What drives my research:

Research Overview

For full publication list please check my website: https://gjchen.me/ or google scholar.

Focus on: modeling / optimization / and creativity.

Large Language Model & LLM on EDA

Agent system / ICL

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Agent System with LLM-labeled Regression Tree:

https://arxiv.org/abs/2408.12775

Agent system / RL + LLM

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AnalogCoder

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In-context learning with Bayesian Optimization: https://arxiv.org/abs/2406.05250

• https://github.com/dekura/LLANA 10+ ⭐ Open-source framework.
• LLMs can effectively transfer knowledge and generate a more promising initial set when given the problem setup. </aside>

Computational Lithography

About computational lithography

👉 Forward Simulation.

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[[DAC23] Nitho: NeRF-inspired forward lithography simulator ](https://gjchen.notion.site/DAC23-Nitho-NeRF-inspired-forward-lithography-simulator-1ffb31bd65a44aa093df95a200b18453)

• [https://arxiv.org/abs/2303.08435]
• Physics-informed modeling. Highest precision learning-based lithography simulator to date.
• Best score in DFM track / #learning-based </aside>

Nitho: NeRF-inspired forward lithography

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[SPIE, OpenSource] TorchLitho :

• Analytical method / PyTorch </aside>

⏮️ Backward Optimization