Continuing & Professional Studies, Palo Alto University

Dr. Eduardo Bunge is a Professor in the Department of Psychology at Palo Alto University (PAU). Dr. Bunge directs the Children and Adolescents Psychotherapy and Technology (CAPT) Research Lab, and is Associate Director for the International Institute of Internet Interventions for Health at Palo Alto University.  His works focus on integrating technology and mental health, and his most recent contributions were in Artificial Intelligence-Based Chatbots for depression, anxiety, and parenting in English and Spanish. He is also the Director of the Master of Science in Psychology at PAU. He was born and educated in Argentina, earned his undergraduate degree at the University of Buenos Aires, and received his Ph.D. in psychology from the University of Palermo (Argentina). Dr. Bunge has more than 80 publications, including five clinical books and more than 70 peer-reviewed articles and chapters.

Nick Jacobson is an assistant professor in the departments of Biomedical Data Science and Psychiatry within the Center for Technology and Behavioral Health in the Geisel School of Medicine at Dartmouth College. He directs the AI and Mental Health: Innovation in Technology Guided Healthcare (AIM HIGH) Laboratory. Dr. Jacobson researches the use of technology to enhance both the assessment and treatment of anxiety and depression. His work has focused on (1) enhancing precision assessment of anxiety and depression using intensive longitudinal data, (2) conducting multimethod assessment utilizing passive sensor data from smartphones and wearable devices, and (3) providing scalable, personalized technology-based treatments utilizing smartphones. He has a strong interest in creating personalized just-in-time adaptive interventions and the quantitative tools that make this work possible. To date, Dr. Jacobson’s smartphone applications which assess and treat anxiety and depression have been downloaded and installed by more than 50,000 people in over 100 countries. Dr. Jacobson is the principal investigator of an R01 Awarded from the National Institute of Mental Health studying the use of personalized deep learning models to predict rapid changes in major depressive disorder symptoms using passive sensor data from smartphones and wearable devices. Additionally, Dr. Jacobson has a strong quantitative background in analyzing intensive longitudinal data. In his work, he employs many different types of analyses including structural equation modeling, multilevel modeling, time-series techniques, dynamical systems modeling, and machine learning. He created a novel modeling technique, entitled the Differential Time-Varying Effect Model (DTVEM), which allows researchers to discover and model optimal lag times in intensive longitudinal data. He recently developed an anxiety and depression monitoring application entitled Mood Triggers which helps users to learn the triggers of their anxiety and depression in their daily lives. He also created an statistical package (written in R) called the Differential Time-Varying Effect Model (DTVEM) which is used to explore optimal time lags in intensive longitudinal data. Driven by a passion to transform mental health care through technology, Dr. Jacobson focuses on harnessing artificial intelligence and passive sensor data from smartphones and wearable devices to develop scalable, personalized interventions for anxiety and depression. His expertise lies in creating personalized just-in-time adaptive interventions and advancing quantitative tools that enable this work.