Do Not Go Gentle Into That Good Night.
--『 Interstellar 』, Dylan Thomas.

I am a final-year Ph.D. candidate at Chinese University of Hong Kong (CUHK-CSE), where I have been fortunate to work with Professor Bei Yu and co-supervised by Professor Martin D. F. Wong. My Chinese name is 陈国晋.

I am on the job market for 2024-2025, appreciate any opportunities!

Research Interests:

  • Scaling deep learning: large language models, agent systems[arxiv'24], LLM on EDA [arxiv'24], large-scale layout representation learning [ICCAD'22].
  • Design for manufacturing: computational lithography [SPIE'24'23], OPC [DAC'24'23,ICCAD'24'22'21'20], SMO [DAC'24, TCAD'24].
  • Optimization: bi-level & multi-level optimization [DAC'24], level-set optimization [ICCAD'21], GPU acceleration.
  • Deep learning in VLSI design: physics-informed networks for EDA problems [DAC'23].

Check my research overview here.

Experiences

2024.07 - 2024.10

Logo  Google DeepMind   Ph.D. Student Researcher
Mountain view, CA

2024.04 - 2024.07

Logo  NVIDIA   Research Scientist Intern
Mentor & Manager. Haoyu Yang & Mark Ren Austin, TX

2023.08 - 2024.4

Logo  University of Texas at Austin   Visiting Scholar
Supervisor : Prof. David Z. Pan Austin, TX

2018

Logo  Tencent   Intern
Shenzhen, China

Publications

Representative publications that I am a primary author on are highlighted.
[Google Scholar; 240+ citations, h-index: 9+] [Download bibtex for all publications] [ORCID]

Preprints

[P3] LLM-Enhanced Bayesian Optimization for Efficient Analog Layout Constraint Generation [bibtex] [paper] [code] arXiv 2024
[P2] AnalogCoder: Analog Circuit Design via Training-Free Code Generation [bibtex] [paper] arXiv 2024
[P1] Intelligent OPC Engineer Assistant for Semiconductor Manufacturing [bibtex] [paper] arXiv 2024

Conference papers

[C17] PACE: Pacing Operator Learning to Accurate Optical Field Simulation for Complicated Photonic Devices [bibtex] [paper]
Hanqing Zhu, Wenyan Cong, Guojin Chen, Shupeng Ning, Ray Chen, Jiaqi Gu, and David Z. Pan
NeurIPS 2024
[C16] Differentiable Edge-based OPC [bibtex] [paper]
Guojin Chen, Haoyu Yang, Haoxing Ren, Bei Yu, and David Z. Pan
ICCAD 2024
[C15] Efficient Bilevel Source Mask Optimization [bibtex] [paper]
Guojin Chen, Hongquan He, Peng Xu, Hao Geng, and Bei Yu
DAC 2024
[C14] Fracturing-aware Curvilinear ILT via Circular E-beam Mask Writer [bibtex]
Xinyun Zhang, Su Zheng, Guojin Chen, Binwu Zhu, Hong Xu, and Bei Yu
DAC 2024
[C13] Performance-driven Analog Routing via Heterogeneous 3DGNN and Potential Relaxation [bibtex]
Peng Xu, Guojin Chen, Keren Zhu, Tinghuan Chen, Tsung-Yi Ho, and Bei Yu
DAC 2024
[C12] Open-Source Differentiable Lithography Imaging Framework [bibtex] [paper] [code]
Guojin Chen, Hao Geng, Bei Yu, and David Z. Pan
SPIE 2024
[C11] AlphaSyn: Logic Synthesis Optimization with Efficient Monte Carlo Tree Search [bibtex] [paper]
Zehua Pei, Fangzhou Liu, Zhuolun He, Guojin Chen, Haisheng Zheng, Keren Zhu, and Bei Yu
ICCAD 2023
[C10] Physics-Informed Optical Kernel Regression Using Complex-valued Neural Fields [bibtex] [paper]
Guojin Chen, Zehua Pei, Haoyu Yang, Yuzhe Ma, Bei Yu, and Martin Wong
DAC 2023 (Best score in DFM track.)
[C9] DiffPattern: Layout Pattern Generation via Discrete Diffusion [bibtex] [paper]
Zixiao Wang, Yunheng Shen, Wenqian Zhao, Yang Bai, Guojin Chen, Farzan Farnia, and Bei Yu
DAC 2023
[C8] GPU-accelerated Matrix Cover Algorithm for Multiple Patterning Layout Decomposition [bibtex] [paper]
Guojin Chen, Haoyu Yang, and Bei Yu
SPIE 2023
[C7] Efficient Point Cloud Analysis Using Hilbert Curve. [bibtex] [paper]
Wanli Chen, Xinge Zhu, Guojin Chen, and Bei Yu
ECCV 2022
[C6] AdaOPC: A Self-Adaptive Mask Optimization Framework For Real Design Patterns [bibtex] [paper]
Wenqian Zhao, Xufeng Yao, Ziyang Yu, Guojin Chen, Yuzhe Ma, Bei Yu, and Martin Wong
ICCAD 2022
[C5] LayouTransformer: Generating Layout Patterns with Transformer via Sequential Pattern Modeling [bibtex] [paper]
Liangjian Wen, Yi Zhu, Lei Ye, Guojin Chen, Bei Yu, Jianzhuang Liu, and Chunjing Xu
ICCAD 2022
[C4] DevelSet: Deep Neural Level Set for Instant Mask optimization [bibtex] [abs] [paper]
Guojin Chen, Ziyang Yu, Hongduo Liu, Yuzhe Ma, and Bei Yu
ICCAD 2021
[C3] Learning Point Clouds in EDA. [bibtex] [abs] [paper]
Wei Li, Guojin Chen, Haoyu Yang, Ran Chen, and Bei Yu
ISPD 2021
[C2] DAMO: Deep Agile Mask Optimization for Full Chip Scale [bibtex] [abs] [paper]
Guojin Chen, Wanli Chen, Yuzhe Ma, Haoyu Yang, and Bei Yu
ICCAD 2020
[C1] A GPU-enabled Level Set Method for Mask Optimization [bibtex] [abs] [paper]
Ziyang Yu, Guojin Chen, Yuzhe Ma, and Bei Yu
DATE 2020

Journal papers

[J7] RuleLearner: OPC Rule Extraction from Inverse Lithography Technique Engine [bibtex]
Ziyang Yu, Su Zheng, Wenqian Zhao, Shuo Yin, Xiaoxiao Liang, Guojin Chen, Yuzhe Ma, Bei Yu, and Martin D.F. Wong
TCAD 2024
[J6] DeepOTF: Learning Equations-constrained Prediction for Electromagnetic Behavior [bibtex]
Peng Xu, Siyuan Xu, Tinghuan Chen, Guojin Chen, Tsung-Yi Ho, and Bei Yu
TODAES 2024
[J5] Ultra-Fast Source Mask Optimization via Conditional Discrete Diffusion [bibtex] [paper]
Guojin Chen, Zixiao Wang, Bei Yu, David Z. Pan, and Martin D.F. Wong
TCAD 2024
[J4] L2O-ILT: Learning to Optimize Inverse Lithography Techniques [bibtex] [paper]
Binwu Zhu, Su Zheng, Ziyang Yu, Guojin Chen, Yuzhe Ma, Fan Yang, Bei Yu, and Martin Wong
TCAD 2023
[J3] A GPU-Enabled Level-Set Method for Mask Optimization [bibtex] [paper]
Ziyang Yu, Guojin Chen, Yuzhe Ma, and Bei Yu
TCAD 2023
[J2] DevelSet: Deep Neural Level Set for Instant Mask optimization [bibtex] [paper]
Guojin Chen, Ziyang Yu, Hongduo Liu, Yuzhe Ma, and Bei Yu
TCAD 2023
[J1] DAMO: Deep Agile Mask Optimization for Full-Chip Scale [bibtex] [paper]
Guojin Chen, Wanli Chen, Qi Sun, Yuzhe Ma, Haoyu Yang, and Bei Yu
TCAD 2022

News

  • Oct. 15, 2024    Back to HK, offer offer come to me!
  • Aug. 07, 2024    Good day! My google scholar citation reached 200. Small step for others, big step for me!
  • July. 22, 2024    Starting internship at Google DeepMind, Mountain View, CA.
  • June. 24, 2024    Attending DAC 2024, San Francisco, CA.
  • Apr. 29, 2024    Starting internship at NVIDIA Research. Let's rock'n'roll! Many thanks to my mentor Haoyu Yang and Mark Ren.
  • Feb. 25, 2024    Traveling to SPIE24, San Jose. [slides], [codes]
  • Feb. 13, 2024    Three papers got accepted by DAC 2024.
  • Jan. 13, 2024    One TCAD about source mask optimization got accepted.
  • Aug. 01, 2023    Coming to Austin.
  • Jul. 28, 2023    Attending DAC conference.
  • Feb. 06, 2023    Two papers got accepted by DAC 2023, one paper get best score in DFM track.

Open Source Repositories

1. 161 | 2024 TorchOPC/TorchLitho   Differentiable computational lithography with PyTorch
2. 10 | 2024 dekura/LLANA   LLM-Enhanced Bayesian Optimization for Efficient Analog Constraint Generation
3. 118 | 2023 OpenOPC/OpenILT   Open-source inverse lithography technology (ILT) framework
4. 124 | 2023 ai4eda/awesome-AI4EDA   A curated paper list of existing AI for EDA studies.

AI for EDA

I’m also maintaining a curated list of AI for EDA papers. Check it out here: Awesome AI for EDA.
The list is under construction and you are welcomed to submit your publications follow the instructions.

Professional Activities

Paper Review / External Review

2023-2024 Neural Information Processing Systems (NeurIPS)
2021-2024 Design Automation Conference (DAC)
2022-2025 AAAI Conference on Artificial Intelligence (AAAI)
2022-2024 IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD)

Teaching

Python Computing (AIST 1110), TA F2022
Mobile Computing (CSCI 3310), TA S2022
Numerical Optimization (AIST 3010), TA F2021

Last updated on Nov, 2024 . Thanks to Bamos for the blog template.