Star formation results from a complex, non-linear interplay between gravity, turbulence, magnetic fields, radiation and stellar feedback. Machine learning, combined with numerical simulations, can effectively cut through the messiness of observation and simulation data to provide insights into the underlying physical behavior. I will describe several recent studies that apply supervised and unsupervised machine learning methods to tackle fundamental star formation questions: What is the distribution and impact of stellar feedback in molecular clouds? How does dense gas become star-forming? What is the future evolution of star-forming regions?

Speaker: Stella Offner (The University of Texas at Austin)

The 2024 Fall Colloquium talks are held on Wednesdays at 3:00 PM. This colloquium is hosted by STScI and will be held as an in-person and virtual event.

You may join in person at STScI’s John N. Bahcall Auditorium or virtually on STScI's Live Science Events Facebook page.

Please direct questions or comments to contact above. The 2024 Fall Colloquium Committee members are: Nestor Espinoza (STScI), Joel Green (STScI), Nick Indriolo (STScI), Elena Manjavacas (STScI), Namrata Roy (JHU), Kevin Schlaufman (JHU), Ethan Vishniac (JHU).