Clemens Wittenbecher specializes in utilizing molecular profiling data, with a particular focus on metabolomics, to uncover the relationship between dietary patterns and the risk of cardiometabolic diseases. His expertise lies in data-driven network analyses, risk prediction, machine learning, and causal modeling techniques, applied to both prospective cohorts and dietary intervention studies. Through his research, Clemens aims to reinforce the evidence supporting the causal impact of dietary composition on cardiometabolic disease development and to pioneer biomarkers for tailored nutrition strategies. He was affiliated with the German Institute of Human Nutrition and the Harvard T.H. Chan School of Public Health. In 2022, he took on roles as an Assistant Professor in precision medicine and diagnostics at Chalmers University of Technology’s Food and Nutrition Science Division and as a Wallenberg Data-Driven Life Science Fellow.