Consultant Profile


Marco Geraci

Region of consultancy:


Professor Geraci obtained a Laurea (MSc) magna cum laude in Economics from the University of Sassari (Italy) in 2000 and a PhD in Applied Statistics from the University of Florence (Italy) in 2005. He carried out academic research in several institutions, including the National Council of Research (Italy), the University of Manchester (UK), University College London (UK) and the University of South Carolina (USA), where he currently holds an appointment as Adjunct Faculty. Professor Geraci is involved in a wide range of collaborations in methodological and applied research. He has published peer-reviewed articles in statistics, cancer epidemiology, maternal and child health epidemiology, physical activity (accelerometry data), gastroenterology, nuclear medicine and higher education. He also authored four statistical R packages on CRAN. He received funding awards for both methodological and collaborative research projects including a major Center grant (NIH P20) for 11 million dollars as lead of the Statistical and Data Management Core, several methodological grants (e.g., NIH R03 and intramural funding) as principal investigator for thousands of dollars, several collaborative grants (NIH R01 and R03) totalling 10 million dollars as co-investigator and lead statistician. In 2010, Professor Geraci was awarded Chartered Statistician by the Royal Statistical Society. He was Statistical Editor for the Journal of Child Health Care (SAGE) and Associate Editor for the Journal of Applied Statistics (Taylor & Francis). He is currently Associate Editor for Statistical Methods and Applications (Springer) and Board Member of Significance (Wiley on behalf of the Royal Statistical Society – RSS and the American Statistical Association – ASA). He performed more than 200 reviews for 45 distinct journals (verified on Publons). He has been awarded Publons Top 1% Reviewers for multidisciplinary (2017) and cross-field (2019).


Statistical methods and applications for health sciences; quantile inference; random-effects models; multivariate statistics; missing data; circular statistics; statistical computing; R and C++ programming; spatial statistics; accelerometer data; physical activity; maternal and child health; epidemiology; pediatric oncology; Crohn's disease.