Rate My Professor Moritz Kraemer

Professor Moritz Kraemer is a Professor of Epidemiology & Data Science at the Department of Biology and Pandemic Sciences Institute, University of Oxford. He co-directs the Oxford Martin School's Programme in Pandemic Genomics and Digital Pandemic Preparedness, and co-founded Global.health, a global consortium that advances infectious disease responses through open-source software and data sharing. Kraemer's research specializes in global infectious disease epidemiology, focusing on how climatic, behavioural, and evolutionary factors interact to shape disease dynamics. His work examines human mobility patterns to predict disease spread risks and inform digital surveillance strategies. He develops computational tools integrating genomic, digital, and spatial data to enhance equitable disease surveillance and public health decision-making. Kraemer's contributions have advanced academic understanding and directly informed national and international public health policies, particularly during the COVID-19 pandemic.

Kraemer completed his DPhil in Epidemiology and Biostatistics at the University of Oxford in 2017, followed by a National Institutes of Health research fellowship at Harvard Medical School and Boston Children’s Hospital in biomedical informatics from 2017 to 2018. His career at Oxford includes post-doctoral research in evolutionary biology and infectious diseases (2016-2017), associate membership in the Department of Zoology (2017-2022), Associate Professor of Computational and Genomic Epidemiology in Zoology (2022-2024), and promotion to full Professor in Biology in 2024. He has received multiple Google AI Impact Awards for advancing AI and machine learning in health research, the Branco Weiss Fellowship, and scholarships from the German National Merit Foundation and DAAD. Key publications include 'Artificial intelligence for modelling infectious disease epidemics' (Nature, 2025), 'The effect of human mobility and control measures on the COVID-19 epidemic in China' (Science, 2020), 'Spatiotemporal invasion dynamics of SARS-CoV-2 lineage B.1.1.7 emergence' (Science, 2021), 'Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus' (Nature Microbiology, 2019), and 'Toward optimal disease surveillance with graph-based active learning' (PNAS, 2024). Kraemer leads an interdisciplinary team developing scalable software for epidemic analysis and supervises DPhil students.