Exoplanet Discovery Initiative

Understanding distant worlds beyond our solar system. Developing the tools to help scientists understand the atmospheres, interiors and habitability of planets orbiting distant stars. 

Advancing a new era of exoplanet science

Thousands of planets have been discovered beyond our solar system. Today’s challenge isn’t finding more worlds; it’s understanding what they’re made of, how they’re formed and whether they could support life.

Researchers in The College of Liberal Arts and Science’s School of Earth and Space Exploration are developing new observational, computational and AI-powered methods that transform telescope data into reliable scientific knowledge. Their work helps prepare the scientific community for discoveries from the James Webb Space Telescope, Giant Magellan Telescope and future NASA missions. 

Triton's surface shown as a color mosaic

Research focus areas

Research acceleration

Leading observations with the James Webb Space Telescope and major ground-based observations while developing new ways to analyze planetary data.

AI and computational methods

Combining physics, machine learning and statistical modeling to improve how scientists interpret observations of distant planets. 

Training the next generation

Providing research opportunities for undergraduate students, graduate students and postdoctoral scholars working across astronomy, computing and statistics. 

Building community

Supporting seminars, visiting scholars, workshops, hackathons and open-source tools that strengthen the broader exoplanet research community.

Why ASU?

  • Leadership in more than 1,000 hours of James Webb Space Telescope observing programs
  • Leadership in AI and high-performance computing
  • Partnership in the Giant Magellan Telescope
  • Internationally recognized discoveries published in leading journals

Preparing for the next generation of discovery

Future observatories will produce unprecedented amounts of data about distant planets. The initiative is developing open, transparent methods that help scientists confidently interpret that information, advancing research into planetary formation, atmospheres and the conditions that make worlds potentially habitable. 

Student opportunities

Students can participate through:

  • Undergraduate research
  • Graduate fellowships
  • Summer research
  • Data hackathons
  • Cross-disciplinary mentorship
  • Open-source software development

Students gain experience working with real telescope data while developing skills in scientific machine learning, statistical inference and high-performance computing that translate across research and industry. They’ll have a chance to co-author publications, contribute to widely open-source tools and establish clear pathways into research and data-science careers.
 

Leading the initiative

Michael Line
Associate Professor
School of Earth and Space Exploration

Luis Welbanks
Assistant Professor
School of Earth and Space Exploration