About Me

I am a Ph.D. Candidate in Statistics at University of California, Los Angeles. My advisor is Dr. Oscar Hernan Madrid Padilla.

I graduated with Highest Distinction honors from University of California, Berkeley, where I pursued a dual degree in Applied Mathematics and Statistics. Throughout my undergraduate years, I had the privilege of collaborating with Dr. Carl Boettiger as a research intern at rOpenSci and with Dr. Philip B. Stark as a research assistant.

I worked with the Data Science & Statistical Research Team at Nokia Bell Labs as a Machine Learning and AI intern from June to December 2022. In Summer 2023, I worked with Payments Data Science and Engineering Team at Netflix as a Machine Learning Scientist Intern.

I will be joining Google as a Research Data Scientist Intern in the upcoming Summer 2024.

Research

My current research focus is on non-parametric statistics and causal inference. I am also interested in interpretable machine learning, optimization, deep learning and their application in computational biology, social science, and economics.

Papers

S. Ye and O.H.M. Padilla. Non-parametric Quantile Regression via the K-NN Fused Lasso. Journal of Machine Learning Research, Vol. 22, No. 111, 1-38, 2021. PDF. Code.

S. Ye, Y. Chen, and O.H.M. Padilla. 2D Score Based Estimation of Heterogeneous Treatment Effects. PDF. Code. Journal of Causal Inference, Vol. 11, No. 1, 1-26, 2023.

A.K. Glazer, H. Luo, S. Devgon, C. Wang, X. Yao, S. Ye, F. McQuarrie, Z. Li, A. Palma, Q. Wan, W. Gu, A. Sen, Z. Wang, G.D. O’Connell, P.B. Stark. Look Who’s Talking: Gender Differences in Academic Job Talks. PDF. ScienceOpen Research, 2023.

S. Ye, Y. Chen, and O.H.M. Padilla. Causal Effect Estimation via Graph Based Fused Lasso. In Preparation, 2024+.

Teaching

Teaching Assistant

UCLA

• STAT 10: Introduction to Statistical Reasoning (Fall 2020, Winter 2021, Spring 2021, Fall 2021, Winter 2022)
• STAT 13: Introduction to Statistical Methods for Life and Health Sciences (Spring 2022)
• STAT 102C: Introduction to Monte Carlo Methods (Summer 2020)

Reader/Grader

UC Berkeley

• STAT 134: Concepts of Probability (Fall 2016, Spring 2017)
• STAT 151A: Linear Modelling (Spring 2018)
• STAT 153: Introduction to Time Series (Fall 2018)
• STAT 155: Game Theory (Fall 2017, Spring 2019)
• MATH 113: Introduction to Abstract Algebra (Spring 2018)
• MATH 170: Mathematical Methods for Optimization (Spring 2019)

UCLA

• STAT 10: Introduction to Statistical Reasoning (Fall 2019, Winter 2020, Spring 2020)
• STAT 13: Introduction to Statistical Methods for Life and Health Sciences (Fall 2023, Winter 2024)
• STAT 15: Introduction to Data Science (Fall 2022)
• STAT 101B: Introduction to Design and Analysis of Experiment (Spring 2023)

Personal

I love travel and food! Click to view my travel photography gallery and restaurant guide!