Felix Beierle 
Can you predict if a self-described pornography-addict will relapse – based on his previous mental condition? We used machine learning to answer this question based on data collected by polish collaborators. Users used a mobile app for tracking their addictions and mental state. You can find a full project description and code on GitHub.
Today, I am starting at the National Institute of Informatics (NII) in the group of Prof. Akiko Aizawa. I acquired funding financing my full-time position in the competitive program IFI (German: Internationale Forschungsaufenthalte für Informatikerinnen & Informatiker) by the German Academic Exchange Service (DAAD). I will work on topics relating to user retention, data science, … Read more
Next app prediction can help enhance user interface design, pre-loading of apps, and network optimizations. Prior work has explored this topic, utilizing multiple different approaches but challenges like the user cold-start problem, data sparsity, and privacy concerns related to contextual data like location histories, persist. The user cold-start problem occurs when a user has recently … Read more
Physical and mental well-being during the COVID-19 pandemic is typically assessed via surveys, which might make it difficult to conduct longitudinal studies and might lead to data suffering from recall bias. Ecological momentary assessment (EMA) driven smartphone apps can help alleviate such issues, allowing for in situ recordings. Implementing such an app is not trivial, … Read more
Several governments introduced or promoted the use of contact-tracing apps during the ongoing COVID-19 pandemic. In Germany, the related app is called Corona-Warn-App, and by end of 2020, it had 22.8 million downloads. Contact tracing is a promising approach for containing the spread of the novel coronavirus. It is only effective if there is a … Read more
Through lockdowns and other severe changes to daily life, almost everyone is affected by the COVID-19 pandemic. Scientists and medical doctors are – among others – mainly interested in researching, monitoring, and improving physical and mental health of the general population. Mobile health apps (mHealth), and apps conducting ecological momentary assessments (EMA) respectively, can help … Read more
My PhD thesis (full title: Integrating Psychoinformatics with Ubiquitous Social Networking: Advanced Mobile-Sensing Concepts and Applications) was published as a book with Springer. You can read a preview of the book here. You can buy from Springer directly, or get it via Amazon (for example, US, DE, JP).
Imagine getting recommendations, for example, for music or TV shows, based on similar people you pass by on the street. No server backend needed, all via device-to-device communication. We designed and implemented such a system. You can find our full article published in IEEE Access here (PDF) and the code on GitHub. We build the … Read more
Today, I successfully defended my PhD (Dr. rer. nat.) thesis “Integrating Psychoinformatics with Ubiquitous Social Networking Through Advanced Mobile-Sensing Concepts and Applications” and was graded with distinction (summa cum laude)! I am grateful for the committee: Prof. Dr. Axel Küpper, Prof. Dr. Rüdiger Pryss, Prof. Dr. Jöran Beel, and Prof. Dr. Sebastian Möller.
We investigated associations between personality traits and smartphone usage in daily life. 526 participants (mean age 34.57 years, SD = 12.85, 21% female) used TYDR (Track Your Daily Routine) for 48 days, on average (SD = 63.2, range 2 to 304). The Big Five Inventory 2 (BFI-2) was used to measure personality traits (Extraversion, Agreeableness, … Read more