Google Scholar Profile
(* denotes equal contribution)
Under Double-blind Review and Preprints
 B. Zhang and R. Picard. 2022. Personalized stress, mood, and health forecast with physiology data: A dynamical system approach. Submitted.
 Acharyya, R., A. Chattoraj*, B. Zhang*, Das, S. and Štefankovič, D. 2021. Statistical mechanical analysis of neural network pruning. Uncertainty in artificial intelligence (2021), 1988–1997.
 Zhang, B., Zaman, A., Silenzio, V., Kautz, H. and Hoque, E. 2020. The relationships of deteriorating depression and anxiety with longitudinal behavioral changes in google and YouTube use during COVID-19: Observational study. JMIR Mental Health. (Nov. 2020).
Workshops and Posters
 Acharyya, R., A. Chattoraj*, B. Zhang*, Das, S. and Stefankovic, D. 2021. Understanding diversity based neural network pruning in teacher student setup. Neural compression: From information theory to applications – workshop @ ICLR 2021 (2021).
 Acharyya, R., Zhang, B., Chattoraj, A., Das, S. and Stefankovic, D. 2021. Diversity based edge pruning of neural networks using determinantal point processes. Neural compression: From information theory to applications – workshop @ ICLR 2021 (2021).
 Zaman, A., Zhang, B., Silenzio, V., Hoque, E. and Kautz, H. 2021. Individual-level anxiety detection and prediction from longitudinal YouTube and google search engagement logs. Workshop on data for the wellbeing of most vulnerable at ICWSM 2021 (2021).
 Zhang, B., Zaman, A., Acharyya, R., Hoque, E., Silenzio, V. and Kautz, H. 2020. Detecting individuals with depressive disorder from personal google search and YouTube history logs. Workshop on machine learning in public health at NeurIPS 2020 (Oct. 2020).