Kavli Institute for Theoretical Physics Courses

Computational and AI Funding Opportunities - Andreas Berlind (NSF)

Explore NSF funding opportunities for computational and AI research in astrophysics. Learn about available grants and how to apply for support in astrostatistics and machine learning projects.

• YouTube
• 43 minutes
• On-Demand
• Free Video

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.

• YouTube
• 31 minutes
• On-Demand
• Free Video

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.

• YouTube
• 29 minutes
• On-Demand
• Free Video

Finding Environmental Measures Sensitive to Halo Properties Using Neural Networks

Exploring neural networks to identify environmental measures that reveal halo properties in galaxy formation studies, enhancing our understanding of cosmic structure evolution.

• YouTube
• 27 minutes
• On-Demand
• Free Video

The Brightest Cluster Galaxy and Intracluster Light - Louise Edwards

Explore the Brightest Cluster Galaxy and Intracluster Light in this talk by Louise Edwards. Gain insights into galaxy clusters, their central galaxies, and the diffuse light between them.

• YouTube
• 29 minutes
• On-Demand
• Free Video

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.

• YouTube
• 24 minutes
• On-Demand
• Free Video

Star Formation Histories of Galaxies Near and Far

Explore galaxy formation and evolution through star formation histories, using advanced statistical and machine learning techniques to analyze vast datasets from current and future astronomical surveys.

• YouTube
• 25 minutes
• On-Demand
• Free Video

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.

• YouTube
• 30 minutes
• On-Demand
• Free Video

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.

• YouTube
• 30 minutes
• On-Demand
• Free Video

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.

• YouTube
• 29 minutes
• On-Demand
• Free Video

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.

• YouTube
• 26 minutes
• On-Demand
• Free Video

Learning from Simulations - Marc Huertas Company

Explore astrostatistics and machine learning in galaxy formation, comparing models with observations and discussing innovative data analysis techniques for advancing astrophysical understanding.

• YouTube
• 34 minutes
• On-Demand
• Free Video

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.

• YouTube
• 27 minutes
• On-Demand
• Free Video

Unsupervised Learning for Stellar Spectra with Deep Normalizing Flows - Jo Ciuca

Explore unsupervised machine learning techniques for analyzing stellar spectra using deep normalizing flows, with applications in galaxy evolution and big data astronomy.

• YouTube
• 28 minutes
• On-Demand
• Free Video

Towards Astronomical Search by Image - The Hubble Image Similarity Project - Josh Peek

Exploring astronomical image similarity using machine learning, focusing on the Hubble Image Similarity Project to enhance search capabilities and facilitate new discoveries in astrophysics.

• YouTube
• 30 minutes
• On-Demand
• Free Video