Charlotte Debus

Dr. Charlotte Debus serves as a junior research group leader at the Scientific Computing Center (SCC) of Karlsruhe Institute of Technology (KIT), directing her independently funded research group since 2022. Her work pioneers sustainable artificial intelligence through robustness optimization, energy efficiency improvements, and carbon footprint reduction in large-scale AI systems.

Her academic foundation includes a physics degree and doctoral research focused on AI methods for medical imaging. Prior to leading her KIT group, she contributed to the Helmholtz AI program as an AI consultant, advising researchers across the Helmholtz Association on AI implementation strategies.

Dr. Debus's research integrates high-performance computing (HPC) principles into AI training workflows to eliminate computational bottlenecks. She demonstrates how synchronizing data loading, forward/backward computation, and network communication across CPU/GPU architectures minimizes idle time and energy waste. Her meteorology case study proves 2D AI architectures achieve weather forecasting accuracy comparable to 3D models while drastically reducing training time and resource consumption—revealing data processing speed and volume as critical efficiency factors beyond dimensional structure.

Funded by the German Federal Ministry of Education and Research, her group develops transparent benchmarking frameworks for AI energy consumption metrics. She actively advocates for industry-wide adoption of these standards to convert computational energy use into tangible CO2 emissions data, driving environmentally responsible AI development practices across research and industry sectors.