About me
Debangan Dey is an Assistant Professor in the Department of Statistics at Texas A&M University. His research focuses on building theory and methods for multivariate stochastic processes as a unifying AI framework to analyze intensive, multilevel, multimodal, longitudinal data collected across space and time. This type of data arises in studies employing Digital Health Technologies, such as smartphone apps and smartwatches, with contextual spatial information like weather, light, and greenspace etc. through location tracking. His work aims to uncover how mental health, sleep, physical activity, and the environment interact and evolve over time.
🚨 Looking for motivated students to work on statistical and machine learning methods for analyzing data from wearables ⌚️, smartphones 📱, with contextual location information📍!
📘 2025: Will be teaching STAT 641: The Methods of Statistics I in Fall 2025.
🎓 2025: Joining Texas A&M University as an Assistant Professor in the Department of Statistics.
📄 2025: Published Graph-constrained analysis for multivariate functional data in Journal of Multivariate Analysis with S. Banerjee, M. A. Lindquist, and A. Datta.
📄 2024: Published Functional principal component analysis for continuous non-Gaussian, truncated, and discrete functional data in Statistics in Medicine with R. Ghosal, K. Merikangas, and V. Zipunnikov
📰 2024: Published Association Between Electronic Diary–Rated Sleep, Mood, Energy, and Stress With Incident Headache in a Community-Based Sample in Neurology with T. Lateef, A. Leroux, L. Cui, M. Xiao, V. Zipunnikov, and K. Merikangas.
→ Featured by: CNN, National Geographic🎤 2023: Organized and chaired a session at JSM 2023 titled Recent Developments in Methods for Digital Brain Health Data.
📰 2017: Published Re-evaluating the effect of age on physical activity over the lifespan in Preventive Medicine with V. Varma, A. Leroux, J. Di, J. Urbanek, L. Xiao, and V. Zipunnikov.
→ Featured by: TIME