As people interact with devices like smartphones, fitness trackers, and social media platforms, they leave behind digital traces. By collecting and analyzing these traces, we can uncover behavioral patterns and quantify an individual’s health and well-being over time.
In this talk, I will introduce the emerging field of digital phenotyping and present findings from several digital phenotyping studies we have conducted. These longitudinal, multi-sensor studies capture a wide range of digital traces from participants. We combine passively collected data from personal devices with subjective surveys completed regularly throughout the study.
The goal of digital phenotyping is to continuously measure and understand human behavior, with a particular focus on mental health. This approach addresses a critical gap in mental healthcare: the lack of high-resolution data on a patient’s condition between clinical visits. I will share how we integrate objective and subjective data to assess both physical and mental health and how we use these insights to predict future health outcomes.
Dr. Talayeh Aledavood
Lecturer at Aalto University, Finland
Talayeh Aledavood leads the Digital Traces Lab at the Department of Computer Science, Aalto University, Finland, where she is a tenured University Lecturer. Until March 2023, she also served as the department’s Vice Head for Diversity, during which she founded and led the committee on Equality, Diversity, and Inclusion. Previously, Talayeh was a James S. McDonnell (JSMF) Postdoctoral Fellow at the School of Interactive Computing at Georgia Tech, where she worked in the Social Dynamics and Well-Being (SocWeB) Lab, advised by Prof. Munmun De Choudhury. Prior to that, she held a JSMF Fellowship at the Department of Psychiatry, University of Helsinki, collaborating with Prof. Erkki Isometsä. Talayeh also completed postdoctoral research at Aalto University’s Department of Computer Science, where she earned her Ph.D. (with distinction) in December 2017 under the supervision of Prof. Jari Saramäki. Her doctoral thesis, titled Temporal Patterns in Human Behavior, explored the patterns of human activity over time extracted from digital traces. Additionally, she completed the EIT Digital Doctoral Program, gaining experience in entrepreneurship and translating research into practical products. In the past, Talayeh has completed research visits to Harvard T.H. Chan School of Public Health, Oxford University Internet Institute, and the Technical University of Denmark.
