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Although we know of thousands of exoplanets, moons outside the Solar System are largely unknown. We develop methods to discover and characterize moons, and have led observational searches. For example, we discovered the first candidate Kepler-1625b I.


Trying to figure out why exoplanet populations look the way they do, is like trying to learn chess by watching games without context. We apply machine learning and natural language processing methods to try and solve this - so that we can master the game.


Statistics provides a window into what's real and what's not. We develop and apply statistics methods, particularly in the analytic arena, to a range of problems from astrobiology to parameter inference. We particularly enjoy weakly constrained problems.


Exoplanets are at the core of our work. We typically leverage survey data, such as Kepler and TESS, to detect and validate new extrasolar planets. A particular focus has been validation without the need for followup observations, such as dynamically interacting planets.

planet detection

Astronomers think about the world differently. In astro engineering, we try to apply this distinct mindset to challenges such as interstellar propulsion, communication systems, climate change and telescope design - such as the Terrascope system.



To us, the end point of exoplanetary research is to resolve whether other civilizations share the stars with us. That is our destiny. We encourage and engage in research on detecting other technologies in astronomical data and placing limits where possible.

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