EWASS 2017 - Symposium S14
Astroinformatics: From big data to understanding the universe at large
Prague 29th - 30th June 2017
Programme
June 29th, Thursday | ||
---|---|---|
09:00 | Petr Škoda : Welcome and Logistics | [pdf] |
09:10 | Mark Allen : The Virtual Observatory - Enabling interoperability in Astronomy | [pdf] |
09:30 | Enrique Solano : The Virtual Observatory: A new framework for new science | [pdf] |
09:50 | Łukasz Wyrzykowski : Transient Sky in the Big Data Era | [pdf] |
10:10 | Sergio Molinari : VIALACTEA: 3D visualization-driven science analysis of large Galactic surveys from the infrared to the radio, and data-mining approaches to the evolutionary classification of star-formation sites. | [pptx] |
10:20 | Adriano Agnello : Mining for lensed quasars in wide-field surveys, and modelling challenges | [pdf] |
10:30 | coffee, Plenary presentations, lunch | |
14:00 | Laurent Eyer : Statistical and machine learning methods to analyse the one billion time series of Gaia | [pdf] |
14:20 | Agnieszka Pollo : Automatic classification of sources in large astronomical catalogues | [pdf] |
14:40 | Kai Polsterer : Uncertain Photometric Redshifts | [pdf] |
15:00 | Daria Dobrycheva : Machine learning technique for morphological classification of galaxies from SDSS | [pdf] |
15:10 | Sabrina Einecke : Machine learning approach for the search of high-confidence blazar candidates and their multiwavelength counterparts | [pdf] |
15:20 | Gabor Marton : An all-sky support vector machine selection of WISE YSO candidates | [pdf] |
15:30 | coffee | |
16:00 | Marco Antonio Alvarez : Enhanced SOM distributed processing for the classification of large spectroscopic data in the Gaia mission. | [pdf] |
16:10 | Marco Antonio Alvarez : A distributed and enhanced implementation of unsupervised ANNs applied to spectrophotometry clustering in the ESA Gaia mission. | [pdf] |
16:20 | Diego Tuccillo : Deep leaning for galaxy surface brightness profile fitting | [pdf] |
16:30 | Vesna Lukic : Classifying radio galaxies with deep learning | [pdf] |
16:40 | Diego Tuccillo : Transfer of knowledge in convolutional neural networks for morphological classification of galaxies | [pdf] |
June 30th, Friday | ||
09:00 | Petr Škoda : Logistic - COST Action | [pdf] |
09:02 | Darko Jevremović : LSST data products | [pdf] |
09:20 | Edwin A. Valentijn : Big Data in Space- Big data in our Computers | [pptx] |
09:40 | Karine Zeitouni : Large Scale Data Management of Astronomical Surveys with AstroSpark | [pdf] |
10:00 | Dejan Vinkovic : Challenges of Big Data processing and machine learning in meteor science | [pptx] |
10:20 | Guilhem Lavaux : Fully non-linear statistical analysis of Large scale structure data for wide and deep surveys | [pdf] |
10:30 | coffee, Plenary presentations, lunch | |
14:00 | Giuseppe Longo : The art of getting science from astronomical data deluge | [pdf] |
14:20 | Aleksandra Solarz : Space and cyberspace: hidden patterns in astrophysical datasets | [pdf] |
14:40 | Ashish Mahabal : The Big Picture from the Bottom Up | [pdf] |
15:00 | Emille Ishida : Domain adaptation and active learning for SNe photometric classification | [pdf] |
15:20 | Gregor Traven : Exploring large spectroscopic surveys using t-SNE reduction of spectral information | [pdf] |
15:30 | coffee | |
16:00 | Rafael De Souza : A data-driven probabilistic approach for emission-line galaxy classification | [pdf] |
16:20 | Johan H. Knapen : SUNDIAL: combining astronomy and computer science to understand the formation and evolution of galaxies | [pptx] |
16:40 | Engelbert Mephu Nguifo : Photo-Z redshift reconstruction using a constructive multilayer perceptron. | [pdf] |
16:50 | Ondřej Podsztavek : Deep Learning in Large Astronomical Spectra Archives | [pdf] |
17:00 | Martin Vo : Light Curves Classifier - Package for obtaining and classifying light curves | [pdf] |
17:10 | Jan Okleštěk : Search for UV Ceti type stars in astronomical surveys using machine learning methods with Python | [pdf] |
17:20 | Petr Škoda : Conclusions and Thanks" | [pdf] |
Posters
Viviana Acquaviva | Measuring the metallicity of galaxies using machine learning | [pdf] |
Eliana M. Amazo-Gomez | Understanding brightness variations of Sun-like stars on the timescale of stellar rotation | |
Maarten Breddels | Visualization and exploration of the a billion stars in the Jupyter Notebook | [pdf] |
Giorgio Calderone | QSFit: Automatic analysis of optical AGN spectra. | [pdf] |
Klemen Čotar | Stellar chemical tagging using phylogenetic trees | [pdf][pdf] |
Rafael De Souza | On the realistic validation of photometric redshifts, or why Teddy will never be Happy | [pdf][pdf] |
Didier Fraix-Burnet | Unsupervised classification in high dimension | [pdf][pdf] |
Laurence Chaoul | Processing Gaia’s Billion Stars in CNES, a Big Data Story | [pdf] |
Emille Ishida | Exploring the spectroscopic diversity of type Ia supernovae with DRACULA: a machine learning approach | [pdf][pdf] |
Doogesh Kodi Ramanah | Optimal and fast Wiener filtering of CMB maps without preconditioning | [pdf][pdf] |
Svitlana Kolomiyets | Adapting meteor databases to applied research | [pdf] |
Marcos Lopez Caniego | The Planck Legacy Archive, more than just a repository | [pdf] |
Dmitry Makarov | HyperLEDA database | [pdf] |
Kaisey Mandel | The Type Ia Supernova Color-Magnitude Relation and Host Galaxy Dust: A Simple Hierarchical Bayesian Model | |
Bruno Merín | ESASky: a science-driven discovery portal for ESA astronomy missions | [pdf] |
Areg Mickaelian | Using big data from large area extragalactic surveys for understanding AGN properties in the Local and Far Universe | [pptx] |
Matteo Miluzio | The Quick Look Analysis (QLA) software for the ESA Euclid mission | [pdf][pdf] |
Emilio Molinari | WAS for WEAVE: our NoSQL approach. | [pdf] |
Jiří Nádvorník | Cross-matching Engine for Incremental Photometric Sky Survey | [pdf][pdf] |
Javier Pascual-Granado | A tool for identifying biases in the harmonic analysis of massive astronomical datasets | [pdf] |
Artem Poliszczuk | Fuzzy logic svm based classification for large astronomical data sets | [pdf] |
Christoph Schaefer | Lenstool-HPC, A high performance computing approach to lens-modelling | [pdf] |
Gyula Szabó M. | Cosmic Risks and Hazards | |
Iryna Vavilova | The inverse median filter as a new approach to the CCD-frames calibration and processing of the big data-sets in automatic mode | |
Branislav Vlahovic | CMB uniformity and geometrical solution of horizon problem without inflation |