Wladimir J. Alonso is a Research Fellow at the Fogarty International Center (US National Institutes of Health). He has pioneered the analyses of latitudinal gradients of seasonal parameters of diseases, as well as the analytical approach that enabled revealing that the annual influenza vaccine is administered at the wrong timing in several tropical regions. Wladimir also has a number of studies on historical epidemiology and on how epidemiological knowledge can be translated into better public health decisions. He teaches workshops on time-series analysis and data visualization, using Epipoi , a software of his authorship, which has been made freely available and is currently used by epidemiologists, public health researchers and students around the globe. He also works (pro-bono) on evolutionary theory, environmental science and animal welfare.

Alex Becker is a PhD student with Prof. Bryan Grenfell in the Department of Ecology and Evolutionary Biology at Princeton University. His current research is focused on dissecting the cross-scale dynamics of measles transmission, with the most recent work being on transmission within primary schools. Generally, he is interested in developing and expanding the methods used to analyse and fit infectious disease time series data.

Wilbert Van Panhuis, MD PhD, is an assistant professor of Epidemiology and Biomedical Informatics at the University of Pittsburgh and faculty of the Public Health Dynamics Laboratory at the University of Pittsburgh Graduate School of Public Health. Dr. Van Panhuis received his MD from the Vrije Universiteit Medical Center in Amsterdam and his PhD in Epidemiology from the Johns Hopkins Bloomberg School of Public Health. Dr. Van Panhuis leads a research program in population health informatics and computational epidemiology aiming to improve access and use of global health data for research and policy. Dr. Van Panhuis is a principal investigator of Project Tycho (www.tycho.pitt.edu), a repository for global health data that specializes in disease surveillance data. Project Tycho has over 3000 registered users from 90 countries. Dr. Van Panhuis and collaborators have used historical disease surveillance data to study the impact of childhood vaccination programs in the US and the epidemiological dynamics of dengue fever in an eight-country region in Southeast Asia. Currently, Dr. Van Panhuis and his team are funded by the US NIH Big Data to Knowledge program and others to improve FAIR (Findable, Accessible, Interoperable, and Reusable) compliance of global health data and of computational models of infectious diseases.

Cécile Viboud is a Senior Research Scientist in the Division of International Epidemiology and Population Studies of the Fogarty International Center, NIH, where she has worked over the past 13 years. She received an engineer degree in biomedical technologies from Lyon University (1998), a Master of Public Health (1999) and PhD in Biomathematics (2003) from the University of Paris. Her research focuses on modeling the transmission dynamics and epidemiology of influenza and other acute viral infections, at the interface of public health, epidemiology and evolution. Recently she has become interested in the transmission dynamics of Ebola and MERS-CoV, and the potential use of disease forecasts in government.

Lander Willem is a research scientist at the Centre for Health Economics Research and Modeling Infectious Diseases at the University of Antwerp, Belgium. He holds a master in Biological Engineering (2010) and a PhD (2015) on agent-based modeling in the field of infectious disease transmission. In the philosophy of engaging in interdisciplinary research, his PhD had a particular focus on model exploration, parameter estimation, social contact patterns and computational efficiency. Currently, he holds a post-doc position targeting influenza and measles transmission dynamics on the individual level and is involved in other projects to improve computational performance. Dr. Willem is principal investigator of an individual-based model, called STRIDE, which is designed to study the interaction between adaptive individual behavior and close-contact disease transmission.