Daniel May

I am a PhD student at TU Wien in the Research Unit of Computational Sustainability, working with Prof. Ivona Brandić within the Institute of Computer Engineering. I work on energy-efficient AI systems, with a current focus on neuromorphic computing and intermediate representations.

I am interested in how machine-learning workloads can be represented, transformed, and executed so they map efficiently to constrained or emerging hardware. This includes systems questions around what information intermediate representations preserve, how they can target neuromorphic or edge devices, and how to evaluate the resulting trade-offs in accuracy, latency, and energy.

My previous work focused on split computing and adaptive offloading for energy-efficient Edge-AI, including multi-objective optimization of accuracy, latency, and energy. More broadly, I am interested in energy profiling, DVFS, model compression, and sustainability-driven application domains such as environmental monitoring, water quality analysis, and resource-efficient IoT systems.

If you are working on neuromorphic computing, sustainable AI, edge AI, or energy-aware systems, feel free to reach out.

Outside research, I’m into space — rockets, telescopes, and the night sky. I am always interested in conversations around edge AI and efficient computing for space systems.