Aalto Materials Digitalization Platform (AMAD) webinar, Oct 29, 2024

Description

Welcome to Aalto Materials Digitalisation Platform (AMAD) webinar.

The Aalto Materials Digitalisation Platform (AMAD) is a robust and versatile data infrastructure for experimental and computational materials data. It facilitates data collection, documentation, management, analysis, sharing and reusing in line with the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. It also enables the use of digital research tools, machine learning, and automation. AMAD not only provides access to machine-readable data, but is also equipped with machine-learning and AI tools that assist in data analysis, expose hidden correlations in data and aid in the discovery of new relations and novel materials.

In the webinar you will be introduced to AMAD, its benefits and features. You will be shown a demo and you'll learn how to use the interface. In addition, the webinar will be a good place to ask questions, give feedback and get to know AMAD administrators. If AMAD has piqued your interest, sign up for the event to find out how AMAD can benefit your research data management workflow and processes.

For more information about AMAD, please check the service page.

Who can participate?

AMAD is open to Aalto researchers, and affiliates from other universities (upon request).

The webinar is aimed at anyone who is interested in AMAD and/or is working with or planning to work with or provide quantitative and experimental research data, in particular materials science data. The webinar is free and open to all.

Learning outcomes

• Learn how the AMAD data infrastructure can streamline and automate data management, digitalisation, and collaboration in research workflows and processes.
• Get to know the AMAD user interface and features and how to use them in practice.
• See how proper data management, combined with data science and machine learning techniques empower interdisciplinary collaborations.

Format

A 1.5-hour webinar with a presentation and a Q&A.

Schedule and location

The training will be held online via Zoom on October 29, at 1–2.30 PM Eastern European Time (EET).

Instructor(s)

Prof. Patrick Rinke is Head of the Chair of AI-based Materials Science at the Technical University of Munich and Adjunct Professor at the Computational Electronic Structure Theory (CEST) group at the Department of Applied Physics at Aalto University. The CEST group develops advanced quantum mechanical, data science and machine learning methods and applies them to pertinent problems in material science, surface science, physics, chemistry, and the nano sciences.
Dr. Filippo Federici is the developer of AMAD and the co-founder and scientific director for Nanolayers Research Computing, where he leads the business' development for image recognition and machine learning methods. Filippo holds a doctorate in Computational Physics from Tampere University of Technology and has extensive knowledge of advanced experimental and computational systems.
 

Aalto RDM & Open Science Training | YouTube | Privacy Notice