Concept-based prototypes summarize the model behavior in condensed fashion, enabling an understanding of model (sub-)strategies. As such, PCX allows to quickly understand spurious model behavior or data quality issues. Importantly, PCX further enables to validate individual model predictions quantitatively and qualitatively, taking important steps towards more objective and applicable XAI.
Advanced studies of computational science with focus in statistical data analysis and artificial intelligence.
Bachelor of Science: Physics
2015 - 2019
Humboldt-University, Berlin
Basic studies of physics.
2018
Uppsala-University, Uppsala
Studies in Uppsala for one semester as a part of the Erasmus exchange programme.
Working Experience
Research Associate / PhD Student
since July 2022
Fraunhofer HHI, Berlin
Research Associate in the Machine Learning Group for Explainable AI (XAI). Advancement and application of concept-based XAI methods, thereby also touching AI robustness.
Research Assistant
November 2020 - July 2022
Fraunhofer HHI, Berlin
Research Assistant in the Machine Learning Group for Explainable AI (XAI). Application and adaption of XAI methods to segmentation and object detection models. Application of XAI to make Deep Neural Networks more efficient by quantization. Development of concept-based explainability methods.
Working Student
June 2019 - November 2020
IAV, Berlin
Tool development, modeling of car motion/behaviour, simulations to analyze safety borders for driving functions. Visualization and interpretation of high-dimensional experimental results.
Working Student, Bachelor Thesis
November 2018 - June 2019
Baumer Hübner, Berlin
General research in magnetic pole rings and magnetization processes. Planing and doing measurements and analyzing the data. Analyzing the magnetic behavior of magnetic pole rings with small diameter. Comparing an analytical model, FEM simulation and experimental measurements.
Working Student
July 2016 - September 2018
DESY, Zeuthen
Supervising school classes visiting the vacuum lab of DESY in Zeuthen. Part of organization team for TeVPA 2018 conference.
contact
Welcome to my homepage!
I live in Berlin and work at Fraunhofer HHI to increase AI transparency. Analyzing and using data to create helpful and interesting results is what made me fall in love with data analytics and programming. Next to my work and studies in these areas, I like to dive deeper into web development.
Please feel free to contact me via maximilian.dreyer[@]hhi.fraunhofer.de or on LinkedIn.