Simon Geisler

Simon Geisler is a researcher at the Technical University of Munich (TUM), working within the Department of Informatics (I26) under Prof. Dr. Stephan Günnemann in the Data Analytics and Machine Learning group. He maintains an office in room 00.11.055 at Boltzmannstr. 3, Garching.

His research focuses on robust deep learning systems, with particular emphasis on uncertainty estimation in deep learning models and machine learning applications for graphs and sequential data. Geisler's work primarily addresses vulnerabilities in graph neural networks and develops methods to improve their reliability against adversarial attacks.

His publication record shows consistent contributions to top-tier machine learning conferences, with research spanning robustness evaluation, defense mechanisms, and scalability challenges in graph representation learning. His work demonstrates strong theoretical foundations coupled with practical applications.

• Gifted student scholarship, Konrad-Adenauer-Foundation (2014-2016)
• Fulbright Scholarship (2015)

Geisler brings valuable industry experience to his academic research, having worked as a Data Scientist at Robert Bosch GmbH from 2015-2020 focusing on Autonomous Driving and Connected Services, plus internships at Google DeepMind (2022) and Bosch Center for Artificial Intelligence (2019). He completed his M.Sc. in Data Science from Albstadt-Sigmaringen University in cooperation with the University of Mannheim (2016-2019).