Simon Mak

Assistant Professor

Department of Statistical Science

Duke University

Office: Old Chemistry 112A

E-mail: sm769[at]duke.edu

Google Scholar, Curriculum Vitae

Education

  • Ph.D. in Industrial Engineering (2018), Georgia Institute of Technology

  • M.Sc. in Statistics (2018), Georgia Institute of Technology

  • B.Sc. in Statistics and Actuarial Science (2013), Simon Fraser University

About me

I am an Assistant Professor in the Department of Statistical Science at Duke University. Prior to Duke, I was a Postdoctoral Fellow at the Stewart School of Industrial & Systems Engineering at Georgia Tech.

My research involves integrating domain knowledge (e.g., scientific theories, mechanistic models, financial principles) as prior information for statistical inference and prediction. This gives a holistic framework for interpretable statistical learning, providing a principled way for scientists to validate theories from data, and for statisticians to integrate scientific knowledge. My research tackles methodological, theoretical, and algorithmic challenges in this integration. This involves building probabilistic models on complex objects (e.g., functions, manifolds, networks), and developing efficient algorithms and data collection methods for model training. Current research is motivated from ongoing projects in nuclear physics, engineering, and finance.

Recent news

  • Jan 2021: Dhruv & Lavonne were among the 15 finalists in the Undergraduate Research Poster Fair of Research Week, with Dhruv placing 2nd place overall. Congrats Dhruv & Lavonne!

  • Nov 2020: Dhruv received 3rd place at the Duke ECE Independent Study Poster Competition, for his poster "Structured Initialization for Matrix Completion". Congrats Dhruv!

  • Nov 2020: Jialei won the 2020 INFORMS QSR Best Student Paper Award, for his paper "Adaptive design for Gaussian process regression under censoring". Congrats Jialei!

  • Nov 2020: Zhehui was a runner-up for the 2020 INFORMS QSR Best Student Paper Award, for his paper "A hierarchical Expected Improvement method for Bayesian optimization". Congrats Zhehui!

  • Aug 2020: Jialei was a runner-up for the 2020 ASA Biometrics Best Student Paper Award, for his paper "Function-on-function kriging, with applications to 3D printing of aortic tissues". Congrats Jialei!

  • Aug 2020: Zhehui was a runner-up for the 2020 ASA SBSS Best Student Paper Award, for his paper "A hierarchical Expected Improvement method for Bayesian optimization". Congrats Zhehui!