Michael Schomaker
About
Prof. Dr. Michael Schomaker is a full professor of Artificial Intelligence & Machine Learning at the Ludwig‑Maximilians‑Universität München (LMU), where he leads research and teaching at the intersection of machine learning, cognitive systems, and AI applications. He studied computer science and mathematics, earning his doctorate and completing postdoctoral research before holding professorships at institutions including the University of Groningen and then LMU. Prof. Schomaker’s work focuses on deep learning, reinforcement learning, cognitive modeling, and large‑scale learning systems, with interests spanning both theoretical foundations and practical uses of AI in areas such as robotics, perception, and automated reasoning. At LMU, he supervises graduate research, contributes to interdisciplinary AI initiatives, and teaches courses on machine learning and intelligent systems. He is an active member of the international AI research community, regularly publishing in leading conferences and journals in artificial intelligence and machine learning.
Research Performance Summary
First Recorded Paper
Linear models and generalizations
Year: 2008
Citations: 143
Venue: Least Squares and Alternatives (3rd edition) Springer, Berlin Heidelberg New
Latest Recorded Paper
A Diagnostic to Find and Help Combat Stochastic Positivity Issues - with a Focus on Continuous Treatments
Year: 2025
Citations: 0
Venue: Journal of Causal Inference
Last 10 Years Publication Activity
This timeline shows the professor's yearly publication activity.