Curriculum Vitae

Education

Ph.D. in Statistics, University of California, Irvine, 2026 (expected)

• Advised by Dr. Babak Shahbaba and Dr. Stephan Mandt
• Expertise: Multimodal Learning, Generative Models, Machine Learning, AI for Science

M.A. in Statistics, Columbia University, 2020

• Advised by Dr. Tian Zheng
• The 2019 Chair’s List Award

B.S. in Statistics, Zhejiang University, 2018

• Chu Kochen Honors College
• Dual Degree: B.A. in English Language and Literature

Work experience

Senior Data Analyst @ Varo Bank, 11/2021 - 08/2022

Machine Learning & Experimental Design

• Improved customized customer retention strategies by modeling customer behavior with Markov chains
• Accelerated the customer acquisition process by 14+% after designing and running an experiment to test the effect of the color changing in the email advertisement, and evaluated A/B Testing results in Tableau
• Standardized the SQL-to-Tableau pipeline, the new ETL and analysis process are widely used in the company

Data Analyst @ YipitData, 09/2020 - 10/2021

Data Science Modeling & Business Analytics

• Increased the revenue by 37+% after creating and presenting a tree-based housing price estimation model, and organized bi-weekly meetings with business partners to assess the client needs and research potential features
• Launched web scraping systems and the monthly reporting system by designing DAGs using AirFlow

Technical Skills

Coding

• Languages: Python (PyTorch, Pandas, Numpy, scikit-learn)
• Databases: PostgreSQL, MySQL, Redshift, Athena
• Software: Tableau, AirFlow, R (dplyr, ggplot2, shiny)

Algorithms

• Generative Models: Diffusion Models, VAE, GAN, Normalizing-Flows
• Artificial intelligence: Multimodal Learning, Representation Learning, RNN, CNN, Contrastive Learning
• AI for Science: Neuroscience, Climate Analysis, Public Health
• Statistical Learning: Random Forest, Decision Trees, Regression, Boosting, PCA, SVM, Clustering, MCMC

Publications and Preprints

Unity by Diversity: Improved Representation Learning in Multimodal VAEs

Sutter T. M., Meng Y., Fortin N., Vogt J. E., Shahbaba B., Mandt S. (2024). "Unity by Diversity: Improved Representation Learning in Multimodal VAEs" arXiv Preprint arXiv: 2403.05300, 2024.

Scaling Up Bayesian Neural Networks with Neural Networks

Moslemi Z., Meng Y., Lan S., Shahbaba B. (2023). "Scaling Up Bayesian Neural Networks with Neural Networks." arXiv preprint: arXiv: 2312.11799, 2023

Log-rank-type tests for equality of distributions in high-dimensional spaces

Liu L., Meng Y., Wu X., Ying Z., Zheng T. (2022). "Log-rank-type tests for equality of distributions in high-dimensional spaces." Journal of Computational and Graphical Statistics 31 (4), 1384-1396.

Teaching

Univerity of California, Irvine

• STATS 212 – Statistical Methods III: Methods for Correlated Data, TA
• STATS 210C - Statistical Methods III: Longitudinal Data, TA
• STATS 67 – Introduction to Probability and Statistics for Computer Science, TA
• STATS 7 – Basic Statistics, TA
• STATS 210P – Statistical Methods I, TA
• STATS 120A – Introduction to Probability and Statistics I, Grader

Columbia University

• GU4234/ GR5234 – Sample Survey, Grader
• GU4222/ GR5222 - Nonparametric Statistics, Grader