Speakers

Dr. Marco Giurgiu is a post-doctoral researcher at the Department of Sport and Sport Science, Karlsruhe Institute of Technology (KIT). During his PhD, he worked intensively on the topic of sedentary behaviour. In particular, his research area comprises examining associations between device-based measured physical behaviour and momentary psychological outcomes by using innovative data collection approaches in real-time (e.g., via smartphone diaries and wearables). The focus is also on just-in-time interventions to integrate sedentary breaks into everyday life. Another area of focus is the measurement of physical behaviour using wearables. Marco Giurgiu’s research particularly addresses the validation of wearables. He is leading the open- science project “Wearable Landscape” (https://wearable-landscape.info/).

Since October 1, 2024, Markus Reichert has been Professor of Sport and Exercise Science at the University of Salzburg (PLUS). He succeeds Günter Amesberger and strengthens the department with a focus on sport psychology, health, and prevention. Markus Reichert completed his studies in sport science in 2012 with a Master of Science at Karlsruhe Institute of Technology (KIT). His doctoral research, completed in 2019, examined the “psychological antecedents and consequences of everyday physical activity,” with studies conducted at KIT and the Central Institute of Mental Health (ZI) in Mannheim. Following his PhD, Reichert worked as a postdoctoral researcher at KIT and ZI Mannheim before accepting a junior professorship in eHealth and Sports Analytics at Ruhr University Bochum in 2021. In Salzburg, he will shape the field of sport psychology with a particular emphasis on health, prevention, and research methodology. Reichert places great importance on modern m(obile)Health approaches that enrich sport psychology and health research. To address his research questions in an ecologically valid and neurobiologically grounded manner, Reichert pursues a multidisciplinary approach, combining methods from sport science, psychology, neuroscience, geoinformatics, and epidemiology. One of his main research areas is the impact of everyday movement—from daily physical activity to structured exercise—on emotional well-being and mental health. His findings significantly contribute to the development of digital health applications aimed at preventing and treating mental disorders such as depression and addiction.

Anna-Maiju Leinonen, PhD (Medical Technology), works as a postdoc researcher at the University of Oulu and the Oulu Deaconess Institute Foundation. Anna-Maiju’s research interests are related to measuring and promoting physical activity. She has gained strong experience in population-based epidemiological research. In recent years, Anna-Maiju has worked as a postdoc researcher and project manager in the SEPAS project, which has examined the societal and economic impacts of physical activity and sedentary behavior utilizing the Northern Finland Birth Cohort 1966 data. 

Marcus Schmidt studied mathematics and physical education. Since finishing his Master's degree in 2011, he works as a scientific employee at the Institute for Sport and Sport Science at TU Dortmund University. He did his PhD about the use of inertial measurement units for jumping and sprinting diagnosis in track and field. His main research interests are the use of sensor technology for the biomechanical analysis of several sports (track and field, volleyball, basketball, handball), performance enhancement, injury prevention as well as underlying aspects of motor learning.

Dr. Saeid Azadifar is a postdoctoral researcher in the MSCA COFUND Data4Healthcare programme, Health science and Technology, University of Oulu, Finland. His research focuses on the role of digital biomarkers derived from wearable devices, such as the Oura Ring, in predicting and understanding health outcomes. During his PhD, he worked extensively on gene prioritization, integrating machine learning models such as graph convolutional networks with biological data to identify disease-associated genes. His broader research interests include data-driven health monitoring, machine learning, digital health, and personalized health technologies.

Dr. Janis Fiedler is a postdoctoral researcher at the Karlsruhe Institute of Technology in Germany. He completed his PhD on the topic of mHealth interventions to enhance physical activity and has since broadened his research focus to include performance diagnostics, fitness, and body composition as foundations for individualized physical activity interventions. Dr. Fiedler is a core member of the Wearable Landscape project, leads the current stage of the living review, and is committed to fostering a culture of open science.

Adham Abdelazeem is a PhD researcher and Research Associate at TU Dortmund University’s Institute of Sport and Sport Science. His research focuses on wearable-based measurement of physical behaviors and the development of data-driven methods to link daily activity patterns with health outcomes. Building on his background in biomedical engineering and machine learning, he explores interpretable analytical frameworks for accelerometer data, aiming to improve cross-cohort comparability and translation to real-world interventions. 

Alireza Sameh is a PhD researcher at University of Oulu, Finland. His research focuses on extract and utilize digital phenotypes and digital biomarkers collected via wearable devices to predict, screen, and analyse mental health problems using Machine learning approaches. He is activly using the Finland Birth Cohort data (NFBC 1966 and 1986) in his project for this project. He is a machine learning scientist with over five years of experience, specializing in developing and prototyping data preparation workflows, time series analysis, signal processing and model architectures to solve data-driven problems in business and healthcare. 

Esmaeil Farhang is a researcher at TU Dortmund, working on AI applications in healthcare. His current focus lies in foundation and large language models (LLM), and the physiological and behavioral wearable signals—such as actigraphy and accelerometer data—for predicting chronic diseases. He has accumulated around five years of experience as a Data Scientist and R&D Machine Learning Engineer, contributing to diverse AI applications including computer vision, speech processing, LLMs, and time-series analysis. During his master’s studies, he conducted research in vision science and the primate visual cortex. Esmaeil holds a B.Sc. in Applied Mathematics and an M.Sc. in Computer Science with a specialization in Artificial Intelligence.