MAHBUBUL HASAN
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My doctoral research focuses on the nexus of applied statistics and deep learning with differential privacy. In the current Ph.D. project funded by National Science Foundation(NSF), I am working to develop a deep learning model which can objectively quantify clinical trials' outcomes and cognitive assessment. In another recent Ph.D. project funded by the National Institute of Health(NIH), I have looked into how pregnancy(yes/no) effect the DNAm of the pregnancy and birth using survival analysis/linear regression. I aim to build state-of-the-art statistical machine learning and deep learning models to solve issues from the internet of things(IoT), social science, learning science, public health, and consumer behavior.

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Research Themes:
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Statistical ML, Deep Learning with Differential Privacy(DP), Others:



Research papers: 

AI and Cognitive Diagnostic Modeling:


Research papers: 


Applied Statistics, Bayesian Inference,  and Biostatistics:


Research papers: 



Consumer Behavior, and AI in Marketing:  ​

Research papers: ​





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2017 & Beyond:  


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