Projects

Research Literature Monitor

Python
RSS
LLM
GitHub Actions
YAML
Automated Literature Screening
Keyword and Semantic Filtering
Research Monitoring

An automated RSS and LLM pipeline that scans newly published research papers, filters them for relevance to subseasonal-to-seasonal forecasting and compound weather extremes, and logs matched papers for review.

Placeholder — image coming soon

Keeping up with the volume of new research across S2S prediction, compound extremes, and AI weather modelling is a constant challenge. This project automates that process with a lightweight pipeline that pulls new papers from journal RSS feeds, scores them against a configurable research profile using an LLM, and logs relevant hits for later review.

The screening prompt is shaped by a profile derived from my Zotero library using the zotero-mcp server, which extracts key journals, topics, and methods to ground the relevance scoring in my actual reading history.

View on GitHub →