Research

Methodology

1. Ghosal, R., Ghosh, S., Schrack, J. A., & Zipunnikov, V. (2025). Distributional outcome regression and its application to modelling continuously monitored heart rate and physical activity. Journal of the American Statistical Association.

2. Ghosal, R., Matabuena, M., & Ghosh, S. (2025). Functional Time Transformation Model with Applications to Digital Health. Computational Statistics & Data Analysis.

3. Dey, D., Ghosal, R.*, Merikangas, K., & Zipunnikov, V. (2024). Functional Principal Component Analysis for Continuous Non-Gaussian, Truncated, and Discrete Functional Data. Statistics in Medicine.

4. Ghosal, R. & Matabuena, M. (2024). Multivariate Scalar on Multidimensional Distribution Regression. Biometrical Journal.

5. Cho, E., Saha, E., Matabuena, M., Wei, J., &  Ghosal, R. (2024). Exploring the Association between Daily Distributional Patterns of Physical Activity and Cardiovascular Mortality Risk among Older Adults in NHANES 2003-2006. Annals of Epidemiology.

6. Ghosal, R. & Maity, A. (2023). Variable Selection in Nonlinear Function-on-Scalar Regression. Biometrics.

7. Ghosal, R., Matabuena, M., & Zhang, J. (2023). Functional proportional hazards mixture cure model with applications in cancer mortality in NHANES and post ICU recovery. Statistical Methods in Medical Research.

8. Ghosal, R., Ghosh, S., Urbanek, J., Schrack, J. A., & Zipunnikov, V. (2023). Shape-Constrained Estimation in Functional Regression with Bernstein Polynomials. Computational Statistics & Data Analysis.

9. Ghosal, R. & Maity, A. (2023). Variable Selection in Function-on-Scalar Single Index Model via the Alternating Direction Method of Multipliers. TEST.

10. Saha, E. & Ghosal, R.* (2023). Gender Difference in the Effects of Chronic Diseases on Daily Physical Activity Patterns in Older Adults: Analysis of Objectively Measured Physical Activity in NHATS 2021. Annals of Epidemiology.

11. Ghosal, R., Varma, V. R., Volfson, D., Urbanek, J., Hausdorff, J. M., Watts, A., & Zipunnikov, V. (2022). Scalar on Time-by-Distribution Regression and its Application for Modelling Associations Between Daily-Living Physical Activity and Cognitive Functions in Alzheimer’s Disease. Scientific Reports.

12. Ghosal, R. & Ghosh, S. (2022). Bayesian Inference for Generalized Linear Model with Linear Inequality Constraints. Computational Statistics & Data Analysis.

13. Ghosal, R. & Maity, A. (2022). Variable Selection in Nonparametric Functional Concurrent Regression. The Canadian Journal of Statistics.

14. Ghosal, R. & Maity, A. (2022). A Score-Based Test for Functional Linear Concurrent Regression. Econometrics and Statistics.

15. Ghosal, R. & Saha, E. (2021). Impact of the COVID-19 Induced Lockdown Measures on PM₂.₅ Concentration in the USA. Atmospheric Environment.

16. Ghosal, R., Varma, V. R., Hillel, I., Volfson, D., Hausdorff, J. M., Watts, A., & Zipunnikov, V. (2021). Distributional Data Analysis via Quantile Functions and its Application to Modelling Digital Biomarkers of Gait in Alzheimer's Disease. Biostatistics.

17. Ghosal, R., Maity, A., Clark, T., & Longo, S. (2020). Variable Selection in Functional Linear Concurrent Regression. Journal of the Royal Statistical Society: Series C.

18. Mirzaei, S., Sengupta, D., & Ghosal, R. (2020). Estimating Menarcheal Age Distribution from Partially Recalled Data. Biostatistics.

Applied Research

1. Ghosal, R., White, J., Finnegan, O., Nelakuditi, S., ..., & Weaver, R. G. (2025). Leveraging Accelerometry and Heartrate Data from Consumer Wearables to Predict Physical Activity in Children: A Device Agnostic Approach. Medicine & Science in Sports & Exercise.

2. Hoppmann, A. L., Hurley, D. M., Cramer, S., Brown, M. J., Ghosal, R., Alberg, A. J., & Bhatia, S. (2025). Neighborhood Socioeconomic Status and Overall Survival among Children with Acute Lymphoblastic Leukemia. Blood Advances.

3. Finnegan, O. L., White, J., Armstrong, B., ..., Ghosal, R., ..., & Weaver, R. G. (2025). The Ability of Monitor-Independent Movement Summary Units... to Harmonize Accelerometry Data... During Simulated Free-Living Physical Activity in Children. Journal for the Measurement of Physical Behaviour.

4. Weaver, R. G., White, J., Finnegan, O. L., Yang, H., ..., Ghosal, R., ..., Armstrong, B., & Beets, M. (2025). Predicting Sleep and Sleep Stage in Children Using Actigraphy and Heartrate via a Long Short‐Term Memory Deep Learning Algorithm: A Performance Evaluation. Journal of Sleep Research.

5. Finnegan, O. L., Yang, H., Armstrong, B., Nelakuditi, S., ..., Ghosal, R., ..., & Weaver, R. G. (2025). Applying Behavioral Biometrics to Mobile Device Use Measurement in Children: Evaluating the Impact of Training Data Size, Proximity, and Type on Model Performance. Journal of Technology in Behavioral Science.

6. Li, K., Ghosal, R.*, ..., & Wei, J. (2024). The Associations of Sensory Impairment with 10-Year Risk of Dementia and Alzheimer’s Disease: The Health and Retirement Study, 2010-2020. Journal of Geriatric Psychiatry and Neurology.

7. Wei, J., Li, K., Ghosal, R., Zhang, D., Merchant, A. T., & Crump, C. (2024). Initiation of Hearing Aids Use and Incident Dementia Among Mid-to-late Life Adults: The Health and Retirement Study 2010-2018. Journal of Geriatric Psychiatry and Neurology.

8. Weaver, R. G., Chandrasekhar, M., Armstrong, B., ..., Ghosal, R., ..., & Yang, H. (2024). Jerks are Useful: Extracting Pulse Rate from Wrist-Placed Accelerometry Jerk During Sleep in Children. Sleep.

9. White, J., Finnegan, O., Tindall, N., ..., Ghosal, R., ..., & Weaver, R. G. (2024). Comparison of Raw Accelerometry Data from ActiGraph, Apple Watch, Garmin, and Fitbit Using a Mechanical Shaker Table. PLOS ONE.

10. Cepni, A. B., Burkart, S., Zhu, X., White, J., Finnegan, O., Nelakuditi, S., ..., Ghosal, R., ..., & Weaver, R. G. (2024). Evaluating the performance of open-source and proprietary processing of actigraphy sleep estimation in children with suspected sleep disorders.... Sleep.

11. Finnegan, O. L., Weaver, R. G., Yang, H., White, J. W., Nelakuditi, S., Zhong, Z., ..., Ghosal, R., ..., & Armstrong, B. (2024). Advancing Objective Mobile Device Use Measurement in Children Ages 6–11 Through Built‐In Device Sensors: A Proof of Concept Study. Human Behavior and Emerging Technologies.

12. Weaver, R. G., White, J., Finnegan, O., Nelakuditi, S., ..., Ghosal, R., ..., & Parker, H. (2023). [suspicious link removed]. Medicine & Science in Sports & Exercise.

13. Weaver, R. G., De Zambotti, M., White, J., Finnegan, O., Nelakuditi, S., ..., Ghosal, R., ..., & Parker, H. (2023). Evaluation of a Device-Agnostic Approach to Predict Sleep from Raw Accelerometry Data... in Children with Sleep Disruptions. Sleep Health.

14. Varma, V. R., Ghosal, R., Hillel, I., Volfson, D., Weiss, J., Urbanek, J., Hausdorff, J. M., Zipunnikov, V., & Watts, A. (2021). Continuous Gait Monitoring Discriminates Community-Dwelling Mild AD from Cognitively Normal Controls. Alzheimer's & Dementia: Translational Research & Clinical Interventions.

*Equal contribution