As a statistician on Takeda’s Quantitative Sciences team in Boston, MA, I focus on statistical modeling and analysis of data from digital devices such as wearable accelerometers, ambulatory blood pressure monitors, respiratory monitors, and polysomnography. My recent projects involve digital assessments in hypersomnolence disorders and ALS.

Before joining Takeda, I was a postdoctoral researcher at the Onnela Lab at Harvard T.H. Chan School of Public Health. I received a PhD in Biostatistics from Johns Hopkins Bloomberg School of Public Health in 2021, and hold Bachelor’s and Master’s degrees in Mathematics from Wroclaw University of Science and Technology, Poland.

In my leisure moments, I find joy in connecting with people, running, and hiking. The peak of my running tenure was probably finishing a full marathon in 2017. Currently, I am working on summiting New Hampshire’s 48 peaks over 4,000 feet. Some summits photos can be found in my 🌄 gallery.

Recently

• Our paper “Upper limb movements as digital biomarkers in people with ALS” is published. This work proposes several measures that quantify count and duration of upper limb movements: flexion, extension, supination, and pronation from wearable accelerometer data.
  
  

• Our paper “Wearable device and smartphone data can track ALS disease progression and may serve as novel clinical trial outcome measures” is published. This work investigates whether mobile applications and wearable devices can be used to quantify ALS disease progression through active (surveys) and passive (sensors) data collection.
  
  

• Our preprint “Performance analyses of step-counting algorithms using wrist accelerometry” is available online. This work evaluates performance of several modern wrist-accelerometry-based algorithms for step count estimation using a common dataset with various continuous walking trials.
  
  

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