ExoHabit: A Human-Centric Map to the Stars

Earth’s life-support is under strain. We rank exoplanets 0–1 for human-centric habitability using NASA data (insolation, temp, radius, mass, orbit) to pinpoint candidates for future human relocation.

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ExoHabit: A Human-Centric Map to the Stars

What inspired us

We love the cosmos—and we care about people. With Earth’s life-support systems under strain, we asked: if we ever needed it, which known worlds look most livable for humans? That spark became ExoHabit.

What our project does

NASA’s archive lists tens of thousands of exoplanets with ~387 columns each. We built a transparent 0–1 habitability score using the five most telling features—insolation flux, equilibrium temperature, radius, mass, and orbital distance—to surface a Top 10 shortlist for potential human relocation.

How we built it

  1. Grounding the “why”: Researched Earth’s habitability trends to frame urgency.
  2. Data pipeline: Pulled NASA’s pscomppars via TAP, cleaned/standardized, kept required fields, converted to Earth-relative units.
  3. Scoring model: Literature-informed preference curves per feature + interpretable weights → single 0–1 score (0 ≈ Earth-like).
  4. Visualization: Three Python programs—trend dashboards, candidate comparisons, and a ranked shortlist—optimized for clear, judge-friendly visuals.
  5. Validation: Sensitivity checks to see how rankings shift as weights change.

Challenges we faced

  • Scale & sparsity: Efficiently filtering a wide, uneven catalog without losing promising candidates.
  • Clarity: Turning dense science into clean plots—iterating Matplotlib/Plotly designs until insights were obvious at a glance.

What we’re proud of

For most of us, it was our first hackathon and our first time teaming up. We’re proud of how we communicated, divided work, and shipped a research-based scoring equation that brought many moving parts together.

What we learned

  • What truly makes Earth habitable—and which proxies (like equilibrium temperature or insolation flux) best signal human-livable conditions.
  • How to balance trade-offs: sometimes you down-weight nice-to-haves to emphasize human-critical factors (gravity/temperature/light).

What’s next

  • We can expand features/weights, add uncertainty and stellar-activity/radiation checks, and open-source the code.

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