Vahid Farrahi


Information Technology


The main focus of my research in the academia, so far, have been applying data mining techniques on the real world problems. Currently, my Ph.D. studies is funded by BioMEP under the Marie Skłodowska-Curie grant agreement No 713645. The ultimate goal of the the project is to assess physical activities and sedentary behavior in Northern Finland Birth Cohort studies, during 14 days of monitoring using accelermeters. We are specifically interested in the association of various health-outcomes with patterns of physical activities and sedentary behaviors.

Research interests

  • Objectively measured physical activity
  • Data Analytics

Ph.D. project abstract

Physical activity is well-known by general public to be a necessity for maintaining health and well-being, which is completely true. To date, it has been proved that physical activity highly correlates with certain type of health problems including diabetes and cancer. For having a better physically active society, providing recommendations at individual and public level regarding physical activity, and getting insights about physical activity and sedentary behaviors in a society, estimation of physical activities in terms of duration, intensities, and energy expenditure on physical activities are necessary non-trivial tasks.

Objective measurement of physical activity data using accelerometers is a practical method of assessing physical activity behaviors. However, it is still a challenge to accurately estimate the amount, intensity and type of physical activities using accelerometer data. To date, (traditional) statistical methods were applied on physical activity data to assess physical activity behaviors. The overall goal of the project is the transition from traditional statistical methods to (big) data mining methods to assess their accuracy and applicability, in order to get better insights about physical activity and sedentary behaviors. Furthermore, as the project constituents follow-up data (including biological samples and subjects’ characteristics), relating various health variables to physical activity behaviors through big data analytics is of great importance as a goal. Ultimately, the health and well-being will be promoted by providing more accurate insights for health practitioners.


Research groups

  • Ph.D. Student,