Dresden 2026 – scientific programme

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AKPIK: Arbeitskreis Physik, moderne Informationstechnologie und Künstliche Intelligenz

AKPIK 1: Tutorial: Machine Learning Use Cases in Materials Science (joint session AKPIK/TUT)

Sunday, March 8, 2026, 16:00–18:15, HSZ/0003

Artificial intelligence (AI) tools are increasingly shaping research in materials science and physics by enabling advanced data analysis, modeling, and predictive capabilities.

This tutorial presents three practical use cases that demonstrate how machine learning methods can support materials science research.

	16:00	AKPIK 1.1	Tutorial: Welcome Remarks Arbeitskreis Physik, moderne Informationstechnologie und Künstliche Intelligenz — DPG AKPIK and •Arash Rahimi-Iman
	16:05	AKPIK 1.2	Tutorial: A practical machine learning case study in materials science: Stumbling blocks, lucky breaks, and helpful colleagues — •Max Grossmann, •Malte Grunert, and Erich Runge
	16:45		5 min. break
	16:50	AKPIK 1.3	Tutorial: Machine Learning-based Analysis of Electron Microscopy Images: Preprocessing and Synthetic Data Generation — •Amir Omidvarnia
	17:30		5 min. break
	17:35	AKPIK 1.4	Tutorial: Machine Learning-based Analysis of Electron Microscopy Images: Segmentation — •Amir Omidvarnia