Zeyuan (Faradawn) Yang

Zeyuan (Faradawn) Yang.

Researcher in distributed systems and ML.

Education

I obtained my B.S. in Mathematics and M.S. in Computer Science from the University of Chicago. I had the privilege to have Professor Haryadi Gunawi as my advisor. My research focuses on Cloud Storage, Distributed Systems, and Machine Learning for Systems.

Research Experiences

1. "Byte-VAE: Novel Memory-Efficient Image Generation Model." [2023] [pdf]

Vector-Quantize Variational Auto-Encoder (VQ-VAE) suffers from high memory usage due to need of a codebook. We designed an innovative rounding method that eliminates the in-memory codebook, achieving near-zero memory consumption while maintaining identical image generation quality.

2. "Scalability Study of Seagate’s Distributed System." [2022] [pdf]

Seagate Technology's distributed storage faced a latency problem. I used the Analytic and Diagnostic Database subsystem to collect metrics like queue depths and operation latencies. Compiling this data, I created a detailed graph of each component's time consumption, leading to a system upgrade that improved throughput by 20%.

Professional Experiences

Video Creation Hobby

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App Creation Hobby

Published 3 apps that obtained a 4.9 rating with 5.6k downloads on App Store. The latest app won $10,000 at 2024 Ai4Science Hackathon.

  • "Latin Garden" -- a language learning app endorsed by students from Beijing Forestry University.
  • "Rolling Monsters" -- a game that reduces stress for college students.
  • "Flowers Don't Die" -- an educational app that uses voice AI to accelerate code learning.
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