王翕职务:副教授
单位: 电话: 出生年月: 邮箱:xi.wang@seu.edu.cn 学历:博士 地址:国家集成电路自动化设计技术创新中心401 职称:副教授
  • 基本信息
  • 教学授课
  • 科学研究
  • 荣誉奖励
  • 团队及招生情况
个人简介
王翕博士,现suncitygroup太阳成集团副教授,博导,德克萨斯理工大学计算机学院客座研究科学家 (Adjunct Research Scientist), 研究方向专注于计算机体系结构和新一代EDA工具。于2020年在美国德克萨斯理工大学取得计算机科学博士学位, 之后跟随图灵奖得主RISC-V开源架构创始人,David A. Patterson 院士,在清华大学任博士后研究员。 拥有超过9年RISC-V体系结构设计经验,含括处理器设计,新一代EDA工具,大语言模型,高性能计算,并行计算,编译器,二进制转译,敏捷开发工具链等领域的科研工作。参与/主持多项由美国国家自然科学基金,美国国防部,美国能源部,深圳市科创委, RISC-V国际基金会,英特尔,亚马逊,大众中国资助的科研项目,项目经费累计1.55亿人民币。全球首创基于AI大语言模型的处理器芯片自动化设计和验证平台ChatCPU。科研成果多次在 DAC, ICCAD, DATE, IPDPS, HPDC, ICPP, JSSC, TC等国际顶级会议和期刊上累计发表50余篇,其中CCF-A类总计18篇。并荣获EDA顶会DAC 2024年度最佳论文提名(在1456篇投稿中排名前5,东南大学首次)IPDPS 2021年度最佳论文奖,ISSCC 2023 Code-a-Chip芯片设计奖第一名,CSAW 2023年度国际AI硬件攻击挑战赛冠军等国际学术会议奖项。多项科研成果被RISC-V国际基金会, 美光科技, 大众, 英特尔, 美光等机构和企业采纳使用。
教育经历



- 2016 - 2020:美国德克萨斯理工大学 (Texas Tech University),计算机科学(博士)

- 2014 - 2016:美国德克萨斯理工大学 (Texas Tech University),计算机科学(硕士)


工作经历
  • 2024.4 - 至今:  东南大学,suncitygroup太阳成集团,副教授

  • 2024.1 - 2024.4:国家集成电路自动化设计技术创新中心,大模型项目组,项目主管

  • 2023.6 - 2024.1:清华大学,深圳国际研究生院,项目研究员

  • 2021.5 - 2023.5:清华大学,深圳国际研究生院,博士后研究员

  • 2018.5 - 2018.8:美国西北太平洋国家实验室(Pacific Northwest National Laboratory),High-Performance Computing Department,博士实习(Ph.D. Intern)

  • 2017.5 - 2017.8:美国阿贡国家实验室(Argonne National Laboratory),Mathematics and Computer Science Division ,科研助理(Research Aide)

  • 2016.5 - 2016.8:美光科技MicronTechnology, Inc.Advanced Memory System Group,编译器工程师(Compiler Engineer)


讲授课程
教学研究
出版物
研究领域或方向

研究专注于AI+IC以及AI+EDA方向,包括:数字芯片自动化设计验证大模型,智能EDA,处理器设计,计算机体系结构,大语言模型,编译器,二进制转译,高性能计算,并行计算,敏捷开发工具链等方向。

研究项目
研究成果


论文发表

  • Jia Xiong, Runkai Li, Haowen Fang, Cheng Ni, Ziran Zhu, Nan Guan, Zhe Jiang and Xi Wang, ParetoPilot:Global Optimization Reasoning on HLS Design Space Exploration with LLMs, IEEE DAC 2026

  • Lik Tung Fu, Jie Zhou, Shaokai Ren, Mengli Zhang, Nan Guan, Zhe Jiang and Xi Wang, ChatSVA: Bridging SVA Generations for Hardware Verification via Task-specific LLMsIEEE DAC 2026

  • Jieran Cui, Zhengkai Wen, Haowen Fang, Yinan Zhu, Jia Xiong, Cheng Ni, Mingchi Zhang, Nan Guan and Xi Wang, ZK-Tracer: A High-Performance Heterogeneous Accelerator for Zero-Knowledge VM Trace GenerationIEEE DAC 2026

  • Qiyuan Chen, Fuxing Huang, Lixin Chen, Hao Wu, Hao Gu, Xiqiong Bai, Xi Wang and Ziran Zhu, Toward True-3D Timing-Driven Analytical Global Placement for Mixed-Size Face-to-Face 3D ICs, IEEE DAC 2026

  • Jianmin Ye, Yifan Zhang, Tianyang Liu, Qi Tian, Shengchu Su, Lik Tung Fu, Nan Guan, Zhe Jiang and Xi Wang, LLM-Aided Reference Model Design for Agile Hardware Verification, IEEE DAC 2026

  • Yuchen Hu, Jialin Sun, Yushu Du, Renshuang Jiang, Ning Wang, Weiwei Shan, Xinwei Fang, Xi Wang, Nan Guan and Zhe Jiang, Beyond Fuzzer Islands: CPU Fuzzing via Smart Coordination, IEEE DAC 2026

  • Ning Wang, Zichong Deng, Bingkun Yao, Jie Zhou, Yuchen Hu, Xi Wang, Zhe Jiang and Nan Guan, CircuitDiff: Bridging Netlist Knowledge with RTL based on Graph Denoising Diffusion, IEEE DAC 2026

  • Junhao Ye, Dingrong Pan, Hanyuan Liu, Yuchen Hu, Jie Zhou, Ke Xu, Xinwei Fang, Xi Wang, Nan Guan and Zhe Jiang, UVMarvel: an Automated LLM-aided UVM Machine for Subsytem-level RTL Verification, IEEE DAC 2026

  • Ning Wang, Bingkun Yao, Jie Zhou, Yuchen Hu, Xi Wang, Zhe Jiang and Nan Guan, Insights from Verification: Training a Verilog Generation LLM using Reinforcement Learning with Testbench Feedback, IEEE DAC 2026

  • Wan, Gwok-Waa and Su, Shengchu and Zhang, Jingyi and Wong, Sam Zaak and Xing, Mengnv and Ji, Lei and Jiang, Zhe and Wang, Xi and Yang, Jun, ChatTest: Coverage-Enhanced Testbench Generation for Agile Hardware Verification with LLMs, IEEE DATE 2026.

  • Changwen Xing, SamZaak Wong, Xinlai Wan, Yanfeng Lu, Mengli Zhang, Zebin Ma, Lei Qi, Zhengxiong Li, Nan Guan, Zhe Jiang, Xi Wang, Jun Yang, ChipMind: Retrieval-Augmented Reasoning for Long-Context Circuit Design Specifications, AAAI 2026

  • Chenxu Niu, Wei Zhang, Jie Li, Yongjian Zhao, Tongyang Wang, Xi Wang, Yong Chen, TokenPowerBench: Benchmarking the Power Consumption of LLM Inference, AAAI 2026

  • Gwok-Waa Wan, Shengchu Su, Ruihu Wang, Qixiang Chen, Sam-Zaak Wong, Mengnv Xing, Hefei Feng, Yubo Wang, Yinan Zhu, Jingyi Zhang, Jianmin Ye, Xinlai Wan, Tao Ni, Qiang Xu, Nan Guan, Zhe Jiang, Xi Wang, Yang Jun, FIXME: Towards End-to-End Benchmarking of LLM-Aided Design Verification, AAAI 2026

  • Qiang Xu, Leon Stok, Rolf Drechsler, Xi Wang, Grace Li Zhang, Igor L Markov, Revolution or Hype? Seeking the Limits of Large Models in Hardware Design, IEEE ICCAD 2025.

  • Chenchen Zhao, Zhengyuan Shi, Xiangyu Wen, Chengjie Liu, Yi Liu, Yunhao Zhou, Yuxiang Zhao, Hefei Feng, Yinan Zhu, Gwok-Waa Wan, Xin Cheng, Weiyu Chen, Yongqi Fu, Chujie Chen, Chenhao Xue, Ying Wang, Yibo Lin, Jun Yang, Ning Xu, Xi Wang, Qiang Xu, MMCircuitEval: A Comprehensive Multimodal Circuit-Focused Benchmark for Evaluating LLMs, IEEE ICCAD 2025.

  • Junhao Ye, Yuchen Hu, Ke Xu, Dingrong Pan, Qichun Chen, Jie Zhou, Shuai Zhao, Xinwei Fang, Xi Wang, Nan Guan, Zhe Jiang, From Concept to Practice: an Automated LLM-aided UVM Machine for RTL Verification, IEEE ICCAD 2025.

  • Bingkun Yao, Ning Wang, Jie Zhou, Xi Wang, Hong Gao, Zhe Jiang, Nan Guan, Xi Wang, Nan Guan, Zhe Jiang, Location is Key: Leveraging LLM for Functional Bug Localization in Verilog Design, IEEE DAC 2025

  • Yuchen Hu, Junhao Ye, Ke Xu, Jialin Sun, Shiyue Zhang, Xinyao Jiao, Dingrong Pan, Jie Zhou, Ning Wang, Weiwei Shan, Xinwei Fang, Xi Wang, Nan Guan, Zhe Jiang, Xi Wang, Nan Guan, Zhe Jiang, UVLLM: An Automated Universal RTL Verification Framework Using LLMs, IEEE DAC 2025.

  • Juxin Niu, Xiangfeng Liu, Dan Niu, Xi Wang, Zhe Jiang, Nan Guan, ReChisel: Effective Automatic Chisel Code Generation by LLM with Reflection, IEEE DAC 2025.

  • Ning Wang, Bingkun Yao, Jie Zhou, Yuchen Hu, Xi Wang, Zhe Jiang, Nan Guan, Large Language Model for Verilog Generation with Code-Structure-Guided Reinforcement Learning, IEEE ICLAD 2025.

  • Ning Wang, Bingkun Yao, Jie Zhou, Yuchen Hu, Xi Wang, Zhe Jiang, Nan Guan, VeriDebug: A Unified LLM for Verilog Debugging via Contrastive Embedding and Guided Correction, IEEE ICLAD 2025.

  • Zeju Li, Changran Xu, Zhengyuan Shi, Zedong Peng, Yi Liu, Yunhao Zhou, Lingfeng Zhou, Chengyu Ma, Jianyuan Zhong, Xi Wang, Jieru Zhao, Zhufei Chu, Xiaoyan Yang, Qiang Xu, DeepCircuitX: A Comprehensive Repository-Level Dataset for RTL Code Understanding, Generation, and PPA Analysis, IEEE ICLAD 2025.

  • Yibo Rui, Yuanhang Li, Rui Wang, Ruiqi Chen, Yanxiang Zhu, Zhixiong Di, Xi Wang, Ming Ling, ChaTCL: LLM-Based Multi-Agent RAG Framework for TCL Script Generation, IEEE ISEDA 2025.

  • J Li, SZ Wong, GW Wan, X Wang, J Yang, EDA-Debugger: An LLM-based Framework for Automated EDA Runtime Issue Resolution,IEEE ISQED 2025.

  • Ke Xu, Jialin Sun, Yuchen Hu, Xinwei Fang, Weiwei Shan, Xi Wang and Zhe Jiang, MEIC: Re-thinking RTL Debug Automation using LLMs, IEEE ICCAD 2024.

  • Xi WangGwok-Waa Wan, Sam-Zaak Wong, Layton Zhang, Tianyang Liu, Qi Tian and Jianmin Ye, ChatCPU: An Agile CPU Design & Verification Platform with LLM, IEEE DAC, Best Paper Award Nominee (5/1456),  2024

  • Gwok-Waa Wan, Sam-Zaak Wong, Xi Wang, Jailbreaking Pre-trained Large Language Models Towards Hardware Vulnerability Insertion Ability, ACM/IEEE GLVLSI 2024.

  • Tianyang Liu, Qi Tian, Jianmin Ye, LikTung Fu, Shengchu Su, Junyan Li, Gwok-Waa Wan, Layton Zhang, Sam-Zaak Wong, Xi Wang, and Jun YangChatChisel: Enabling Agile Hardware Design with Large Language ModelsISEDA 2024.

  • Yuxuan Du, Zhengguo Shen, Junyi Qian, Chengjun Wu, Weiwei Shan, and Xi Wang, DSC-TRCP: Dynamically Self-calibrating Tunable Replica Critical Paths Based Timing Monitoring for Variation Resilient Circuits, IEEE JSSC, 2024. 

  • Cai Li, Haochang Zhi, Kaiyue Yang, Junyi Qian, Zhihao Yan, Lixuan Zhu, Chao Chen, Weiwei Shan, and Xi Wang, A 0.61μW Fully-Integrated Keyword-Spotting ASIC with Real-Point Serial FFT-Based MFCC and Temporal Depthwise Separable CNN, IEEE JSSC, 2023.

  • Xi Wang, John D. Leidel, Brody Williams, Alan Ehret, Miguel Mark, Michel Kinsy, and Yong Chen, xBGAS: A Global Address Space Extension on RISC-V for High Performance Computing, IEEE Conference on International Parallel & Distributed Processing Symposium (IPDPS), Best Paper Award (1/462), 2021. 

  • Xi Wang, Antonino Tumeo, John D. Leidel, Jie Li and Yong Chen, HAM: Hotspot-Aware Manager for Improving Communications with 3D-Stacked Memory, IEEE Transactions on Computers (TC). 

  • Zach Hansen, Brody Williams, John D. Leidel, Xi Wang, Yong Chen, DMM-GAPBS: Adapting the GAP Benchmark Suite to a Distributed Memory Model, IEEE High Performance Extreme Computing Conference (HPEC), 2021.

  • Brody Williams, John D. Leidel, Xi Wang, and Yong Chen, CircusTent: A Benchmark Suite for Atomic Memory Operations, ACM International Symposium on Memory Systems (MEMSYS), 2020.

  • John D. Leidel, Xi Wang, Brody Williams, and Yong Chen, Toward a Microarchitecture for Efficient Execution of Irregular Applications, ACM Transactions on Parallel Computing (TOPC), 2020. 

  • Xi Wang, John D. Leidel, Brody Williams, and Yong Chen, PAC: Paged Adaptive Coalescer for 3D-stacked memory, ACM High-Performance Parallel and Distributed Computing (HPDC), 2020. 

  • Xi Wang, Brody Williams, John Leidel, et al., Remote Atomic Extension (RAE) for Scalable High Performance Computing. IEEE Design Automation Conference (DAC), 2020. 

  • Xi Wang, Antonino Tumeo, John D. Leidel, Jie Li, and Yong Chen, MAC: Memory Access Coalescer for 3D-Stacked Memory, ACM International Conference on Parallel Processing (ICPP), 2019.

  • Jie Li, Xi Wang, Antonino Tumeo, Brody Williams, John D. Leidel, and Yong Chen, PIMS: A Lightweight Processing-in-Memory Accelerator for Stencil Computations, ACM International Symposium on Memory Systems (MEMSYS), 2019

  • Xi Wang, John D. Leidel, Yong Chen, Memory Coalescing for Hybrid Memory Cube, ACM International Conference on Parallel Processing (ICPP), 2018.


学术兼职
  • IEEE DAC 2024 Best Paper Award Nominee (5/1456)

  • IEEE VLSI 2024 “Code-a-Chip” Award, First Prize

  • CSAW 2023 International AI Hardware Attack Challenge, First Prize

  • IEEE ISSCC 2023 “Code-a-Chip” Award, First Prize

  • IEEE Conference on IPDPS 2021 Best Paper Award (1/462)

  • Best Research Poster Award of NSF CAC (Cloud and Autonomic Computing) in 2020

  • Helen DeVitt Jones Excellence in Graduate Teaching Award of Texas Tech University in 2018

  • Travel Grant for attending ACM/IEEE SC17 (Super Computing 2017) in Denver 2017

  • Travel Grant for attending ACM/IEEE SC16 (Super Computing 2016) in Salt Lake City 2016


团队介绍

我们的团队名称为GEAR( Group of Emerging Architecture Research),专注于前沿芯片架构和芯片设计验证自动化方向的前沿探索,致力于推动全球AI+IC和AI+EDA的技术的发展,应对如今领域定制架构设计和日益繁复的系统设计挑战,以软硬协同的方式开展端到端的全栈式芯片设计自动化研究。


Every cog in the GEAR counts! & There is no loser in a winning team! 我们关注每一位团队成员的未来发展,以Top-Down的教育方式辅助全栈式的芯片设计流程学习,鼓励以兴趣为导向的开放研究模式。同时,我们也根据团队成员们的个人发展规划,平衡科研探索(Research)和工程实现(Development),致力于培养IC行业的六边形战士。



招生情况


课题组常年招收博士/硕士研究生及本科生,欢迎对芯片设计验证大模型、人工智能、处理器设计、计算机体系结构、EDA工具链、大语言模型、人工智能、私密计算、编译器、二进制转换等方向感兴趣的同学加入,详情请通过邮件沟通咨询(xi.wang@seu.edu.cn)。

毕业生介绍