Overview

Welcome! My name is Philipp Geiger, on this web page I give an overview over my work in research and software development, and general background.
I'm an industry research scientist at Bosch Center for Artificial Intelligence. Before, I did my doctorate in computer science and a postdoc at Max Planck Institute for Intelligent Systems and University of Stuttgart, including a stay at Microsoft Research Cambridge, and my diplom in mathematics with philosophy as side subject at Heidelberg University and Humboldt University of Berlin.
Generally, I conduct research and development in a broad range of topics in machine learning (core part of artificial intelligence) and multiagent systems (analysis and optimization of multiple intelligent decision makers' interaction behavior). Often, this combines project-driven software engineering and experimental aspects with statistical/mathematical analysis, and aims at innovative solutions for problems important to business and society as a whole. Recently, I've been focusing on deep generative multiagent imitation learning, deep model-based reinforcement learning and game theory, and I'm also exploring foundation models, in particular fine-tuning of vision language models. Applications I work on include energy-efficient building control and autonomous driving and its safety validation (see also further background).
I'm also increasingly interested in the political aspects of artificial intelligence.
Selected publications (see also all publications and further material):
- Fail-Safe Adversarial Generative Imitation Learning. (2022). TMLR.
- Learning game-theoretic models of multiagent trajectories using implicit layers. (2021). AAAI.
- Causal inference by identification of vector autoregressive processes with hidden components. (2015). ICML. [Slides.]
Further links: my profiles on Google Scholar, DBLP, OpenReview, GitHub.