Curriculum Vitae

Etienne Müller is a research assistant and PhD candidate since 2018. He received his Master's degree in Product Development and his Bachelor's Degree in Mechanical Engineering at the Hamburg University of Technology in 2017 and 2014, respectively.

Etienne's current research topic is the development of spiking neural networks in the context of path planning and decision making.

Research Interests

Conversion of today's commonly used analog neural network to spiking neural network for the usage in neuromorphic computing.

Thesis Supervision

Finished:

• Master Thesis (2021): Performance of Time to First Spike Encoded Spiking Neural Networks
• Guided Research (2021): Conversion of TransformerNets
• Master Thesis (2021): Conversion of LSTM-based Recurrent Neural Networks
• Master Thesis (2021): Conversion of GRU-based Recurrent Neural Networks
• Research Internship (2020): Carla as Open Source Platform for Analyzing and Evaluating Autonomous Driving
• Master Thesis (2020): Converting Analogue to Spiking Convolutional Neural Networks for Object Detection
• Graduation Thesis (2019): Semantic Segmentation of Integrated Circuit Layout Images