Yuhua Zheng

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Zhejiang University, EE

I am an undergraduate student majoring in Information Engineering at the College of Information Science and Electronic Engineering, Zhejiang University, and was selected for the 2024 cohort of the Shannon Excellence Program. I maintain a GPA of 4.78/5.00, ranking among the top three students in my major.

My research interests lie in Efficient AI and AI infrastructure. I am currently working on the optimization and deployment of edge models, as well as machine learning compilers. More broadly, I am interested in the co-design of algorithms, compiler and runtime systems, and hardware for efficient AI computing.

I have a cross-disciplinary background in computer science and electrical engineering, with experience in software development, embedded systems, and hardware-aware optimization. This background helps me approach AI systems from both algorithmic and system-level perspectives.

Outside research, I enjoy playing table tennis and value the focus, persistence, and teamwork that the sport brings.

education

Zhejiang University

B.Eng. in Information Engineering

College of Information Science and Electronic Engineering

2024 Cohort, Shannon Excellence Program · 2024 – 2028

GPA: 4.78 / 5.00 Top 3 in major

awards

Zhejiang Provincial Government Scholarship 2025
Second Prize, National Undergraduate Mathematics Competition (CMC) 2025
Second Prize, Zhejiang Provincial Physics Competition for College Students 2025
Second Prize, Zhejiang Provincial Advanced Mathematics Competition 2024

news

Mar 19, 2026 Our paper, LVOmniBench: Pioneering Long Audio-Video Understanding Evaluation for Omnimodal LLMs, is now available on arXiv.
Mar 12, 2026 Our paper, MobileKernelBench: Can LLMs Write Efficient Kernels for Mobile Devices?, is now available on arXiv.
Feb 05, 2026 Personal website launched! Built with al-folio template on Jekyll.

selected publications

  1. LVOmniBench: Pioneering Long Audio-Video Understanding Evaluation for Omnimodal LLMs
    Keda Tao, Yuhua Zheng, Jia Xu, and 13 more authors
    arXiv preprint arXiv:2603.19217, 2026
  2. MobileKernelBench: Can LLMs Write Efficient Kernels for Mobile Devices?
    Xingze Zou, Jing Wang, Yuhua Zheng, and 8 more authors
    arXiv preprint arXiv:2603.11935, 2026