Dresden 2026 – wissenschaftliches Programm

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SYAI: Symposium AI and Data Challenges behind Emerging Self-Driving Laboratories

SYAI 1: AI and Data Challenges behind Emerging Self-Driving Laboratories

Donnerstag, 12. März 2026, 09:30–12:15, HSZ/AUDI

So-called Self-driving Laboratories (SDLs) or Materials Acceleration Platforms (MAPs) represent a cutting-edge convergence of artificial intelligence (AI) and machine learning (ML) with lab automation and robotics. SDLs are designed to automate and accelerate experimental processes, addressing inefficiencies and enhancing the precision and safety of lab operations. SDLs operate in active learning loops, in which an ML algorithm selects and plans experiments that are subsequently executed by increasingly automated (robotic) modules. Data from these experiments are fed back into the ML model, refining it and guiding subsequent experiments. This iterative process enhances the efficiency and effectiveness of experimental exploration, and it is the adaptive quality to directly exploit the information gained through the experiments in the past loops that distinguishes modern SDLs from classic approaches in high-throughput experimentation or combinatorial chemistry.

With SDLs emerging in a wide range of application fields from heterogeneous catalysis over optoelectronics to batteries, advances in experiment automation and robotization are obvious drivers for improved throughputs. Complementary to this are, however, multiple IT- and AI/ML- related aspects of SDLs, not least comprising data pipelines and management, workflows, AI- agent platforms, featurization of the experimental data or experiment planning (especially using noisy and multi-fidelity data). This symposium will survey the present state-of-the-art of these aspects and discuss current frontiers.

	09:30	SYAI 1.1	Hauptvortrag: Data and Experimental Foundations for Reliable Self-Driving Laboratories — •Dr. Marcus Tze-Kiat Ng
	10:00	SYAI 1.2	Hauptvortrag: Digital Catalysis - AI for Experiment Planning and Control — •Christoph Scheurer
	10:30	SYAI 1.3	Hauptvortrag: Autonomous, Data-Driven Workflows for Materials Acceleration Platforms with pyiron — •Jan Janssen and Joerg Neugebauer
	11:00		15 min. break
	11:15	SYAI 1.4	Hauptvortrag: Machine Learning for Autonomous Optimization and Discovery of Materials — •Pascal Friederich
	11:45	SYAI 1.5	Hauptvortrag: Transforming Our View on Transformers in the Sciences — •Kevin Maik Jablonka