Marco Werner

Dr. Marco Werner is a Researcher in the Soft Matter Theory and Polymer Physics department at the Leibniz Institute of Polymer Research Dresden, part of the Theory of Polymers division. His work bridges computational methods with polymer physics to advance soft materials understanding.

His research focuses on:

• Machine learning of structure-property relationships in polymers
• Patterns in chemical sequences controlling copolymer-membrane interactions
• Neural network approaches to reveal hidden physical variables
• Inverse problems in soft materials design
• Static and dynamic conformation patterns in polymers
• Data-driven coarse-graining of simulation models

Dr. Werner's publications demonstrate expertise at the intersection of AI and polymer physics, with recent work in ACS Macro Letters and npj Computational Materials showing how machine learning can accelerate materials discovery and solve complex physics problems in soft matter systems. His research trends indicate increasing integration of deep learning techniques with traditional polymer physics approaches.

His contributions include developing "trans-encoder" neural networks for chemical space analysis and advancing transfer learning methods between different levels of coarse-graining in polymer simulations.