Important Dates

Mar 31
(Extended Deadline) for abstract submissions
April 15
Communication of accepted abstracts
Apr 10
Early registration for conference ends
May 27
Networks in Food Systems and Nutrition Satellite


Major advances in data science, nutrition, and health behavior have enabled novel networked frameworks across multiple levels that can inform personalized health recommendations, community interventions, and population level policies. Sensors and other digital tracking technologies are now able to record individual eating patterns with great detail, as well as to link eating to important locational, temporal, and social factors. At the same time, efforts in large scale computing and artificial intelligence have led to food ingredient databases that provide rich detail on food contents at the chemical level, and to food trade databases that help to map food production and supply infrastructure. New approaches that integrate these advances across scales, based in network science and big data, are beginning to uncover new insights about the relationship between specific food chemicals with consumption behaviors, linking this to health and disease outcomes. This satellite symposium aims to bring together a diverse group of researchers in this exciting new research space for the first time at NetSci 2019, including experts from food science, biochemistry, bioinformatics, nutritional epidemiology, and population health science; established investigators in network science applied to food systems, nutrition, and medicine; and budding researchers. Talks and discussion will explore topics and challenges within major themes:

Network Medicine

Mapping food compounds and linking them to health; epidemiological studies

  • Data-driven or mechanistic approaches to link compounds (nutrients, chemical compounds, toxins) in food with disease and health
    • Nutritional epidemiology (population-level nutrition research)
    • Precision nutrition (individual-level nutrition research)
  • Mapping networks of food compounds and linking with disease and health

Food Science, Technology, & Health Implications

Plant biology, chemistry, pharmacology, and computation

  • Basic research on what compounds (nutrients, chemicals, toxins) are in food coming from different disciplines such as biochemistry, bioinformatics, cheminformatics, pharmacology
  • Technology-enabled agriculture systems and nutrition / health implications

Population health networks and tracking technologies

Physiological & psychological factors that drive food choices and technologies that link consumption to health

  • Physiological / psychological / social factors and systems that drive food choices
  • Current methods for measuring eating habits / what and where people eat.
    • Individual level: Self-tracking devices, passive methodologies, and sensors
    • Population level: Spatial data, environmental data
  • Interventions for healthful eating
  • Data-driven studies of cultural eating trends (e.g. recipes) and nutrition / health implications

Food Supply Networks & Food Environment

Processes related to growing, manufacturing, and distributing food; infrastructure that affects access to and consumption of food

  • Methods for studying how urban, environmental (food availability / access / marketing) factors impact eating behavior and health
  • Mapping and modeling market and food supply system structure
  • Traceability in the food supply chain
  • Epidemiological studies related to tracing foodborne disease through the food supply

Objectives and Format

The objective of this satellite is to bring together a community of researchers interested in exploring new insights and collaborations that come from integrating current methodologies and findings across these food and health system themes, and the impact and translation of this knowledge. Presentations and sessions will catalyze discussion on complex topics related to food-nutrition-health networks and systems, aiming towards the following goals:

  1. to better understand the current state of the field from different disciplinary perspectives
  2. to identify intersections and interdependencies across systems that impact human health
  3. to formalize areas of future research that have potential to make major scientific advances in our knowledge and have potential to result in significant improvement in health outcomes
This will be facilitated through a format including presentations from invited speakers and tracks of contributed talks within each of the 4 themes, with time for discussion on open problems and future collaborations.

Call for Abstracts

We invite abstracts on all topics related to merging data and network science with nutrition, medicine, food science, behavioral/psychological, and public health approaches to food-nutrition-health networks and systems for contributed talks to take place at the satellite symposium. Topics of special interest are mentioned under each of the 4 themes (above).

We welcome new and/or recently published work. As this is an emerging field within network science, we also welcome work in progress and idea-generation themed contributions. Please indicate which of the 4 theme(s) your contribution fits in most closely.

There is no word limit on abstracts but please limit their length to one page, including title, authors, figure(s), references, etc. All abstracts will be considered for contributed and flash talks (please indicate if you have a preference).

The deadline for abstract submission is March 31 (Extended Deadline) and acceptance notifications will be sent by April 15.

Submission format

  • Authors are invited to submit 1-page abstracts
  • Submissions should include the title, author(s), affiliation(s) and email address for the corresponding author
  • Electronic submission of manuscripts in PDF format is required
All participants are required to register through the main conference. One- and two-day satellite-only registration is available for participants attending only the satellite sessions.


8:00-8:15 am Welcome & Introduction
8:15-9:30 am Network Medicine: Mapping food compounds and linking them to health; epidemiological studies
Keynote (30 min)
Invited Speaker (20 min)
Contributed Speaker (15 min)
2 Flash Talks (10 min)
9:30-10:45 am Food science, technology, and health implications: Plant biology, chemistry, pharmacology, and computation
Keynote (30 min)
Invited Speaker (20 min)
Contributed Speaker (15 min)
Flash Talks (10 min)
10:45-11:15 am Coffee Break
11:15 am-12:30 pm Population health networks and tracking technologies: Physiological/psychological factors that drive food choices and technologies that link consumption to health
Keynote (30 min)
Invited Speaker (20 min)
Contributed Speaker (15 min)
Flash Talks (10 min)
12:30-1:45 pm Food supply networks and food environment: Processes related to growing, manufacturing, and distributing food; infrastructure that affects access to and consumption of food
Keynote (30 min)
Invited Speaker (20 min)
Contributed Speaker (15 min)
Flash Talks (10 min)
1:45-2:00 pm Discussion + Future Collaborations



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.

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

Dr. Pachucki is an Assistant Professor in the Department of Sociology and the UMass Computational Social Science Institute. His research interests include social determinants of health, culture, and social network dynamics. If we better understand how, when, and why people are connected, we can gain insight into how health and culture changes at the individual, interpersonal, and population level over time. Prior to his UMass position, he was on the faculties at Massachusetts General Hospital and Harvard Medical School. His post-doctoral training was with the Robert Wood Johnson Foundation Health & Society Scholars program at UC Berkeley and UCSF. His research is currently supported by the National Institutes of Health (NICHD, NINR, NHLBI), and has been supported by the National Science Foundation, the Robert Wood Johnson Foundation, National Institute on Aging, National Institute of Diabetes and Digestive and Kidney Diseases.


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.