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Education

Experience

  • 2024.01 - 2024.10
    Research Assistant
    The Pennsylvania State University, United States
    Explored graph-generation-based strategies to address the Out-of-Distribution (OOD) problem in machine learning on graph-structured data.
    • Advised by Prof. Lu Lin.
  • 2023.03 - 2023.09
    Master Thesis
    Distributed Computing Group (DISCO), ETH Zurich, Switzerland
    Designed and implemented three diffusion models for sketch graph generation.
    • Advised by Prof. Pascal Frossard and Prof. Roger Wattenhofer.
  • 2022.09 - 2023.03
    Engineering Internship focusing on deep learning
    Logitech, Lausanne, Switzerland
    Designed and implemented a non-parallel low-latency real-time any-to-any voice conversion system.
    • Advised by Dr. Milos Cernak.
  • 2022.07 - 2022.10
    Research Assistant
    Signal Processing Laboratory (LTS4), EPFL, Switzerland
    Designed and implemented the conditional denoising process for the graph discrete denoising diffusion model.
    • Advised by Prof. Pascal Frossard.
  • 2021.02 - 2022.01
    Master Semester Projects
    Laboratory for Information and Inference Systems (LIONS), EPFL, Switzerland
    Explored regularization of polynomial networks for image recognition.
    • Advised by Prof. Grigorios Chrysos and Prof. Volkan Cevher.

Honors and awards

Certificates

Logitech Internship Certificate
Logitech Europe SA 2023-02-26

Skills

Deep Learning Libraries
PyTorch
PyG (PyTorch Geometric)
TensorFlow
Graph Analysis
NetworkX

Languages

Chinese
Native speaker
English
Proficient

Interests

Graph Neural Networks (GNNs)
Graph Generation
Time Series Analysis