2025 Winter School for AstroStatistics

Winter School for AstroStatistics

Sharjah Academy for Astronomy, Space Sciences, and Technology (SAASST)

Introduction

Welcome to the 2025 Winter School for AstroStatistics in Sharjah, United Arab Emirates. This five-day intensive program brings together astronomers, statisticians, and data scientists to bridge the gap between astronomy and statistical methods.

In modern astronomy, the ability to analyze and interpret complex datasets is as important as gathering observational data. This school aims to equip researchers with the statistical tools and methodologies needed to extract meaningful insights from astronomical data.

Whether you’re a seasoned researcher looking to update your statistical knowledge or a student beginning your journey into astronomical data analysis, this school offers valuable learning opportunities in a collaborative environment.

 

Essential Information

Dates

10–14 November 2025  

Location

Sharjah Academy for Astronomy, Space Sciences, and Technology (SAASST)  

Target Audience

Graduate students, early-career researchers, and professionals in astronomy, physics, statistics, and related fields.  

Format

Lectures, hands-on sessions, group projects, and networking opportunities.


Register Now

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Topics

The Winter School covers a wide range of topics at the intersection of astronomy and statistics, providing both theoretical foundations and practical applications. The curriculum is designed to build skills progressively throughout the week.

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Classical & Bayesian Statistics

Fundamental statistical concepts, hypothesis testing, and Bayesian inference applied to astronomical data.

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Optimization Methods

Techniques for finding optimal solutions to complex astronomical data problems.

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Markov Chain Monte Carlo

MCMC methods for sampling probability distributions in astronomical parameter estimation.

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Simulation-Based Inference

Using simulations to make inferences about astronomical processes and phenomena.

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Machine Learning Practices

Implementation of machine learning algorithms for astronomical data analysis.

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Clustering

Techniques for identifying natural groupings in astronomical datasets.

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Classification & Regression

Methods for categorizing astronomical objects and predicting continuous variables.

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Deep Learning

Neural networks and deep learning approaches for complex astronomical data analysis tasks.


Hands-on Sessions

Each topic will be accompanied by practical exercises using Python and relevant astronomical datasets. Participants will work with tools such as Astropy, scikit-learn, PyTorch, and specialized statistical packages to implement the concepts covered in lectures.

 

School Schedule

Detailed Schedule Coming Soon

The complete program schedule with session times, breaks, and special events will be published here. Please check back for updates.

Organizing Committee

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H. E. Prof. Hamid Al-Naimiy

Director General of SAASST
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Dr. Antonios Manousakis

Director of Space Sciences Department
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Noora Alameri

Head of the High Energy Astrophysics Lab
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Maryam Alqasimi

Research Analyst | High Energy Astrophysics Lab
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Abdulla Esmail

Research Analyst | High Energy Astrophysics Lab

Teaching Body

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Dr. Kostantinos Kovlakas

Institute of Space Sciences (CSIC, IEEC)
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Dr. Kostantinos Kovlakas

Institute of Space Sciences (CSIC, IEEC)

Researcher in binary stellar evolution He uses statistics and machine-learning tools to study observed and simulated populations of ultraluminous X-ray sources.

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Dr. Paolo Bonfini

Alma Sistemi Leading Research Engineer
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Dr. Paolo Bonfini

Alma Sistemi Leading Research Engineer

Expert in the application of machine learning techniques in astronomy, bioinformatics, and software optimization. Current ML lecturer at the Dept. of Physics of the University of Crete.

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Dr. Grigoris Maravelias

National Observatory of Athens & FORTH Researcher in the field of massive star sand X-ray binary populations.
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Dr. Grigoris Maravelias

National Observatory of Athens & FORTH Researcher in the field of massive star sand X-ray binary populations.

Observational astronomer, who uses machine-learning techniques to solve astrophysical problems.

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Andreas Tersenov

FORTH & CEA Paris-Saclay
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Andreas Tersenov

FORTH & CEA Paris-Saclay

PhD candidate in weak lensing cosmology. Specializes in convergence mapping, cosmological inference with higher-order statistics, likelihood-based/free methods, and deep neural networks for cosmology problems.

Teaching Assistants

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Maryam Alqasimi

Research Analyst | High Energy Astrophysics Lab - SAASST
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Noora Alameri

Head of the High Energy Astrophysics Lab - SAASST
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Aisha Alowais

Head of the Space Artificial Intelligence Lab - SAASST
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Munya Alkhalifa

Research Engineer | Space Artificial Intelligence Lab - SAASST
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Abdollah Masoud

Research Engineer | Space Weather and Ionosphere Lab - SAASST

Venue & Accommodation

Venue & Access

Venue

The 2025 Winter School for AstroStatistics will be hosted at the Sharjah Academy for Astronomy, Space Sciences, and Technology (SAASST), a state-of-the-art facility dedicated to astronomy education and research.

Facilities

SAASST features modern lecture halls, computer labs, an astronomical observatory, planetarium, and exhibition areas. All sessions will take place within the main building.

Opening Hours

The venue will be open to participants from 8:00 AM to 6:00 PM daily during the school.

Map Location

Directions & Distances

  • From Sharjah University: 2 km (5 minutes by car)
  • From Sharjah International Airport: 12 km (15 minutes by car)
  • From Dubai International Airport: 25 km (30 minutes by car)

Transport & Accessibility

  • Taxi: Readily available at airports and throughout the city
  • Private Car: Ride-sharing apps operate in Sharjah
  • Public Buses: Routes connect major landmarks to the venue

Accommodation Options

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Golden Tulip Sharjah

Modern hotel with comfortable rooms, restaurant, and fitness center.
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Golden Tulip Sharjah

Modern hotel with comfortable rooms, restaurant, and fitness center.

3.5 km from SAASST

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Sharjah Grand Hotel

Luxury accommodation with multiple dining options and spa facilities.
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Sheraton Sharjah Beach Resort

Beachfront resort with premium amenities and scenic views.
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Sheraton Sharjah Beach Resort

Beachfront resort with premium amenities and scenic views.

8 km from SAASST

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Discover Sharjah and UAE

From museums and mountains to souks and shorelines, Sharjah is a fascinating place to visit. Sharjah is a capital of heritage and culture, and a land blessed with stunning beaches, desert landscapes, and mountainous terrain. The third largest of the seven emirates, Sharjah is a unique destination for cultural, historical, natural and simply beautiful experiences. Whether you want to explore or relax, be entertained or informed, shop or dine – Sharjah offers countless ways to spend your days and nights. And, whether travelling for business or pleasure, Sharjah has world-class, state-of-the-art facilities and services to meet your needs. Crowned the Cultural Capital of the Arab World in 1998, the Capital of Islamic Culture in 2014, and the Arab Tourism Capital for 2015, Sharjah attracts tourists from all corners of the world.

Visit Sharjah

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Sharjah Academy for Astronomy Space Sciences and Technology (SAASST) and the University of Sharjah

The University of Sharjah, a beacon of academic excellence, offers a diverse range of programs and cutting-edge research opportunities. Partnered with the Sharjah Academy for Astronomy, Space Sciences, and Technology (SAASST), the university provides students with unique access to advanced research facilities and observatories. SAASST offers a unique blend of academic excellence and hands-on research opportunities in the fields of astronomy and space sciences for the students of the University of Sharjah. Experience the vibrant intellectual environment of the University of Sharjah and SAASST, where innovation and discovery are at the forefront. Join us for an inspiring winter school that will expand your knowledge and ignite your passion for space sciences.

Partners

AstroStat Academy