All past updates

2024

• [2024-10-11] Our paper “Smartphone screen time characteristics in people with suicidal thoughts: retrospective observational data analysis study” is published. This work shows the feasibility of using passively collected phone logs for studying smartphone screen time characteristics as an alternative to self-report measures in people with suicidal thinking.
  
  

• [2024-05-30] Our paper “Tracking amyotrophic lateral sclerosis disease progression using passively collected smartphone sensor data” is published. This study demonstrates how passively collected GPS and accelerometer data from smartphones can be used to quantify changes in mobility, walking, and other motor functions in individuals with ALS.
  
  

• [2024-03-30] I obtained a green card through the EB-2 NIW process.
  
  

• [2024-03-01] 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.
  
  

2023

• [2023-03-06] 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.
  
  

2022

• [2022-11-21] Our preprint “Wearable device and smartphone data can track ALS disease progression and may serve as novel clinical trial outcome measures” is out. 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.
  
  

• [2022-10-25] 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.
  
  

• [2022-07-27] Our paper “Estimating knee movement patterns of recreational runners across training sessions using multilevel functional regression models” is published. 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.
  
  

• [2022-07-22] 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).
  
  

• [2022-07-13] 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.
  
  

• [2022-04-27] I was elected as a member of the Alpha chapter of the Delta Omega Society. A nice certificate I received is available here.
  
  

• [2022-01-13] Our paper “Free-living gait cadence measured by wearable accelerometer: a promising alternative to traditional measures of mobility for assessing fall risk” is published. We showed that in community-dwelling older adults, free-living walking cadence was significantly related to fall rates (while clinic-based mobility measures were not).
  
  

• [2022-01-01] For my first post-grad role, I accepted a postdoctoral researcher position at the Onnela Lab at Harvard University. I will be working at methods for digital phenotyping and its applications.
  
  

2021

• I defended my PhD thesis “Statistical Methods for Wearable Device Data and Sample Size Calculation in Complex Models”! My defense slides, with video recording linked, are available. I published the Acknowledgements and Dedication parts of the thesis.
  
  

• I received Travel Reimbursement Award to 3rd Annual Health Data Science Symposium at Harvard to present our work on harmonization of open-source and proprietary accelerometry-based physical activity measures in Nov 2021.
  
  

• Our preprint “Upstrap for estimating power and sample size in complex models” is available on bioRxiv. We evaluate power estimation properties of the upstrap and provide a series of “read, adapt and use” R code examples for simple and complex settings, including GLMM. See the relevant project page.
  
  

• I received Student Poster Sponsorship and will present our work on harmonization of open-source and proprietary accelerometry-based physical activity measures during the ActiGraph Digital Data Summit in Nov 2021.
  
  

• I am a co-instructor for Introduction to R for Public Health Researchers Summer Institute week-long course. All class materials are available online.
  
  

• Our paper “Estimation of free-living walking cadence from wrist-worn sensor accelerometry data and its association with SF-36 quality of life scores” is published. Check out the GitHub repo showing examples of using our method for automatic walking strides segmentation from wrist-worn sensor accelerometry data collected in the free-living environment.
  
  

• I received the Louis I. and Thomas D. Dublin Award for the Advancement of Epidemiology and Biostatistics for work on open-source physical activity measurements.
  
  

• I received the Helen Abbey Award for excellence in teaching.
  
  

• Our paper “Connectivity‐informed adaptive regularization for generalized outcomes” is published. We proposed riPEER (ridgified Partially Empirical Eigenvectors for Regression) extension to generalized linear regression, addressing both theoretical and computational issues. See the relevant project page.
  
  

2020

• Our paper “Predicting Subjective Recovery from Lower Limb Surgery Using Consumer Wearables” is published. We showed that passively collected wearable PGHD can capture post-surgery physical activity changes relative to individual’s baseline, and baseline data can improve prediction of self-reported recovery time at 4 weeks post surgery.
  
  

• During the upcoming workshop “The Future of Digital Health”, I will give a talk highlighting “Predicting subjective recovery from lower limb surgery using consumer wearables” paper I co-authored. This workshop will highlight key papers from the newly released Special Issue of Digital Biomarkers, sponsored by Evidation Health and DiMe. Register for the workshop here.
  
  

• During summer of 2020, I am working as a Data Science Intern in Digital Measures team @ Evidation Health. My main project aims at estimating medical procedure recovery trajectories and predicting recovery time from wearable patient-generated health data.
  
  

• Why R? Foundation awards a supporting grant for Women in Data Science to aid exceptional female data scientists in Poland. I serve as a member of Scientific committee for this initiative.
  
  

2019

• I passed my preliminary schoolwide oral exam. My Committee consisted of three faculty from the Dept. of Biostatistics, one faculty from Dept. of Epidemiology, and one faculty from the Dept. of Medicine.
  
  

• I received Leadership, Empowerment and Learning Culture Award during Novartis US Analytics Conference 2019. My conference talk presented the work done as a Sensor Data Analytics Intern with Novartis in Basel, Switzerland during summer 2019.
  
  

• Our paper “Adaptive empirical pattern transformation (ADEPT) with application to walking stride segmentation” just got published in Biostatistics with the journal’s highest reproducibility status! See ADEPT article online.
  
  

• Our R package adept that implements ADEPT pattern-segmentation method is out on CRAN (CRAN index. The vignette shows example of strides segmentation from raw accelerometry data of 25min outdoor run w/ walking and resting bouts. Listed May 2019 top 40 new CRAN packages.
  
  

• I am working as Sensor Data Analytics Intern with Novartis pharmaceutical company in Basel, Switzerland this summer. I am also presenting at ICAMPAM 2019 conference on Jun 26 in Maastricht, the Netherlands.
  
  

• Our R package runstats that provides methods for fast computation of running sample statistics for time series is out on CRAN (CRAN index). Use runstats to compute (1) mean, (2) standard deviation, and (3) variance over a fixed-length window of time-series, (4) correlation, (5) covariance, and (6) Euclidean distance (L2 norm) between short-time pattern and time-series. Implemented methods utilize Convolution Theorem to compute convolutions via Fast Fourier Transform (FFT).
  
  

• Our recent article “Accelerometry Data in Health Research: Challenges and Opportunities” is now published and available online.
  
  

2018

• Interested in statistical methodology for singal processing in physical activity research? Come to JSM session on Wednesday (8/1/2018), 2:00 PM - 3:50 PM.
  
  

• WhyR? 2018 conference starts on July 2nd in Wroclaw, Poland. Both academia and industry professionals meet and discuss experiences in R software development and analysis applications.
  
  

• I am working as a Research Assistant with Drs. Jacek Urbanek and Ciprian Crainiceanu this summer at a novel approach for identifying individual working strides from subsecond accelerometry data of walking.