Networks in Food Systems and Nutrition

John Ioannidis

Professor of Medicine, School of Medicine, Stanford University

C.F. Rehnborg Chair in Disease Prevention at Stanford University, Professor of Medicine, Professor of Health Research and Policy, and Professor (by courtesy) of Biomedical Data Science at the School of Medicine; Professor (by courtesy) of Statistics at the School of Humanities and Sciences; co-Director, Meta-Research Innovation Center at Stanford; Director of the PhD program in Epidemiology and Clinical Research. Professor Ioannidis is a physician-scientist and writer with contributions in evidence-based medicine, epidemiology and public health, data science and clinical research. He has pioneered the field of meta-research (research on research). He says that much of the published research doesn't meet good scientific standards of evidence. His PLoS Medicine paper on “Why most published research findings are false” has been the most-accessed article in the history of Public Library of Science (>2.5 million hits). He has recently directed his focus on nutrition research, recently publishing “The Challenge of Reforming Nutritional Epidemiologic Research” as a Viewpoint in JAMA. He was a Visiting Senior Fellow in Science, Technology & Society at Harvard Kennedy School and was named a Young Global Leader by the World Economic Forum. He is currently building a new purpose-driven data and AI startup.

Elena Naumova

Professor and Chair, Division of the Nutrition Data Science, Friedman School of Nutrition Science and Policy, Tufts University

Dr. Naumova is the Chair of the Division of Nutrition Data Science at the Friedman School of Nutrition Science and Policy. Her research activities span a broad range of programs in emerging and re-emerging diseases, environmental epidemiology, molecular biology, nutrition, and growth. Her primary expertise is in development of analytical tools for spatiotemporal and longitudinal data analysis applied to disease surveillance. Her current interest is in understanding factors governing seasonal patterns and establishing methodology for assessing disease seasonality.

Bruce Y. Lee

Associate Professor of International Health at the Johns Hopkins Bloomberg School of Public Health, Executive Director, Global Obesity Prevention Center (GOPC), Associate Professor, Johns Hopkins Carey Business School

Bruce Y. Lee, MD, MBA is Associate Professor of International Health at the Johns Hopkins Bloomberg School of Public Health, Executive Director of the Global Obesity Prevention Center (GOPC), as well as Associate Professor at the Johns Hopkins Carey Business School. Dr. Lee has two decades of experience in industry and academia in systems science, digital health, and developing mathematical and computational methods, models, and tools to assist decision making in health. Dr. Lee is a regular contributor to Forbes and the HuffPost and has also written for a range of other general media. His Twitter handle is @bruce_y_lee.

Kayla de la Haye

Director, USC Center for Applied Network Analysis, Keck School of Medicine, University of Southern California

Kayla de la Haye is an Assistant Professor of Preventive Medicine at the University of Southern California, where she directs the USC Center for Applied Network Analysis. She works to promote healthy eating and prevent disease in families and communities by applying social network analysis and systems science. Dr. de la Haye is a member of the Board of Directors of the International Network of Social Network Analysis, and she holds a Ph.D. in psychology from the University of Adelaide, Australia.

Yelena Mejova

Research Leader, Digital Epidemiology Group, ISI Foundation

Yelena Mejova is a Research Leader at the ISI Foundation, Turin, Italy, member of the Digital Epidemiology group. Previously, she was a Scientist in the Social Computing Group at the Qatar Computing Research Institute (QCRI). Specializing in social media analysis and mining, her work concerns the quantification of health and wellbeing signals in social media, as well as tracking of social phenomena, including politics and news consumption. She co-edited a volume on the use of Twitter for social science in Twitter: A Digital Socioscope, and spoken widely about the use of social media for epidemiology, demography and social science.

John de la Parra

Associate at Harvard University, Harvard University Herbaria; Ethnobotany Research Associate, Open Agriculture Initiative, MIT Media Lab

Dr. John de la Parra is an ethnobotanist and plant chemist with specialties in medicinal plants and food crops. He is the Research Lead at the MIT Media Lab’s Open Agriculture Initiative where his work focuses on how phenotypic variation and human selection influence plant-based drug discovery and food choice. He holds additional appointments as an Associate researcher at Harvard University where he heads up the Harvard Herbariome Project, as a Lecturer of Environmental Studies at Tufts University, and a Lecturer of Biotechnology at Northeastern University.

Burçin Bozkaya

Visiting Professor, Human Dynamics Lab, MIT Media Lab; Director, Behavioral Analytics & Visualization Lab, Professor of Business Analytics, Sabanci University (Turkey)

Dr. Burçin Bozkaya earned his B.S. and M.S. degrees in Industrial Engineering at Bilkent University, Turkey and his Ph.D. in Management Science at the University of Alberta, Canada. He is currently working as a Professor of Business Analytics at Sabanci University School of Management and also the Director of Behavioral Analytics and Visualization Lab in Istanbul, Turkey. Dr. Bozkaya is an active researcher in the field of behavioral (big data) analytics and has publications in numerous international journals in the fields of spatio-temporal analysis, vehicle route planning and optimization, location-based services and (spatial) decision support systems.

Mark Pachucki

Assistant Professor, Department of Sociology, Computational Social Science Institute, University of Massachusetts

Mark C. Pachucki is a social scientist who investigates social determinants of health, culture, and social network dynamics. His work explores relational mechanisms by which the social world influences health through the lifecourse, especially health behaviors during adolescence and older adulthood, key sensitive periods for changes in well-being. He is Assistant Professor of Sociology at UMass Amherst, and core faculty in its Computational Social Science Institute.

Noelle Noyes

MA, DVM, PhD, Veterinary Population Medicine Department, University of Minnesota

Noelle Noyes is Assistant Professor in the Veterinary Population Medicine Department at the University of Minnesota, St. Paul. Dr. Noyes’ current research focuses on improving the understanding of antibiotic resistance in livestock production, with the ultimate goal of optimizing animal and public health, and food safety and security. Noelle was a USDA NIFA Post-Doctoral Fellow and an NIH T32 Pre-Doctoral Fellow. She was recipient of the German Chancellor Fellowship from the Alexander von Humboldt Foundation, and received her MA from Osnabrueck University and her BA from Amherst College. Noelle completed a dual-degree PhD-DVM program at Colorado State University before joining University of Minnesota faculty. Currently, her lab is conducting studies on microbiome, pathogen and antibiotic resistance issues related to livestock production and food safety, with funding from USDA, NIH, National Pork Board, National Cattlemen’s Beef Association, Foundation for Meat and Poultry Research and Education, and the University of Minnesota.

Abigail Horn

Keck School of Medicine, University of Southern California

Abigail Horn is a Postdoctoral Fellow in the Center for Applied Network Analysis at the at the University of Southern California Keck School of Medicine. Her work focuses on modeling network structure and transmission dynamics and integrating emerging information sources to solve problems relating to preventing infectious and chronic diseases. Abigail recently led a research project at the German federal-level food protection agency to develop, implement, and evaluate algorithms and decision support systems for modeling food supply networks to identify the source of large-scale outbreaks of foodborne disease. Her current work involves integrating digital trace data to quantify the impact of mobility on food consumer behavior, nutrition, and health.

Giulia Menichetti

Network Science Institute, Northeastern University

Giulia Menichetti is an Associate Research Scientist at the Network Science Institute (Barabasi Lab, Northeastern University). She is a physicist, with a background in network modeling of biological information. She currently leads the Foodome project that aims to track the full chemical complexity of the food we consume and develop quantitative tools to unveil, at the mechanistic level, the impact of these chemicals on our health.