Byron Wallace
Valentin’s research combines computational methods from social data science and network analysis, with approaches from reproducible research and metascience to study issues of data governance, responsible data science workflows, transparency, reproducibility, bias, and social impact of data-intensive research. His current focus is on evaluating the robustness and reliability of AI/ML technologies in the social and health sciences.
Damon Centola
Damon Centola is the Elihu Katz Professor of Communication, Sociology and Engineering at the University of Pennsylvania, where he is the founding director of the Network Dynamics Group and a Senior Fellow at the Leonard Davis Institute of Health Economics. Before coming to Penn, Centola was a professor at MIT and a fellow at Harvard University.
The world's leading expert on how social networks influence behavior change, belief change and collective intelligence, Centola was awarded a U.S. Patent for inventing a network method to spread new ideas and beliefs online. His work has been funded by the National Science Foundation, the National Institutes of Health, the Robert Wood Johnson Foundation, the James S. McDonnell Foundation, the Templeton Foundation, Facebook, PerBak Capital Partners, and the Hewlett Foundation. He is the recipient of numerous scientific awards, including the 2017 James Coleman Award for Outstanding Research in Rationality and Society and the 2011 Goodman Prize for Outstanding Contributions to Sociological Methodology.
Centola is the author of Change, published in 2021 (Little Brown) and translated into 10 languages. His scholarly book, How Behavior Spreads, won the Harrison White Award for Outstanding Scholarly Book in 2019 and has been translated into three languages. His research and writing have been featured in media such as The New York Times, The Washington Post, The Wall Street Journal, Los Angeles Times, Philadelphia Inquirer, Chicago Tribune, The Atlantic, Wired, TIME, Science, Nature, Scientific American, New Scientist, Psychology Today, CNN, Hidden Brain, and NPR’s Radio Times. His speaking and consulting clients include Amazon, Apple, Cigna, General Motors, Microsoft, Ben & Jerry’s, the U.S. Army, the NBA, and many of the world’s largest philanthropic organizations.
Erin E. Bonar
Erin E. Bonar, Ph.D., is a licensed clinical psychologist and the Kathy Fant Brzoznowski Research Professor in Behavioral Health Technology Innovations and Professor with tenure in the Department of Psychiatry at the University of Michigan. She is the Director of Research Strategy for the Michigan Innovations in Addiction Care through Research and Education program (MI-ACRE). Dr. Bonar studies ways to prevent and treat substance use disorders spanning developmental periods of adolescence, emerging adulthood and adulthood. Her work uses novel technologies including social media, telemedicine, and patient portal approaches.
Fred Muench
Fred Muench, Ph.D. is a clinical psychologist with more than 20 years of experience designing and implementing digital interventions for mental health and addiction. He is the CEO of Clear30, a digital cannabis break and long-term support program for adolescents and young adults. He also serves as an Associate Professor at The Feinstein Institutes for Medical Research, where his work centers on developing, testing, and scaling digital tools for mental health and substance use care.
Previously, Fred was President and CEO of the Partnership for Drug-Free Kids, where he oversaw the creation of the nation’s largest digital support platform for families across prevention, recovery, and peer-based services. He led the organization through its merger with the National Center on Addiction and Substance Abuse, forming the Partnership to End Addiction, where he continued as President before launching Clear30 and returning to research.
Fred has held faculty appointments at Columbia University’s College of Physicians and Surgeons and adjunct positions at New York University in both the Department of Psychology and the Interactive Telecommunications Program, where he taught courses on building digital tools for mindful behavior change. He has served as Principal Investigator on numerous grants from NIAAA, NIDA, FDA, RWJF Pioneer, Upswing, Twilio, Google, and other foundations.
Laura Edelson
Laura Edelson is an Assistant Professor of Computer Science at Northeastern University. Her research focuses on the understanding the spread of harmful content on large online networks and using user data donation to understand social media algorithmic systems. Her work has been covered in the New York Times, the Wall Street Journal, and the Washington Post, and she has written about the need for transparency about social media algorithms in opinion writing for Scientific American and the New York Times. She is the co-Director of Cybersecurity for Democracy and the former Chief Technologist of the Antitrust Division and the Civil Rights Division of the Department of Justice.
Michael W. Wagner
Michael W. Wagner is the William T. Evjue Distinguished Chair for the Wisconsin Idea in the University of Wisconsin-Madison’s School of Journalism and Mass Communication, where he directs the Center for Communication and Civic Renewal. A former journalist and winner of multiple teaching, best article, and public service awards, Wagner’s work studying how individual engagement in the information ecology influences what people believe, want, and do, has been published in Science, Journal of Communication, Political Communication, and many other outlets. Wagner’s work has been funded by organizations including the National Science Foundation, the John S. and James L. Knight Foundation, and the William + Flora Hewlett Foundation.
Sherry Emery
Sherry Emery is a Senior Fellow at NORC, in the Public Health Department. She is also the Director of NORC’s Social Data Collaboratory, an interdisciplinary research team that collects and analyzes data from and about social and digital media. For over 25 years, her research has focused on understanding the effects of the advertising and marketing of tobacco products, food and beverages, and prescription drugs on individual and population health.
Valentin Danchev
Valentin’s research combines computational methods from social data science and network analysis, with approaches from reproducible research and metascience to study issues of data governance, responsible data science workflows, transparency, reproducibility, bias, and social impact of data-intensive research. His current focus is on evaluating the robustness and reliability of AI/ML technologies in the social and health sciences.