Ralf Huss MD, PhD profile image
Ralf Huss, MD, PhD
Scientific Advisory Board Member
  • Sabbatical; Department of Pathology, Technical University of Munich

Dr. Ralf Huss MD, Ph.D. joined Definiens in 2015 as Chief Medical Officer with further responsibilities in Science & Innovation following founder and Nobel Laureate Gerd Binning's role.

Dr. Huss is a board-certified surgical and molecular pathologist and obtained his medical doctorate from the Universitat Erlangen (DE) in 1991. He is specialized in internal medicine (Universitatsspital Zurich (CH)) and immunology (Institut fur Pathologie under Nobel Laureate Rolf M. Zinkernagel), Universitat Zurich (CH). Also, Huss is an Associate Professor at Ludwigs-Maximilians-Universitat Munchen (DE), a lecturer at the Technische Universitat Munchen, and honorary professor at the School of Medicine, University College Dublin (IE).

Dr. Huss spent his early career during the 1990s as a Research Associate in Nobel laureate Edward D. Thomas' Laboratory at the Fred Hutchinson Cancer Research Center, in Seattle, Washington (US). Later, he returned to Europe to become an immunology researcher at the Institut fur Immunologie, Universitatsklinikum Essen (DE) and completed his pathology training at the Ludwig-Maximilians-University Munchen (Institut fur Pathologie) between 1995 and 2005.

In 2005, he joined Roche Diagnostics as Global Head of Pathology and Tissue Biomarkers and later headed the Cell Therapy Initiative at Roche Penzberg (DE). In 2011, he joined apceth GmbH, a stem-cell and gene-therapy company which he co-founded in Munchen, as Chief Scientific Officer, where he worked until starting at Definiens in 2015.

Dr. Huss received numerous awards, among them from the "International Jose-Carreras-Foundation", the "American Society of Hematology" and the "European Leukemia Society" for his work on stem cell plasticity and the development of experimental leukemia. He recently turned his scientific and clinical focus towards Computational Pathology and co-authored scientific articles and textbooks on artificial intelligence and machine learning to support diagnostic decision making."