Dr. Nico Mothes (né Hoffmann) is a seasoned AI researcher and industry expert specializing in Digital Twins, Surrogate Modeling, and AI-driven process optimization. With a background in medical image and signal analysis, he has extended his expertise into industrial AI solutions, working with leading companies in semiconductors, manufacturing, and energy sectors.

As Lead Machine Learning Engineer at Helm & Walter IT-Solutions / SAXONY.ai, he leads projects at the intersection of machine learning, numerical simulation, and real-time analytics, enabling companies to enhance production efficiency, predictive maintenance, and process automation. His work spans from AI-based error detection to sensor calibration in gas analytics and object detection & pose estimation for industrial automation.
Previously, he led a Helmholtz AI research group at Helmholtz-Zentrum Dresden-Rossendorf, where he developed Physics-Informed Neural Networks and scalable AI solutions for high-performance computing environments. His open-source contributions, such as Neural Solvers, have been featured at major conferences, including PyTorch Conference 2022.

Dr. Mothes has published in top-tier AI journals and conferences, including NeurIPS, ICML and MICCAI, and has been recognized for his contributions to AI-driven scientific computing and industrial applications. He actively engages in the German AI ecosystem, organizing hackathons and industry collaborations, and has received the Digitalpreis Sachsen for his efforts in AI education for kids.

With his strong foundation in deep learning, inverse problems, and AI-driven decision support, he is passionate about bridging the gap between cutting-edge AI research and real-world industrial applications.