AI-Driven Polymer Research from the Schubert Group Presented at AI4X Conference 2026
At AI4X Conference 2026 in Singapore, the Schubert Group presented recent advances in AI-driven polymer research, highlighting how automation, high-throughput experimentation, and machine learning are accelerating the discovery of new materials.
Prof. Dr. Ulrich S. Schubert at AI4X Conference
Image: Jingyu Feng
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The Schubert Group contributed to the AI4X Conference 2026 in Singapore, one of the leading international events dedicated to artificial intelligence, machine learning, automation, and autonomous research.
During the conference, Prof. Dr. Ulrich S. Schubert presented recent advances in data-driven polymer research, highlighting the integration of high-throughput experimentation, automated workflows, and machine learning methods into modern materials development. These approaches enable the generation and analysis of large polymer datasets and support the accelerated discovery of new functional materials.
A central topic of the presentation was the increasing role of automation and digitalization in polymer science. By combining experimental platforms with advanced data analysis, researchers can explore complex materials systems more efficiently and gain deeper insights into structure–property relationships.
The presented work reflects ongoing activities within the Schubert Group and its collaborative research environment, including HIPOLE Jena and the JointLab for Polymers Jena–Bayreuth. The conference also provided an opportunity to exchange ideas with researchers from around the world who are developing new approaches for AI-supported scientific discovery.
The strong international interest in these topics underscores the growing importance of data-centric research strategies for the future of polymer science and materials development.