Dr. Predrag “Pedja” Klasnja is an Associate Professor in the School of Information at the University of Michigan. His research lies at the intersection of human-computer interaction, behavioral science, and health informatics and he studies how technology can better enable people to manage their health in their day-to-day lives. As an implementation researcher, the central focus of his work is on the development of causal pathway diagramming, which is an approach to represent causal processes hypothesized to underlie the functioning of implementation strategies. This approach allows researchers and practitioners to select strategies that are most likely to impact prioritized determinants of behavior, uncover factors that may influence the effectiveness of these strategies, and determine the appropriate measurement variable, which indicates that the implementation initiative is working as intended. As part of the Intensive Longitudinal Health Behavior Network, he was a Co-Principal Investigator on the “Dynamic Models of Behavior Study” (https://ilhbn.ssri.psu.edu/projects/dmb-dynamic-models-behavior), which was a micro-randomized  trial of a multi-component, multiscale, adaptive intervention to increase physical activity and sedentary behavior (https://www.si.umich.edu/people/pedja-klasnja).

Dr. Inbal Nahum-Shani is a Research Assistant Professor at the University of Michigan’s Institute for Social Research. Her research focuses on developing and employing behavioral theory and novel methodologies to construct adaptive interventions, namely interventions that modify the type, timing, dose, or delivery mode of support in order to address the unique and changing needs of individuals. She is an expert on deploying novel research methodologies including the Sequential Multiple Assignment Randomized Trial (SMART) design, related data analytic methods for constructing adaptive interventions, Factorial and Fractional Factorial Designs, and Multilevel Data Analysis and Experimental Designs for developing behavioral interventions. As part of the Intensive Longitudinal Health Behavior Network (https://ilhbn.ssri.psu.edu/projects), she was the Principal Investigator on the “Mobile Application for regulating Smoking study” (https://ilhbn.ssri.psu.edu/projects/mars-mobile-application-regulating-smoking), which aimed to identify states of vulnerability and receptivity to just-in-time interventions. The study employed methods for the joint modeling of EMA, location, motion sensors, and time to event as a function of underlying latent states (https://ihpi.umich.edu/our-experts/inbal).

Dr. Genevieve Dunton is a Professor of Preventive Medicine and Psychology at the University of Southern California. Dr. Dunton´s research examines the etiology of health behaviors related to chronic disease risk in children and adults, with a focus on physical activity and nutrition. Dr. Dunton is the Director of the USC REACH (Real-Time Eating Activity and Children’s Health) lab, the goals of which are to develop, test, and apply real-time data capture methodologies, including EMA and wearable sensors, to better understand the effects of time-varying psychological, social, and environmental factors on eating and physical activity episodes. As part of the Intensive Longitudinal Health Behavior Network (https://ilhbn.ssri.psu.edu/projects/time-temporal-influences-movement-and-exercise), she was the Co-Principal Investigator on the “Time Influences of Movement and Exercise study,” which aimed to assess differences in the micro-temporal processes underlying the adoption vs. maintenance of physical activity and sedentary behaviors (https://keck.usc.edu/faculty-search/genevieve-dunton/).

Dr. Stephen Intille is an Associate Professor in the Khoury College of Computer Sciences and the Bouve College of Health Sciences at Northeastern University. He leads a multi-disciplinary research team exploring the application of advanced sensing and mobile technologies to preventive health domains. An area of interest is the measurement of health-related behaviors, such as physical activity, sedentary behavior, and sleep, as well as measurement of eating behaviors and other contextual factors and affective states, often via context-sensitive self-report. He is experienced in deploying and evaluating systems in a variety of domains where automatic pattern recognition algorithms may support novel preventive health technologies that measure health behavior and motivate health behavior change with “just-in-time” information presentation. As part of the Intensive Longitudinal Behavior Network (https://ilhbn.ssri.psu.edu/projects/time-temporal-influences-movement-and-exercise), he was the Co-principal investigator on the “Time Influences of Movement and Exercise study,” which aimed to assess differences in the micro-temporal processes underlying the adoption vs. maintenance of physical activity and sedentary behaviors (https://www.khoury.northeastern.edu/people/stephen-intille/).

Dr. Justin T. Baker, MD, PhD, is the scientific director of the McLean Institute for Technology in Psychiatry (ITP) and director of the Laboratory for Functional Neuroimaging and Bioinformatics at McLean Hospital. Dr. Baker’s research uses both large-scale studies and deep, multilevel phenotyping approaches to understand the nature and underlying biology of mental illnesses. His current deep phenotyping projects use single-case experimental designs in individuals with severe conditions including bipolar disorder, schizophrenia, borderline personality disorder, and obsessive-compulsive disorder. By applying computational approaches, such as latent construct modeling, machine learning, and dynamical systems analysis, the data collected from each study—and each individual—can reveal key relationships to advance human neuroscience and develop novel, personalized therapeutics. His research studies involve the collection and analysis of temporally dense behavioral assessments to study neuropsychiatric conditions using an array of acquisition technologies and analytic approaches. As part of the Intensive Longitudinal Behavior Network (https://ilhbn.ssri.psu.edu/projects/bls-bi-polar-longitudinal-study), he was the Co-Principal Investigator on the “Bi-Polar Longitudinal Study”, which aimed to predict adverse events (mania/psychosis) prior to their occurrence via the detection of changes in behavior of at-risk patients.  (https://www.mcleanhospital.org/profile/justin-baker).