Do Not Go Gentle Into That Good Night.--『 Interstellar 』, Dylan Thomas.
Greetings! I’m currently a student researcher at Google DeepMind. I am also 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.
I am on the job market for 2024-2025, appreciate any opportunities!
Check my research overview here.
2024.07 - Present
Google DeepMind
Ph.D. Student Researcher |
2024.04 - 2024.07
NVIDIA
Research Scientist Intern |
2023.08 - 2024.4
University of Texas at Austin
Visiting Scholar |
2018
Tencent
Intern |
Representative publications that I am a primary author on are
highlighted.
[Google Scholar; 229+ citations, h-index: 8+]
[Download bibtex for all publications]
[ORCID]
[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 |
[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 |
[P1] |
LLM-Enhanced Bayesian Optimization for Efficient Analog Layout Constraint Generation
[bibtex]
[paper] [code] arXiv 2024 |
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. | 113 | 2023 OpenOPC/OpenILT Open-source inverse lithography technology (ILT) framework |
4. | 118 | 2023 ai4eda/awesome-AI4EDA A curated paper list of existing AI for EDA studies. |
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.
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) |
Python Computing (AIST 1110), TA | F2022 |
Mobile Computing (CSCI 3310), TA | S2022 |
Numerical Optimization (AIST 3010), TA | F2021 |
Last updated on Oct, 2024 . Thanks to Bamos for the blog template.