Mohammad Ghasempour
Postdoctoral Researcher at Umeå School of Business, Economics, and Statistics (USBE)
Umeå, Sweden
Summary
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Senior🎓
Top SchoolMohammad Ghasempour is a postdoctoral researcher at Umeå University with eight years of experience bridging rigorous statistical theory and practical machine learning applications. He holds a PhD in Statistics and an MS in Stochastic Analysis, and his work centers on causal inference, semiparametric models, and asymptotic theory with direct applications in public health. Mohammad has developed novel methods—such as CNN-based doubly robust estimators and an R package DNNcausal—and published in venues like JCGS, demonstrating a rare blend of deep mathematical expertise and hands-on statistical programming. He also brings industry experience as a machine learning consultant and data analyst, having deployed scalable workflows with SparkR, Keras, and TensorFlow. Colleagues describe him as someone who consistently translates theoretical advances into reproducible, scalable solutions for real-world data challenges.
8 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy (PhD) Mathematics, Doctor of Philosophy (PhD) Mathematics at Tarbiat Modares UniversityDoctor of Philosophy - PhD Statistics, Doctor of Philosophy - PhD Statistics at Umeå School of Business, Economics, and Statistics (USBE)Master of Science (MS) Mathematics, Master of Science (MS) Mathematics at Sharif University of Technology
Github Skills (5)
r-package8
fomantic-ui1
shiny1
htmlwidgets1
visualize1
Programming languages (2)
Github contributions (5)
stat4reg/SDRcausal
Jun 2020 - Oct 2021
SDRcausal is a R Package that provides semiparametric estimators.
Contributions:45 commits, 3 PRs, 14 pushes in 1 year 4 months
r-packageestimators
stat4reg/DNNcausal
May 2022 - Feb 2023
Contributions:17 commits, 8 pushes in 9 months
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