Source for abensonca.github.io — Andrew Benson's research site. Built with Jekyll on GitHub Pages.

.
├── _config.yml             Site config + author metadata
├── _data/
│   ├── navigation.yml      Top-nav items
│   ├── highlights.yml      Front-page research-area cards
│   ├── members.yml         Group-member manifest (single source of truth)
│   ├── code.yml            Software/projects on /code/
│   ├── cv.yml              CV entries
│   └── papers.yml          AUTO-GENERATED — recent ADS papers
├── _layouts/               default / page / home
├── _includes/              nav, footer, paper-card, member-card
├── _sass/main.scss         Custom theme (no parent theme, light + dark mode)
├── assets/
│   ├── css/style.scss      Loads _sass/main.scss
│   └── img/                Static figures + auto-generated paper figures
├── scripts/
│   ├── fetch_papers.py     ADS query → AI summary + figure → _data/papers.yml
│   └── fetch_affiliations.py ORCID employments → members.yml
└── .github/workflows/
    ├── update-papers.yml         Weekly
    └── update-affiliations.yml   Monthly

Recent papers and (where ORCID iDs are listed) alumni affiliations refresh themselves on a schedule — see below.

Append an entry to _data/members.yml:

- name: Jane Doe
  role: Graduate student (USC)
  status: current             # or "alumni"
  website: https://example.com
  orcid: 0000-0000-0000-0000  # optional; enables auto-updated affiliations

Set affiliation_locked: true to prevent the scheduled job from overwriting that member's current_affiliation.

Runs weekly. For each selected paper from the configured ADS library it:

1. Fetches metadata from NASA ADS.
2. Downloads the arXiv PDF, renders the first ~12 pages.
3. Asks a small vision-capable model on GitHub Models to pick the page containing the most representative figure.
4. Crops whitespace and saves the figure to assets/img/papers/.
5. Asks the same model for a two-sentence plain-English summary.
6. Writes the result to _data/papers.yml and commits it back to the repo.

If a paper already has a figure on disk and a summary in the data file, the expensive steps are skipped — so re-runs are cheap.

Create a repo secret named ADS_API_TOKEN with a NASA ADS API token (generate one here). The default GITHUB_TOKEN is wired up for GitHub Models access via the models: read permission declared in the workflow.

From the Actions tab, run Update papers with an optional limit input.

Runs monthly. Calls the public ORCID API for every member that has an orcid: field set, finds their most recent employment, and updates current_affiliation: in _data/members.yml. Members without an ORCID iD, or with affiliation_locked: true, are left alone.

Why not LinkedIn? LinkedIn's terms of service prohibit scraping and they aggressively block unauthenticated traffic. ORCID is the practical alternative for academics — it has a public API and many alumni already have profiles.

bundle install
bundle exec jekyll serve --livereload

Then visit http://127.0.0.1:4000/.

To preview the auto-generation pipelines locally:

pip install -r scripts/requirements.txt
ADS_API_TOKEN=… GITHUB_TOKEN=… python scripts/fetch_papers.py
python scripts/fetch_affiliations.py --check    # dry run

Site content is © Andrew Benson. The bundled _sass/normalize.scss retains its original MIT license.