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Hi, I’m Haolan, a master student at Yale University and currently working as a research assistant at Yale Computer Science under the supervision of Prof. Rex Ying, working on graphs and fact checking (NLP).

Prior to Yale, I received my bachelor’s degrees in Computer Science and Financial Engineering from Sichuan University China, where I did projects and research in computer vision, computational finance.

I am looking for full-time positions as a machine learning engineer, data scientist, data analyst, data engineer, or in quantitative finance and related fields. I am open to opportunities in both industry and academia.

Several of my projects are listed in the Portfolio section.

Please feel free to reach out to me via email: haolan.zuo [at] gmail [dot] com or LinkedIn.

Education

• M.S. in Computer Science, Yale University, 2024
• B.S. in Computer Science, Sichuan University, 2023
• B.S. in Fiancial Engineering, Sichuan University, 2023

Professional Experience

• Machine Learning Engineer Intern, Meituan, Summer 2023
  • Division: Mobike
  • Project: Graph nerual networks for bike station recommendations
    • Built data ETL pipeline for large-scale graph dataset from spatio-temporal data using PySpark and SQLs
    • Improved overall profit by 7% by building GNNs for bike station recommendations; achived 72% ACC@500 in component-specific tests
    • Deployed the model as a service using Docker and Flask via RESTful APIs
• Machine Learning Engineer Intern, Johns Hopkins University, Summer 2022
  • Employer: The Johns Hopkins Center for Bioengineering Innovation and Design (CBID)
  • Project: Wearable device applications for deformity spine patients
    • Developed iOS and watchOS applications for inertial sensor data collection and synchronization using Swift
    • Implemented LSTM prediction model for human activity recognition using Tensorflow
• Data Scientist Extern, Yale Biotech Club - Bexorg Inc., Fall 2023
  • Project: Temporal data mining for brain cultivation experiments
    • Enhanced high-frequency signal data integrity via data cleansing, feature selection, and downsampling using Pandas
    • Uncovered causal relationships between variables using scikit-learn for random forest, mutual information, and Bayesian networks

Research and Teaching Experience

• Research Assistant, Yale University, Fall 2023 - Present
  • Advisor: Prof. Rex Ying
  • Research orientation: Graph Foundation Model, Graph Transformer, Information Bottleneck, Trustworthy Deep Learning
  • Results have been accepted by ICML 2024 and submitted to NeurIPS 2024
• Teaching Assistant, Yale University, Spring 2024
  • Instructor: Prof. Alex Wong
  • Course: CPSC 381/581, Introduction to Machine Learning
  • Topics: Stochastic Gradient Descent, Kernel Support Vector Machine, Principal Components Analysis, Neural Networks