Stephan Günnemann is a Professor at the Department of Informatics, Technical University of Munich. His main research focuses on reliable machine learning techniques, specifically targeting graphs and temporal data. His works on subspace clustering on graphs as well as his analysis of adversarial robustness of graph neural networks have received the best research paper awards at ECML-PKDD and KDD.

Stephan acquired his doctoral degree at RWTH Aachen University, Germany in the field of computer science. From 2012 to 2015 he was an associate of Carnegie Mellon University, USA. Stephan has been a visiting researcher at Simon Fraser University, Canada, and a research scientist at the Research & Technology Center of Siemens AG. In 2017 he became Junior-Fellow of the German Computer Science Society. He currently acts as scientific advisor for the Fraunhofer Society to build up a new institute for Cognitive Systems focusing on safe and reliable AI.

Stephan has been a (senior) PC member/area chair at conferences including NeurIPS, ICML, KDD, ECML-PKDD, AAAI, WWW.

Konstanty Korski graduated from Poznan School of Medical Sciences (2001) and was board certified in pathology (2008). Since his graduation, he served as a staff pathologist in the Pathology Department at Greater Poland Cancer Center in Poznan, Poland, where his main focus was breast, gynecologic and urinary pathology, cytopathology, immunohistochemistry and molecular pathology. At that time, in one of his roles he coordinated tumor sample collection process in the collaborative international Tumor Cancer Genome Project (TCGA).

Six years ago, he joined the Pathology and Tissue Analytics Department in the Early Biomarker Development Oncology (pRED) group at the Roche Innovation Center Munich. His area of research activity encompassed an application of digital pathology to tumor tissue analysis in the context of early phase clinical trials. He focused on characterization of tumor immune infiltrate with the use of multiplex immunohistochemistry and digital image analysis. Konstanty was instrumental in the development of IRIS digital pathology platform and its introduction to the early drug development strategy. In addition, he was part of the pRED team testing deep learning technology for the analysis of histopathological images and applying this approach to the computational pathology. In April 2020, he joined the Imaging Data Science team in Personalized Healthcare group of Roche Pharma Product Development as the pathology lead for Digital Pathology products. Konstanty co-authored 23 peer reviewed publications and two patent applications.

Privately, Konstanty likes spending his free time with his family, reading books, watching movies, biking and travelling.