Doctoral researcher Mario Gaimann in the junior research group of Miriam Klopotek on Many Body Systems, has successfully applied as a Scientific Computing Intern at the Simons Foundation Internship Program. The Simons Foundation’s mission is to advance the frontiers of research in mathematics and the basic sciences.
Gaimann will be situated at the Flatiron Institute in the vibrant city of New York from late May to early August. Within the Scientific Computing Core department, he will be immersed in a stimulating environment, working alongside his mentor Robert Blackwell, a distinguished software engineer at the Scientific Computing Core, renowned for his expertise in physics and computational science.
In his capacity as an intern, Mario Gaimann will contribute to the advancement of an accelerated code for simulation-based reservoir computing, which has been developed within the SimTech project PN6-15 in project network 6. This aligns closely with the Simons Foundation's mission of pushing the frontiers of basic sciences. Reservoir computing with physical systems, a cutting-edge field utilizing dynamical systems to solve computational challenges, holds promise for transforming the field of time-series predictions across various domains, including weather forecasting, energy management, and financial modeling.
The internship promises to be a dynamic learning experience, offering Gaimann the opportunity to tackle challenging tasks in a state-of-the-art scientific computing environment. He will sharpen his skills in software engineering and scientific computing while delving into acceleration techniques such as parallelization and GPU computing. Additionally, Gaimann will evaluate established particle simulation frameworks and implement them for reservoir computing applications. The culmination of his efforts will be the deployment of integrated, accelerated reservoir computing code utilizing Flatiron's high-performance computing cluster resources.
Mario Gaimann brings a wealth of interdisciplinary knowledge and curiosity to the internship, stemming from his background in physics and current research on intelligent systems. He will use this opportunity to extend his already very international and prestigious scientific network, including in the International Max Planck Research School for Intelligent Systems (IMPRS-IS), the Graduate Academy of the Stuttgart Center for Simulation Science (SimTech), and the International Association of Physics Students (IAPS). His research interests span from applying methods from many-body physics to machine learning, with a particular focus on reservoir computing. He is passionate about uncovering optimal conditions for learning in complex, physical systems using techniques from statistical physics. Future applications include spatio-temporal forecasting, but also next-generation computing.