Shinpei Nakamura-Sakai

Shinpei Nakamura-Sakai

Ph.D. Student in S&DS at Yale

Shinpei Nakamura-Sakai

I am a Ph.D. student in Statistics and Data Science at Yale University. My research interest lies in causal inference, synthetic data generation, and machine learning application. In application, I enjoy applying theory to solve problems related to finance, medicine, social science, and sports. I am very fortunate to be advised by Professor Jas Sekhon and Professor Laura Forastiere.

Research

(*) indicates equal contribution and exchangeable

Synthetic Data and Differential Privacy

  • Enhancing Collaborative Medical Outcomes through Private Synthetic Hypercube Augmentation: PriSHA
    Shinpei Nakamura-Sakai, Dennis Shung, Jasjeet Sekhon
    Conference on Health, Inference, and Learning (CHIL), 2024, PMLR
    AAAI SSS Clinical FMs, 2024, Traditional Track (Spotlight, top 10 submission)
    Paper
  • Supervised generative optimization approach for tabular data
    Shinpei Nakamura-Sakai*, Fadi Hamad*, Saheed Obitayo, Vamsi K. Potluru
    Proceedings of the ACM International Conference on AI in Finance (ICAIF), 2023, (Oral, top 20.5%)
    Paper
    • Winner of 2nd Place at JPMorgan Chase Global Hackathon

Causal Inference

  • Estimating causal effects of interventions altering social connectivity patterns under network interference
    Shinpei Nakamura-Sakai, Laura Forastiere
    Poster, Award, Media, News
    • Winner of the statistical significance award at Joint Statistical Meeting (JSM), 2023

Sports Analytics

  • Estimating the age conditioned average treatment effects curves: An application on assessing load-management strategies in the NBA
    Shinpei Nakamura-Sakai, Laura Forastiere, Brian Macdonald
    arXiv, Award1, Award2, Media, News
    • Winner of the best poster award at New England Symposium on Statistics in Sports (NESSIS), 2023
    • Winner of the best poster award at UConn Sports Analytics Symposium (UCSAS), 2022

Healthcare and Social Sciences

  • Validation of an Electronic Health Record–Based Machine Learning Model Compared With Clinical Risk Scores for Gastrointestinal Bleeding
    Dennis L Shung, Colleen E Chan, Kisung You, Shinpei Nakamura, Theo Saarinen, Neil S Zheng, Michael Simonov, Darrick K Li, Cynthia Tsay, Yuki Kawamura, Matthew Shen, Allen Hsiao, Jasjeet Sekhon, Loren Laine
    Gastroenterology, 2024
    Paper

  • GUTGPT: NOVEL LARGE LANGUAGE MODEL PIPELINE OUTPERFORMS OTHER LARGE LANGUAGE MODELS IN ACCURACY AND SIMILARITY TO INTERNATIONAL EXPERTS FOR GUIDELINE RECOMMENDED MANAGEMENT OF PATIENTS WITH UPPER GASTROINTESTINAL BLEEDING
    Mauro Giuffrè, Kisung You, Sunny Chung, Simone Kresevic, Colleen Chan, Theo Saarinen, Shinpei Nakamura, Loren Laine, Joseph JY Sung, Guadalupe Garcia-Tsao, Ian Gralnek, Alan N. Barkun, Jasjeet Sekhon, Dennis Shung
    Gastroenterology, 2024
    Paper

  • COVID-19 Vaccine Perceptions in the Initial Phases of US Vaccine Roll-out: An Observational Study on Reddit
    N Kumar, I Corpus, M Hans, N Harle, N Yang, C McDonald, S Nakamura-Sakai, …
    BMC Public Health, 2022
    Paper

  • News Events and Their Relationship With US Vape Sales: An Interrupted Time Series Analysis
    Kamila Janmohamed, Shinpei Nakamura-Sakai, Abdul-Nasah Soale, Laura Forastiere, Navin Kumar
    BMC Public Health, 2021
    Paper

  • Longitudinal Analysis of the Determinants of Life Expectancy and Healthy Life Expectancy: A Causal Approach
    Rohan Aanegola, Shinpei Nakamura-Sakai, Navin Kumar
    Healthcare Analytics, 2021
    Paper

Employment

Media Appearance

  • LeBron James Has Done Everything in the NBA. Except This.
    THE WALL STREET JOURNAL
    Article

  • Alumni Spotlight
    The University of Chicago, Department of Statistics
    Article

Teaching

Yale

  • Teaching Fellow: Data Analysis (S&DS 361/661), Instructor: Brian Macdonald, Spring 2023
  • Teaching Fellow: Statistical Case Studies (S&DS 425), Instructor: Brian Macdonald, Fall 2022, Fall 2021
  • Teaching Fellow: Applied Machine Learning and Causal Inference (S&DS 317/517), Instructor: Jas Sekhon, Spring 2022

Universidad Nacional Autónoma de México (UNAM)

  • Adjunct Professor: Advanced Probability, Spring 2020
  • Teaching Assistant: Stochastic Processes, Spring 2017
  • Teaching Assistant: Risk Theory, Fall 2016
  • Workshop Instructor: Construction and Evaluation of Actuarial Models Exam C, Fall 2016

The University of Chicago

  • Workshop Instructor: Introduction to Deep Learning, Summer 2019