.8M GEOGLOWS reaches, 15-day forecasts, an A to D evidence ladder grading global models, flood layers back to 1990
  • AI on the map: ask the map, explain this view, review your model results, run what-if scenarios
  • Studio: a seven-role agent crew plans, runs, and signs off a study, returning Word, Excel, notebook, and engineering exports (HEC-RAS/HMS, SWMM, MODFLOW 6)
  • MCP server for Claude or Cursor · HydroGym RL calibration environment
  • 3,200+ tests · CAMELS-validated · 30+ outside contributors · Zenodo-archived

Explorer

Agronaut ⭐ 5

PyPI Runs local

Open-source agriculture assistant you run on your own machine: a multimodal tool-calling agent over a deterministic, cited engineering core.

  • LLM collects and routes; a validation gate guards a pure, tested trust zone that does the math, and every number in a reply is checked against what the engine computed
  • Cited aquaponics and hydroponics design (10 fish, 34 crops), farm and crop records, and experimental field-irrigation checks (drip, sprinkler, soil water)
  • Photos and voice notes on Telegram, WhatsApp, and the web; a cited table returns a ranked differential, never a verdict
  • RAG measured, not asserted: hit 0.879 · recall 0.833 · MAP 0.604 · 8/10 off-topic refused; nine techniques benchmarked, four ship. Faithfulness ~0.8, citation accuracy 1.00, judge agreement reported too
  • 1,770+ tests · advice-safety golden set in CI · agronaut eval · DPG compliance pack

PyTorch PhysicsNeMo

A differentiable research twin of Taiwan's Choushui alluvial fan: pumping policy in, groundwater heads and land subsidence out, gated against held-out data at every stage.

  • 174 monitoring wells, 116,769 metered pumps, 798 leveling benchmarks, 2012–2022, on a 1 km four-aquifer grid
  • Full chain hindcast of subsidence: R² 0.639, RMSE 5.7 cm across 36 ensemble members; compaction column R² 0.652 out of fold
  • Policy projections to 2032 (36 members × 3 policies × 21 years in ~50 min on one GPU) and a decision app with orthophoto and terrain
  • Failures published, not hidden: on new 2023–2026 data the frozen forecast loses to seasonal climatology (RMSE 2.07 m vs 1.67 m), and every gate verdict is in the README

Live demo

MMS NLLB

Speech recognition and translation for Mooré, a language of ~8M people and almost no training data.

  • ASR corpus of 37,654 utterances / 85 h; fine-tuned MMS-1b reaches 16.8% WER / 4.3% CER on 564 held-out utterances, vs 31.1% zero-shot
  • Curated 205,271 parallel pairs across 4 directions: LID-gated, fragment-filtered, decontaminated against FLORES-200
  • LoRA fine-tunes of NLLB-200 600M and 3.3B on a single consumer RTX 4070
  • Honest about what isn't solved: a native-speaker blind A/B puts translation at a coin flip, so it ships as unproven
  • Three adapters on the Hub · Colab demo

paper-agent ⭐ 8 · Claude Code plugin Semantic Scholar

A Claude Code plugin that turns the agent into a disciplined manuscript collaborator. Six strict modes (draft, review, revise, proofread, audit, format), Semantic Scholar MCP citation resolution with no API key, anti-fabrication guardrails, a number checker that traces every figure to its source, and a submission-ready .docx with a compliance report. Ships profiles for 10 journals (Hydrogeology Journal, J. Hydrology, WRR, HESS, Groundwater, IEEE TIM, and more) plus a generic quantitative-science profile. Install with one command: /plugin marketplace add Rekin226/paper-agent.


🛠️ Tech stack

tech stack

PyTorch · Hugging Face (transformers, PEFT, datasets) · LangChain · LangGraph · AutoGen · MCP · CUDA / bf16 · NVIDIA PhysicsNeMo · RAG & vector search (FAISS) · Ollama / vLLM · pandas · NumPy · SciPy · FastAPI · Django · PostgreSQL · Docker · GitHub Actions · pytest · Streamlit · Gradio

🔬 Interests

Agentic AI & tool use · LLM fine-tuning for low-resource languages · Evaluation, guardrails & AI safety in production · Physics-informed & scientific ML · Uncertainty quantification · AI as a digital public good


📈 GitHub activity

stats top langs streak trophies

Open to conversations about AI/ML engineering roles and collaborations. LinkedIn · rachidouedraogo.com

POUK_YAM AquaScope

Building AI for science · Taichung, Taiwan

Pinned Loading

  1. aquascope aquascope Public

    Explore river records and run reproducible water analyses in your browser. Open hydrology data, methods, and exports.

    Python 30 41

  2. paper-agent paper-agent Public

    Claude Code plugin to draft, review, revise, proofread, and audit quantitative-science journal manuscripts at submission quality. Five strict modes, Semantic Scholar MCP citation integrity (no API …

    Python 8 2

  3. HydroPhysicsAI HydroPhysicsAI Public

    GPU physics-informed neural operators for groundwater, benchmarked against per-well gray-box ODEs (PyTorch / PhysicsNeMo / CUDA)

    Python 3

  4. Agronaut Agronaut Public

    An open-source AI agronomy agent that runs locally on your own machine or server, reaches you on Telegram and WhatsApp, and computes aquaponics system designs from a deterministic, source-cited eng…

    Python 5 15

  5. aquascope-demos aquascope-demos Public

    Real-world hydrology demo cases for AquaScope. Self-contained reproducible Jupyter notebooks with every headline result checked against a published reference.

    Jupyter Notebook

  6. groundwater-prediction-graybox-model groundwater-prediction-graybox-model Public

    Gray-box modeling workflow for groundwater level prediction in the Zhuoshui Alluvial Fan, Taiwan. Companion code to a Hydrogeology Journal manuscript.

    Python