Yuan-Sen Ting

Research reveals how metals influence galaxy evolution and star formation.

Researchers use a novel approach to find signs of parity violation in galaxy distributions.

Self-supervised learning enhances predictions for stellar time series data.

A study on how new ideas transform astronomical research through technology and collaboration.

This article examines how galaxy mergers influence insitu star formation.

A new framework utilizes machine learning for efficient literature review in astronomy.

Dwarf galaxies reveal insights into star formation and chemical evolution.

Scientists use neural networks for a deeper look into galaxy data.

New research sheds light on the Milky Way's early formation through metal-poor stars.

Mephisto streamlines data analysis in astronomy, improving hypothesis generation.

A new AI assistant for astronomy enhances research and education.

Learn how attenuation bias affects our view of the universe.