Tatsuhiro Shimizu

• Received NSK Scholarship (awarded to top four students in Japan for full tuition and living costs)

• First-authored a paper and co-authored another paper on the evaluation and learning of personalized stochastic decisions, which are under the review of one of the top machine learning conferences

• Developed a novel data-driven method to evaluate and improve a combination of personalized decisions from offline data, which yielded up to 10 times more precise evaluation than the baseline methods for real-world data

Grade: GPA 3.96/4.00, Valedictorian Selected Coursework: Causal Inference, Machine Learning, Linear Algebra, Multivariable Analysis, Database, Logic, Statistics, Data Science, Game Theory, Networking Technology & C/C++ Programming

Grade: GPA 3.95/4.00 Selected Coursework: Causal Inference, Machine Learning, Natural Language Processing, Reinforcement Learning, Vector Analysis, Integration on Manifolds, Discrete Mathematics, Differential Equations & Data Structures

• Evaluated the causal effect of the introduction of remote work on the productivity of more than 5000 employees by using Difference-in-Difference (DID) and Synthetic Control Method (SCM) in R and Python

• Analyzed the market and competitors of selected chain stores using data from a comprehensive consumer survey on the lifestyle, consumer behavior, and media exposure by R • Narrowed down advertising target based on the characteristics of the selected ch