About Me

Hello! I’m Chengao SHI (施塍驁), a PhD candidate in Computer Engineering at the Hong Kong University of Science and Technology (HKUST). My research bridges advanced machine learning and architecture simulation—most recently focusing on innovative methods for memory workload synthesis and high-speed trace reduction. One of my papers, “[Memory Workload Synthesis Using Generative AI],” received the Best Paper Award at MEMSYS 2023.

Background & Evolving Interests

I’m excited to combine knowledge from these two seemingly distinctive fields into next-generation HPC solutions. By leveraging insights from ML, I aim to reduce simulation time for large-scale workloads, thus enabling faster hardware core development and more accurate microarchitectural exploration.

Other Experiences and Hobbies

Before HKUST, I spent years in Xi’an, China, completing my BSc in computer science (honored program) at Xi’an Jiaotong University. Beyond academia, I enjoy:

• Teaching and Mentoring: I’ve served as a teaching assistant in computer architecture and stochastic process, helping students decode complex concepts.
  
• Travel: I’ve lived in Hong Kong, China Mainland, US, and Canada, and visited 10+ countries.
• Climbing: Whenever possible, I like to build my finger strength and unwind by trying new bouldering problems at the local gyms.

If you’re interested in collaborations—whether in next-gen memory system design or advanced ML for HPC—don’t hesitate to reach out: cshiai@connect.ust.hk.