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I am interested in machine learning. Machine learning is the problem of automatically building models which explain observed systems and predict their future behavior. My current research interests lie in adversarial learning problems, in transfer learning, and in data science. In adversarial learning, an adversary exercises some control over the data-generation process; this reflects many security applications of machine learning. Transfer learning algorithms learn to perform a task, but do so using training data that reflect a different task. Machine learning has many diverse applications, and I am working on some of them: computer security (detection of malware, analysis of encrypted network traffic), precision medicine, and model-building in the sciences. Here is an overview of my current research projects.
Our group offers courses on machine learning. If you are a student of the master program Data Science and have a question regarding this program, please visit this information page where you will find general information as well as contact information of the counsellor. If you have a question regarding a particular course, please visit the Moodle page of your course where you will find announcements as well as a contact.
I am a Professor of Computer Science at the University of Potsdam. From 2007 to 2008 I was the head of the Machine Learning Group at the Max Planck Institute of Computer Science in Saarbrücken. Between 2003 and 2006, I was Assistant Professor at Humboldt-Universität zu Berlin. I was awarded an Emmy Noether Fellowship of the German Science Foundation DFG in 2003 and an Ernst von Siemens Fellowship by Siemens AG in 1996. I received a Master's Degree in Computer Science (Diplominformatiker) in 1995 and a Ph.D. (Dr. rer nat.) in 1999 from Technische Universität Berlin.