Zizheng Guo

Zizheng Guo

Ph.D. Student

Peking University

I am a 4th-year Ph.D. candidate at Peking University, advised by Prof. Yibo Lin. My research interests include data structures, algorithm design and GPU acceleration for combinatorial optimization problems in physical design automation.

Currently, I hold broad interest in topics like signoff timing analysis, power analysis, logic simulation, and performance-driven backend EDA tasks.

My Chinese name is 郭资政.

Interests
  • Data Structure and Algorithms
  • GPU Acceleration using CUDA
  • Reinforcement Learning
Education
  • BSc in Computer Science, 2018-2022

    Peking University

  • PhD Student, 2022-

    Peking University

Recent Publications

(2026). HeteroSTA: A CPU-GPU Heterogeneous Static Timing Analysis Engine with Holistic Industrial Design Support. IEEE/ACM Asia and South Pacific Design Automation Conference (ASPDAC) 2026.

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(2026). HeteroLatch: A CPU-GPU Heterogeneous Latch-Aware Timing Analysis Engine. IEEE/ACM Asia and South Pacific Design Automation Conference (ASPDAC) 2026.

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(2025). IncreGPUSTA: GPU-Accelerated Incremental Static Timing Analysis for Iterative Design Flows. 2025 IEEE/ACM International Conference on Computer-Aided Design (ICCAD).

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(2025). Differentiable Physical Optimization. 2025 IEEE/ACM International Conference on Computer-Aided Design (ICCAD).

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(2025). DiffCCD: Differentiable Concurrent Clock and Data Optimization. 2025 IEEE/ACM International Conference on Computer-Aided Design (ICCAD).

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Recent Posts

Zizheng won Best Poster Award at ACM SIGDA Student Research Forum (SRF) 2026

Zizheng Guo has won the Best Poster Award (Research) in the 2026 ACM SIGDA Student Research Forum at ASP-DAC 2026 (SRF@ASP-DAC 2026), advised by Prof. Yibo Lin, for his outstanding work on Empowering Chip Design Optimization and Verification with CPU-GPU Heterogeneous Computing.

Zizheng's team won the First Place in the 2024 ICCAD CAD contest (Problem C)

Yufan Du and Zizheng Guo have won the first place in the 2024 ICCAD CAD contest, advised by Prof. Yibo Lin, for their outstanding work on Problem C: Scalable Logic Gate Sizing Using ML Techniques and GPU Acceleration.

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