CV

Tong Zhu

toz015@ucla.edu
https://toz015.github.io
Fremont, CA, USA, , US
Google Scholar ORCID GitHub

Summary

Currently employed at UCLA. A PhD Candidate in Biostatistics.

Education

  • Doctor of Philosophy (PhD) in Biostatistics
    University of California, Los Angeles
    Courses: Uncertainty in LLMs, Agent-based AI
  • Master of Science in Computer Science
    2024-05-01
    Northeastern University
    GPA: 4.0
    Courses: Algorithm, Distributed Database
  • Master of Science in Statistics and Operations Research
    2020-06-01
    University of North Carolina at Chapel Hill
    Courses: Applied Statistics, Machine Learning, Time Series Forecasting

Work Experience

  • Software Engineer Intern
    2024-06-01 - 2024-08-01
    Amazon
    • Developed key features for Amazon B2B in AWS platform to automate event-driven applications using EventBridge
    • Implemented enhancements in the Visibility Service using Java, JavaScript and TypeScript, improving real-time tracking and monitoring of important business transactions across the platform
    • Conducted integration tests for all Outbound services and events, ensuring smooth and error-free deployment
    • Designed and tested dashboards using CloudWatch to monitor service performance metrics
  • Data Scientist
    2021-02-01 - 2022-08-01
    ByteDance Ltd.
    • Collaborated with cross-function team to deploy dynamic subscription tool to improve customer experience in platform
    • Verified product feasibility and deployed XGBoost model to select the important indicators for customers to help design product features
    • Applied interrupted time series to estimate the potential revenue impact, and evaluate the risk of restricting creator's quotes strategy in advance
    • Conducted attribution analysis to evaluate marketing campaign performance which provided powerful evidence to spur on product marketing
  • Data Scientist
    2020-08-01 - 2020-12-01
    Blingby
    • Built data ETL pipelines through Apache Spark to transform raw data into features by combining business sense and statistical knowledge
    • Developed, maintained web-based dashboards with Tableau to update daily data analysis report, which increased 20% daily work efficiency
  • Machine Learning Intern
    2020-06-01 - 2020-08-01
    TouchSuite
    • Queried and cleaned terabyte-sized order data from Azure SQL using pyodbc
    • Conducted online analytical processing (OLAP) to display critical sales performance from different dimensions
    • Developed item-based approaches to handle cold-start problems and tuned the model hyper-parameters through SparkML cross-evaluation toolbox which reduced root mean square errors by 10%

Skills

Programming Languages

  • Python
  • R
  • Java
  • JavaScript
  • SQL

Tools and Platforms

  • MySQL
  • Tableau
  • AWS
  • Spark

Publications

  • Incentivizing Truthful Language Models via Peer Elicitation Games
    2025
    NeurIPS 2025
    This paper introduces Peer Elicitation Games (PEG), a training-free, game-theoretic framework for aligning LLMs.
    View Publication

Teaching

  • Biostat 203A
    2025
    University of California, Los Angeles, Biostatistics Department
    Role: TA
    Introduction to Data Management and Statistical Computing
  • Biostat 201
    2025
    University of California, Los Angeles, Biostatistics Department
    Role: TA
    Topics in Applied Regression

Portfolio

  • Portfolio item number 1
    Portfolio
    Short description of portfolio item number 1
    View Project

Interests

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