Daniel Bernhard May

Dr. Daniel Bernhard May is a PreDoc Researcher in the Research Unit of Computational Sustainability at Technische Universität Wien (Institute of Computer Engineering). His work focuses on energy-efficient AI systems, particularly split computing and adaptive offloading in edge-cloud environments, model compression techniques, and federated learning applications. He earned his MSc in Business Informatics from TU Wien in 2025.

Research Interests: Daniel specializes in computational sustainability, optimizing AI workloads through energy profiling, dynamic voltage and frequency scaling (DVFS), quantization, pruning, and distillation. His research bridges hardware-software co-design with sustainable AI applications for resource-constrained environments, including potential use cases in space systems.

Scientific Contributions: Recent work includes

• Developing hardware-software frameworks for energy-aware edge inference (DynaSplit)
• Advancing neural network splitting methodologies
• Creating predictive models for medical applications

Awards:

• Netidee Scholarship recipient for master's thesis on neural network optimization

Academic Engagement:Active participant in international conferences (EuroSys 2025) and educational programs (KTH Summer School on Edge AI 2025).