Mark Deutel is a computer scientist pursuing his PhD at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) at the chair of Hardware-Software-Co-Design. He is also affiliated with the Fraunhofer Institute for Integrated Circuits IIS in Nuremberg, where he is a scientific researcher in the Efficient AI group. His work focuses on the efficient design of deep neural networks (DNNs) for use on embedded edge devices, mainly Cortex-M microcontroller units (MCUs). Since MCUs are generally resource-constrained, his main research interest is to optimize the trade-off between a DNN’s resource requirements and its accuracy. This includes hardware-aware neural architecture search (NAS), DNN pruning, quantization, and efficient programming techniques. Recently, he has also added on-device training of fully quantized DNNs on MCUs to his list of interests.