Previous Meetings and Events

2022 Asia-Pacific Conference on Applied Mathematics and Statistics. 

Detailed information can be found here.

Detection of gravitational waves requires the operation of very sophisticated detectors producing large amounts of data. The sensitivity of the gravitational-wave detectors to astrophysical signals is limited by the noise associated with the instruments themselves and their environment. Invaluable astrophysical information is buried in data sets that may be too large or complex to be analyzed with traditional data-processing techniques. This workshop will focus on the development of techniques for a more efficient handling of gravitational-wave data sets, reduction of detector noise, identification of astrophysical signals and increase in detection confidence. It will bring together astrophysicists, mathematicians and statisticians working on the state-of-the-art data analysis.

Detailed information can be found here.

This is the eleventh in the series of the annual Astroinformatics conferences. The conference is sponsored in  part by the Center for Data-Driven Discovery (CD3) and the Astronomy Department at Caltech, the Zwicky  Transient Facility (ZTF), and the Heidelberg Institute for Theoretical Studies (HITS).

Detailed information can be found here.

   IAA-IAU seminar. Prof Ilya Mandel will discuss some of the techniques used to address challenges faced when dealing with modern astronomical data sets. This shall be a virtual event.

Detailed information can be found here

Penn State's Center for Astrostatistics is continuing its annual Summer Schools in Statistics for Astronomers designed for graduate students and researchers in astronomy. This is being supplemented with a new additional week-long Summer School in Astroinformatics. Lectures and tutorials are presented by a team of experienced professors in statistics, astronomy, computer science, and informatics. Classroom instruction is interspersed with hands-on analysis of astronomical data with opportunity for discussion of methodological issues.

• Summer School in Statistics: June 1-5 2020.
• Summer School in Astroinformatics: June 8-12 2020.

Detailed information can be found here

Going into the 2020s, cosmic large scale structure will be mapped with increasing detail by the next generation of observational facilities operating at various wavelengths (radio, optical, infra-red) and exploiting various techniques. Meanwhile, theory and simulations are increasing in sophistication in their ability to describe large-scale structure. These advances could potentially allow greater constraints into cosmological parameters and theories of galaxy evolution.

Topics to be discussed include, but are not limited to:

• Characterizing and modeling the cosmic web
• Observational surveys of the cosmic web, ongoing and planned
• The growth of protoclusters into clusters
• Statistical measurements beyond 2-point
• Galaxy evolution in the context of the cosmic web
• Constrained realization modeling of large-scale structure
• The intergalactic medium tracing the cosmic web
• Exploiting cosmic voids for cosmology

Detailed information can be found here.

Th he decade 2020-2030 will be cosmology’s  new golden age with the launch of two spatial missions dedicated to cosmology, Euclid in 2022 and WFIRST in 2026, and the starting of the Large Synoptic Survey Telescope (LSST) observations in 2022. These international projects, ushering in the era of Big Data for cosmology, will require new statistical methods to tackle computational and theoretical challenges,

Program Outline

4-10 April : School: ADA X school on statistics for cosmology.

20-24 April: Workshop1: Lensing (methodologies in Lensing).

11-15 May: Workshop2: Galaxy Clustering (methodologies in clustering).

25-28 May: Workshop3: Theory and Interpretation of the data.

Detailed information can be found here.

Astrostatistics is developing fast as astronomy is confronted to huge volumes of data. This constitutes undoubtly a new era through a move from object- to data-driven astrophysics. The question that needs to be solved is the following: how can we reconnect statistical results obtained by automatic tools such as machine learning or hypothesis testing, with object-driven inferences derived from visual inspection, modelisation or numerical simulation? How do we reconcile a statistical, hence fuzzy, classification with the visual Hubble sequence of galaxies? How do we describe, synthetize, the data cubes (images + spectra) obtained by IFUs? How can we constrain a model of stellar evolution with the statistics of billions of stars? How do we characterize a scaling law in a 4-D or 10-D dimension parameter space? In this workshop, we want to focus particularly on the connection between the tools and the astrophysics, between data analysis and science.

Detailed information can be found here.

IEEE SSCI is a flagship annual international conference on computational intelligence sponsored by the IEEE Computational Intelligence Society, promoting all aspects of theory, algorithm design, applications and related emerging techniques. IEEE SSCI 2019 will co-locate exciting symposiums, each dedicated to a special topic within or related to computational intelligence, thereby providing a platform for promoting cross-fertilization and collaboration. IEEE SSCI 2019 will be featured by keynote speeches, panel discussions, oral presentations and poster sessions.

Detailed information can be found here.

PES university is proud to host a unique meeting in Bangalore this year, jointly organized by Department of Computer Science and Engineering & Center for AstroInformatics, Modeling and Simulation, PES University, IEEE Computer Society Bangalore Chapter and International Astrostatistics Association. The meeting is a first of its kind in INDIA and we look forward to your support to make it a success.

Detailed information can be found here.