AstroInformatics 2019

The final agenda can be found here

The conference ended with a hackathon

The best student paper winners are:

  • Manuel Pérez: Adversarial variational transfer for semi-supervised domain adaptation
  • Joshua Yao-Yu Lin: Hunting for dark matter substructures with neural networks



Monday, June 24 Data Science and X-informatics
9:15 10:00 Umaa Rebbapragada Tutorial: Machine Learning basics
10:30 11:15 Dima Duev  Tutorial: Deep Learning
11:15 12:00 Matthew Graham Tutorial: Time series analysis
1:15 2:00 Anima Anandkumar Opening Keynote: Artificial Intelligence
2:00 2:30 Tapio Schneider Clouds, Climate, And Data-Informed Earth System Modeling
2:30 3:00 Lior Pachter High-Dimensional Data Analysis In Astronomy And Biology
4:00 4:45 Santiago Lombeyda Tutorial: Data Visualization
4:45 5:00 George Djorgovski A special announcement
Tuesday, June 25 Astroinformatics Methods and Applications
9:00 9:30 Ajit Kembhavi Applications of Deep Learning in Astronomy and Electron Microscopy
9:30 10:00 Ashish Mahabal Deep Learning for classification in astronomy and biomedicine
10:00 10:15 Banafsheh Beheshtipour  Clustering Observational Data Using Deep Learning Network
10:15 10:30 Joshua Yao-Yu Lin Hunting for dark matter substructures with neural networks
11:00 11:30 Kai Polsterer From Photometric Redshift to Improved Weather Forecasts: An Interdisciplinary View of Machine Learning in Astronomy
11:30 11:45 Giuseppe Longo Star Formation Rates as a ML Problem: An Application to SDSS Data
11:45 12:00 Andres Galarza Random Forest applied to the photometric survey JPLUS
1:30 2:00 Andy Connolly Looking Below the Noise - Asteroid Hunting With the LSST
2:00 2:15 Dima Duev Deep learning for the Zwicky Transient Facility (ZTF): real/bogus classification
and identification of fast-moving objects
2:15 2:45 Pavlos Protopapas Physical Symmetries Embedded in Neural Networks
2:45 3:00 Stephen Portillo Dimensionality Reduction of SDSS Spectra with Autoencoders
3:30 4:00 Alberto Krone-Martins Strongly Lensed Quasars: Where Entropy Meets Astrometry, Wavelets And Machine Learning
4:00 4:30 Peter Tino Dynamical Systems as Feature Representations for Learning from Data
Wednesday, June 26 Astroinformatics for Large Projects
9:00 9:30 Rich Doyle JPL, Autonomy, and Data Science
9:30 10:00 Kiri Wagstaff Anomaly Detection And Explanation In Galaxy Observations From The Dark Energy Survey
10:00 10:15 Asad Khan Deep Learning at Scale for the Construction of Galaxy Catalogs in the Dark Energy Survey
10:15 10:30 Antonio D'Isanto ESCAPE to victory: building the infrastracture for next generation astronomy
11:00 11:30 Bruce Bassett Scaling Towards Exabyte Science With The SKA
11:30 11:45 Tim Galvin Using a semi-supervised method for radio source classification using PINK
11:45 12:00 Erfan Nourbakhsh Managing scalable data workflows on HPC clusters
1:30 2:00 Matthew Graham Can We Predict the Future of Aperiodic Sources?
2:00 2:30 Francisco Forster The Universe in a Stream: Building the ALeRCE Broker
2:30 2:45 Manuel Pérez Adversarial variational transfer for semi-supervised domain adaptation
2:45 3:00 Vijay Varma Data-driven modeling of numerical relativity simulations
3:30 4:00 Jess McIver Noise Mitigation Methods For Gravitational Wave Detectors
4:00 4:15 William Wei Gravitational Wave Denoising of Binary Black Hole Mergers with Deep Learning
4:15 4:30 Kent Blackburn GWOSC: Gravitational Wave Open Science Center
Thursday, June 27 Methodology transfer, quantum computing, and looking ahead
9:00 9:30 Dan Crichton Enabling Methodology Transfer for Scientific Analysis from Space Science
to Biomedicine
11:00 11:45 John Preskill Closing Keynote:  Quantum Computing: Reality vs. Hype
Carlos Barbosa Using probabilistic programming to study stellar populations of galaxies
Marco Canducci Clustering compact-binary objects in the parameter space 
Richard Feder Multiple Band Probabilistic Cataloging: A Joint Fitting Approach to Source
Detection and Deblending
Erica Hopkins Crowdsourcing to GPUs​: semi-automated classification of radio morphologies
for 946,419 sources in FIRST with 299,266 IR counterparts in UKIDSS
Collin McLeod Autoencoders and Quasar Emission Lines: Using New Techniques to Solve
an Old Problem