Peilin Shao | AI and Automation in Architecture | Young Researcher Award

Published on by Architecture Engineers

Assist. Prof. Dr. Peilin Shao | AI and Automation in Architecture | Young Researcher Award

Lecturer | Shanxi Datong University | China

Assist. Prof. Dr. Peilin Shao is a Lecturer at Shanxi Datong University specializing in intelligent manufacturing, with academic training in industrial and manufacturing systems engineering as well as mechanical design, manufacturing, and automation. He has been actively involved in advanced research on assembly process modeling, knowledge graph construction, and AI-driven inference, contributing to projects that integrate large language models with manufacturing knowledge systems and supporting intelligent decision-making in complex engineering processes. His work encompasses assembly deviation analysis, process knowledge graph frameworks, and intelligent question-answering methods, with publications in reputable journals such as the Proceedings of the Institution of Mechanical Engineers, Applied Sciences, and the International Journal of Advanced Manufacturing Technology, alongside conference contributions in intelligent networked systems. Dr. Shao has demonstrated research leadership through collaborative projects and scholarly contributions that advance intelligent manufacturing. His research impact includes 8 citations, 5 publications, and an h-index of 1.

Profiles: Scopus | ORCID

Featured Publications

1. Qiao L., Shao P., Zhao H., Huang Z., An assembly deviation calculation method based on surface deviation modeling for circumferential grinding plane. Proc. Inst. Mech. Eng. Part B: J. Eng. Manuf., 2021.

2. Shao P., Huang Z., Qiao L., A novel assembly knowledge graph construction framework enhanced by large language model. Int. J. Adv. Manuf. Technol., 2025, Accepted.

Dr. Peilin Shao’s work advances intelligent manufacturing by integrating large language models with assembly process knowledge, enabling smarter, data-driven engineering decisions. His vision is to accelerate industry transformation through AI-enabled knowledge engineering that fosters sustainable, high-precision, and globally competitive manufacturing practices.

Peng Wang | AI and Automation in Architecture | Editorial Board Member

Published on by Architecture Engineers

Dr. Peng Wang | AI and Automation in Architecture | Editorial Board Member

Researcher | Inspur Group Co.,Ltd | China

Peng Wang is a computer architecture researcher serving as a doctoral researcher at the Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, specializing in GPU rendering optimization, compiler optimization, and microarchitecture-independent performance analysis. He has contributed to multiple high-impact research projects, including the development of RayBench and RenderBench benchmark suites, GPU microarchitecture-independent characteristic profiling tools, and LLVM-based RISC-V vectorization optimizations, demonstrating strong technical leadership in benchmarking, compiler engineering, and heterogeneous computing systems. His research outputs include publications in recognized journals such as Electronics, IEEE Access, and other peer-reviewed venues, along with several patents covering GPU performance optimization, cloud game automation, and feature-analysis methodologies. He has actively supported the scientific community through peer-review service for reputable journals and international conferences, reflecting his growing influence in the fields of computer architecture and intelligent systems. His combined expertise in software-hardware co-design, GPU architecture analysis, and compiler technologies positions him as an emerging leader dedicated to advancing high-performance computing research and innovation.

Profile: ORCID

Featured Publications

1. Wang P., Qu H.L., Latency-Aware and Auto-Migrating Page Tables for ARM NUMA Servers. Electronics, 2025, 14(8), 1685.

2. Wang P., Yu Z.B., LLVM RISC-V RV32X Graphics Extension Support and Characteristics Analysis of Graphics Programs. IEEE Access, 2023, 3291920.

3. Wang P., Yu Z., RenderBench: The CPU Rendering Benchmark Suite Based on Microarchitecture-Independent Characteristics. Electronics, 2023, 12(19), 4153.

4. Wang P., Yu Z., RayBench: An Advanced NVIDIA-Centric GPU Rendering Benchmark Suite for Optimal Performance Analysis. Electronics, 2023, 12(19), 4124.

5. Wang P., Chen Y., Xing M.J., Method for Supporting RISC-V Custom Extension Instructions Based on LLVM. Comput. Syst. Appl., 2021, 31(11), Article 8347.

Peng Wang’s work advances high-performance computing by delivering optimized GPU and CPU rendering benchmark suites, compiler enhancements, and microarchitecture-independent performance tools that strengthen the reliability and efficiency of modern computing systems.He aims to drive global innovation through scalable, energy-efficient, and architecture-aware computing solutions that empower future heterogeneous computing technologies.