Bernt Schiele joins as CLS Senior Fellow

09 August 2020

We welcome Prof. Dr. Bernt Schiele, Director of the Computer Vision and Machine Learning Department at the Max Planck Institute for Informatics in Saarbrücken, who joins our Center as a CLS Senior Fellow. His research currently focuses on two main areas: computer vision and multimodal sensor processing.

To help shape the next phase of the Max Planck ETH Center for Learning Systems, the Center has decided to reach out beyond the network of experts within the two partners, the ETH Zurich and MPI for Intelligent Systems, and seek the involvement of a further select group of outstanding European researchers in machine learning and AI. These CLS Senior Fellows will be invited to participate in meetings of the Center, provide scientific advice and help set the strategic direction, as well as offering PhD supervision.

Prof. Dr. Bernt Schiele has accepted the invitation to become one of the Center’s first two CLS Senior Fellows. Prof. Schiele studied computer science at the University of Karlsruhe, Germany and obtained his PhD in 1997 from INP Grenoble, France under the supervision of Prof. James L. Crowley. The title of his thesis was "Object Recognition using Multidimensional Receptive Field Histograms". Positions at Massachusetts Institute of Technology, ETH Zurich and TU Darmstadt followed. Bernt Schiele has been Max Planck Director at the MPI for Informatics and Professor at Saarland University since 2010.

Professor Schiele writes: “My group currently focuses on two main areas of the broader field, namely computer vision and multimodal sensor processing. In the area of computer vision we address some of the most basic functionalities of image and video understanding such as 3D object class recognition or 3D people detection and tracking. We also look at the problem of 3D scene understanding of traffic scenes as a case study for complete scene understanding. In the area of multimodal computing we currently focus on the problem of human activity recognition as a means to study how ubiquitous or wearable computing may benefit from better sensor understanding. As a final cross-cutting theme for both areas we also work in the area of machine learning. It is clear that only advanced machine learning techniques will allow inference of higher-level information from noisy sensor data and enable the large-scale nature of current and future multimodal databases and sensor-streams to be dealt with“.

CLS Co-Director Bernhard Schölkopf writes, “Bernt Schiele has an outstanding profile in computer vision, and his work has been instrumental in establishing modern machine learning methods in a number of computer vision application problems.” Welcome, Professor Schiele!

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