About Me

Rex Chang (Hsi-Jui Chang) studies Electronics and Electrical Engineering at National Yang Ming Chiao Tung University, focusing on edge-cloud collaborative AI systems. I research how edge devices and cloud models can work together efficiently. At the CAD for GREAT Systems Lab, I develop Split-Federated Learning and Parameter-Efficient Fine-Tuning techniques to optimize distributed AI.

My experience spans work at the Intelligent Edge/Fog Computing Alliance Lab and UCSD EEG Lab, where I’ve implemented machine learning models for diverse applications. I aim to pursue a PhD in Computer Science to advance distributed AI architectures that balance computational efficiency, personalization, and privacy.

What I Believe

I envision a future where AI evolves beyond centralized models into personalized assistants that understand individual users deeply. These edge-based assistants will handle privacy-sensitive tasks while collaborating with cloud infrastructure for complex computations. This distributed approach creates AI systems that are not just powerful, but truly personal. My research aims to enable this future by developing efficient edge-cloud collaborative frameworks that respect both computational constraints and user privacy.

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Interests
  • Edge-Cloud Collaborative AI Systems
  • Distributed Machine Learning
  • Resource-Efficient Model Deployment
Education

  • BSc Electronics and Electrical Engineering

    National Yang Ming Chiao Tung University

Experience

  1. Research Assistant

    CAD for GREAT Systems Lab, NYCU

    Research focuses on:

    • SFL (Spilt Federate Learning)
    • LoRA (Low-Rank Adaptation)
    • PEFT (Parameter-Efficient Fine-Tuning)

  2. Research Assistant

    Intelligent Edge/Fog Computing Alliance Lab, NYCU
    Led the development of HyperFedX, a novel framework combining explainable AI with federated learning to prevent free-rider behavior in distributed systems.

  3. Summer Research Intern

    EEG Lab, Swartz Center for Computational Neuroscience, UCSD
    Applied large language models to analyze EEG signals and eye-tracking data from the ZuCo dataset

Education

  1. BSc Electronics and Electrical Engineering

    National Yang Ming Chiao Tung University
    Research focuses include Federated Learning, XAI, and Spilt Federate Learning techniques.