The Uses and Limitations of CNNs for Galaxy Merger Identification
10:00
Aizaan Akhmetzhanova
Detecting Model Misspecification in Cosmology with Scale-Dependent Normalizing Flows
10:20
Coffee
☕
10:50
Andrew Engel
Mantis Shrimp: Exploring Photometric Band Utilization in Computer Vision Networks for Photometric Redshift Estimation
11:10
Tri Nguyen
Constraining Dark Matter through Stellar Kinematics and Simulation-based Inference
11:30
Max Lee
Zooming by in the CARPoolGP Lane: new CAMELS-TNG simulations of zoomed-in massive halos
11:50
Dalya Baron
From data to insight: machine-assisted discoveries in the big data era in astronomy
12:20
Lunch
🥙
1:50
Lindsay House
Harnessing Citizen Science and AI for the Hobby-Eberly Telescope Dark Energy Experiment
2:10
Stephanie Juneau
Can ML/AI tell us why galaxies stop forming stars?
2:30
Tanmoy Lashkar
An Unsupervised Dive into Gamma-ray BurstAfterglow Classification
2:50
Coffee
☕
3:20
Shiro Mukae
Applying Deep Learning to Enhance Low-S/N Galaxy Identification in the HETDEX Spectroscopic Survey
3:40
Tjitske Starkenburg
Towards combined constraints on galaxy astrophysics, dust attenuation, and cosmology from galaxy luminosity functions and colors
4:00
Mini-Break
🚰
4:10
Career Panel
Kevin Gullikson, Randi Ludwig, and Eric Murphy
5:00
End
🌃
Wednesday, May 7th
Time
Presenter
Talk Title
8:30
Registration + Coffee
👋🏽 ☕
9:00
Peter Melchior
Optimizing Instrument Utilization and Survey Design with Structured Learning
9:30
Brian Kirk
RL for Radio Interferometry Data Processing
9:50
Yufeng Luo
Bad Imaging Exposure Identification with Self-Supervised Learning
10:10
Brian Mason
The CosmicAI Observable Universe Working Group: Use Cases and Vision
10:30
Coffee
☕
11:00
Guangwen Chen
AI-Driven Radio Source Detection and Classification for LOFAR, uGMRT, and SKA
11:20
Aritra Ghosh
Harnessing ML & Large Surveys to Probe Galaxy Evolution: from HSC Size-Environment Correlations to Rubin Anomaly Detection
11:40
Poster Talks
📊
12:10
Lunch + Poster Session
🥙 🖼️
2:10
Andrew Vanderburg
Can AI help reveal the elements/minerals that make up rocky exoplanets?
2:30
Maja Jablonska
SPICE: AI-Driven Stellar Spectral Synthesis with Surface Inhomogeneities and BinarySPICE: AI-Driven Stellar Spectral Synthesis with Surface Inhomogeneities and Binary Interactions
2:50
Coffee
☕
3:20
Zoe de Beurs
Enhancing exoplanet mass measurement precision with machine learning
3:40
Brett A. McGuire
Machine Learned Chemical Intuition for Automated Analysis of Spectral Line Observations
4:00
Mini-Break
🚰
4:10
Anna Lena Schaible
RUBIX: Fast and differentiable forward modeling of IFS observations
4:30
Marc Huertas-Company
Towards robust AI deployment for constraining the physics of galaxy formation.
5:00
End
🌃
Thursday, May 8th
Time
Presenter
Talk Title
8:30
Registration + Coffee
👋🏽 ☕
9:00
Alessandra Corsi
Optimizing radio observations of gravitational wave events: from present to future
9:30
Preshanth Jagannathan
SAM-RFI : An image segmentation approach to Radio Frequency Interference identification and flagging
9:50
Huaxi Chen
AI-driven Astronomical Discoveries with FAST
10:10
Javier Viana
Can Explainable AI Teach Us Astrophysics?
10:30
Coffee
☕
11:00
Hossen Teimoorinia
Utilizing Generative AI for Spectral Decomposition and Image Simulation of Next-Generation Space-Based Telescopes
11:20
Agglelos Katsaggelos
AI Accelerated Simulations with Multi-Scale Astrophysics using Physics-Based Deep Learning
11:40
Shunyuan Mao
Deep Operator Networks and Physics-informed Neural Networks for fluid dynamics in astronomy
12:00
Ghassem Gozalias
Plasma Physics Meets AI (Plasma AI): Towards Scalable and Intelligent Simulations
12:20
Lunch
🥙
1:20
Xuefei Tang
Accelerating 3D Photodissociation Region Modeling via Neural Ordinary Differential Equations
1:40
Aldana Grichener
Nuclear Neural Networks: Emulating Late Burning Stages in Core Collapse Supernova Progenitors
2:00
Grant Stevens
Improving The Practicality of Active Learning Pipelines inReal-World Problem Settings: A Case Study in The Classification of Astronomical Data
2:20
Qingyun Wang
AI4Scientist: Accelerating and DemocratizingScientific Research Lifecycle
2:50
Coffee
☕
3:20
Sebastian Joseph
AstroCodeBench: Evaluating Large Language Models for Specialized Code Reasoning in Astronomy
3:40
Howard Isaacson
Integrating a Large Language Model for querying Roman Space Telescope Data
4:00
Mini-Break
🚰
4:10
Matthew Ho
Practical Cosmological Inference With Learning the Universe
4:30
Sheena Panthaplackel
Harnessing the Coding Capabilities of LLMs
5:00
End
🙏🏽
Posters
Presenter
Talk Title
Thomas G. Bisbas
High-resolution 3D modeling of photodissociation regions
Carter Day
Improvements on NRAO Proposal Classification Model
Sanjana Gautam
Designing AI Agents to Assist Astronomy Research
Antonio Hales
AI-Powered Image Reconstruction: Unlocking Planet Formation Insights from ALMA Observations
Syed Hussian
AstroCodeBench: An Astronomy Domain-Specific Benchmark of Code Capabilities in Current Leading LLMs
Xuejian Jiang
Modeling the astrochemical properties of molecular clouds with 3D-PDR and PDFchem
Mst Shamima Khanom
AI-Driven Insights into the Baryon Cycle: Unveiling Galactic Evolution with Simulations
Hanwool Koo
Application of anomaly detection to MeerKAT radio data using machine learning techniques
Casey Law
Enabling a Radio Survey Revolution with DSA-2000 and Machine Learning
Jennifer Li
Fast and flexible inference framework for continuum reverberation mapping using simulation-based inference
Cicero Lu
Sequencing Silicates in the Spitzer IRS Debris Disk Catalog I: Methodology for Unsupervised Clustering
Amanda Lue
Cosmology with One Galaxy: Auto-Encoding the Galaxy Properties Manifold
Kuang Mao
PrestoZL: a gpu-accelerated high-throughput Jerk Search toolkit for binary pulsars
Adele Plunkett
ALMA Science Archive: Leveraging big data from start to finish
Richard Stiskalek
Inferring the Ionizing Photon Contributions of High-Redshift Galaxies to Reionization with JWST NIRCam Photometry
Josh Taylor
Searching for Structure in Spectral Cubes with Multiview Prototype Embedding and Clustering
Nina de la Torre
Modeling Chemical Networks
Giuseppe Viterbo
CASBI: chemical abundance simulation based inference
Digvijay Wadekar
Using interpretable ML to improve galaxy cluster mass estimation
Han Wang. Mr.
FAST-FREX and RaSPDAM: The Dataset and AI Method for Accelerating FRB Search
Charles Willard
Predicting Stellar Migration Histories of Disk Stars
Jackson Zariski
Machine-learning Applications to Telescope Pointing and Guiding
Gao-Yuan Zhang
Chemical evolution in MHD simulations of the CMZ
Dhruv Zimmerman
Reimagining SED Fitting with Simulations and Machine Learning
Zhengping Zhu
RAYTHEIA: A high-performance algorithm for 3D radiative transfer in astronomical simulations
