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