The CAMELS Project - Paco Villaescusa Navarro
Exploring the CAMELS project: a large-scale simulation suite for galaxy formation and cosmology, combining hydrodynamics and machine learning to advance our understanding of the Universe.
Finding Simple Structures in Complex Datasets - Dalya Baron
Exploring data-driven techniques to uncover simple structures in complex astronomical datasets, focusing on galaxy formation and evolution using advanced statistical and machine learning tools.
How Supermassive Black Holes Ignite the Intergalactic Medium - Tales from the Low Redshift Lyman-alpha Forest
Explore how supermassive black holes impact the intergalactic medium through the lens of the low redshift Lyman-alpha forest, offering insights into galaxy formation and evolution.
Dust Properties of Galaxies from a Data-Driven Hierarchical Model - John Forbes
Explore data-driven hierarchical modeling to uncover dust properties in galaxies, revealing insights into galaxy formation and evolution through advanced statistical techniques.
Galaxy Zoo in the Deep Learning Era - Mike Walmsley
Exploring Galaxy Zoo's evolution with deep learning, focusing on self-supervised techniques and new tools for galaxy morphology analysis in the era of big astronomical data.
Galaxy Merger Reconstruction with Generative Graph Neural Networks - Yuan Sen Ting
Exploring galaxy merger reconstruction using generative graph neural networks, advancing our understanding of galaxy formation and evolution through innovative machine learning techniques.
Learning to Simulate the Universe with Deep Learning - Elena Giusarma
Explore deep learning techniques for simulating the universe, focusing on innovative approaches to model cosmic structures and enhance our understanding of galaxy formation and evolution.
Outliers - How I Learned to Love Them, and Why You Should Too
Discover the value of statistical outliers in galaxy formation studies. Learn how anomalous galaxies challenge current paradigms and drive new insights in astrophysics and cosmology.
Tracing Dark Matter with Stars - Lina Necib
Explore innovative techniques for detecting dark matter using stellar dynamics. Learn how advanced statistical methods and machine learning are revolutionizing our understanding of galactic structure and evolution.
Cosmology - DM Halo - Local Group - Risa Wechsler (Stanford)
Explore cosmology, dark matter halos, and the local group with Stanford researcher Risa Wechsler. Gain insights into cutting-edge astrophysical concepts and their implications for our understanding of the universe.
Modeling Dwarf Galaxy Formation with UniverseMachine - Richie Wang (Stanford)
Explore dwarf galaxy formation using UniverseMachine, a statistical tool for modeling galaxy evolution in cosmological simulations. Learn about abundance matching, multiresolution simulations, and future research directions.
Black Hat USA 2025
Black Hat USA 2025