Bio

I am a postdoctoral researcher at the Onnela Lab in the Department of Biostatistics at Harvard T.H. Chan School of Public Health. I am working on methods for digital phenotyping and its applications with Beiwe platform.

My statistical methods interests include: methods for processing, features extraction and analysis of accelerometry data, power estimation in complex settings, functional regression methods, machine learning, R software development.

I received PhD in Biostatistics from Johns Hopkins Bloomberg School of Public Health in December 2021. I received my Bachelor’s and Master’s degrees in Mathematics from Wroclaw University of Science and Technology in Poland in 2013 and 2015. Prior to joining Johns Hopkins, I worked as a research assistant at Indiana University and as an analyst for Opera Software Internet browser company.

In my free time, I enjoy connecting with people and running. I completed my first full marathon in 2017 in Denver, CO.

Download my CV.

Recently

• Our work “Estimating knee movement patterns of recreational runners across training sessions using multilevel functional regression models” is accepted. This work can serve as a reference for practitioners modeling repeated functional measures at different resolution levels in the context of biomechanics and sports science applications.
  
  

• Our paper “Comparison of Accelerometry-Based Measures of Physical Activity: Retrospective Observational Data Analysis Study” is published. This work provides comparison and harmonization mapping between minute-level accelerometry-derived measures (ActiGraph AC, MIMS, ENMO, MAD, AI).
  
  

• Our paper “Quantification of acceleration as activity counts in ActiGraph wearables” is out. This work publishes activity counts algorithm from ActiGraph’s ActiLife and CentrePoint.
  
  

• I was elected as a member of the Alpha chapter of the Delta Omega Society.
  
  

See all past updates.