Mingjie Liu  

 



  ![](/sites/default/files/person/Mingjie_Liu.jpg)

  

 Mingjie Liu is currently a Research Scientist at NVIDIA, where he actively conduct research on Electronic Design Automation. He received his PhD degree in electrical and computer engineering from the The University of Texas at Austin in 2022. His research interest include applied machine learning for design automation and design automation for analog and mixed-signal integrated circuits.



   Research Area(s)

[Artificial Intelligence and Machine Learning ](/research-area/machine-learning-artificial-intelligence)

[Circuits and VLSI Design](/research-area/circuits)

 

 

  

 Main Field of Interest

[Circuits and VLSI Design](/research-area/circuits)

 

  

 Google Scholar

[https://scholar.google.com/citations?user=-v5DbrMAAAAJ&hl=en&oi=ao](https://scholar.google.com/citations?user=-v5DbrMAAAAJ&hl=en&oi=ao)

 

  

 

 

 



 ### Publications

 

### 2025 

[Spec2RTL-Agent: Automated Hardware Code Generation from Complex Specifications Using LLM Agent Systems](/publication/2025-06_spec2rtl-agent-automated-hardware-code-generation-complex-specifications-using)

[Zhongzhi Yu](/person/zhongzhi-yu), [Mingjie Liu](/person/mingjie-liu), Michael Zimmer, Yingyan (Celine) Lin, Yong Liu, Mark Haoxing Ren



[IEEE International Conference on LLM-Aided Design, 2025](https://iclad.ai/)









### 2023 

[ChipNeMo: Domain-Adapted LLMs for Chip Design](/publication/2023-10_chipnemo-domain-adapted-llms-chip-design)

[Mingjie Liu](/person/mingjie-liu), Teo Ene, Robert Kirby, Chris Cheng, [Nathaniel Pinckney](/person/nathaniel-pinckney), [Rongjian Liang](/person/rongjian-liang), Jonah Alben, Himyanshu Anand, Sanmitra Banerjee, Ismet Bayraktaroglu, Bonita Bhaskaran, Bryan Catanzaro, Arjun Chaudhuri, Sharon Clay, Bill Dally, Laura Dang, Parikshit Deshpande, Siddhanth Dhodhi, Sameer Halepete, Eric Hill, Jiashang Hu, Sumit Jain, [Brucek Khailany](/person/brucek-khailany), George Kokai, Kishor Kunal, Xiaowei Li, Charley Lind, Hao Liu, Stuart Oberman, Sujeet Omar, Sreedhar Pratty, Jonathan Raman, Ambar Sarkar, Zhengjiang Shao, Hanfei Sun, Pratik P Suthar, Varun Tej, [Walker Turner](/person/walker-turner), Kaizhe Xu, Mark Haoxing Ren













[VerilogEval: Evaluating Large Language Models for Verilog Code Generation](/publication/2023-09_verilogeval-evaluating-large-language-models-verilog-code-generation)

[Mingjie Liu](/person/mingjie-liu), [Nathaniel Pinckney](/person/nathaniel-pinckney), [Brucek Khailany](/person/brucek-khailany), Mark Haoxing Ren



[2023 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)](https://arxiv.org/abs/2309.07544)









[A 9.7fJ/Conv.-Step Capacitive Sensor Readout Circuit with Incremental Zoomed Time Domain Quantization](/publication/2023-04_97fjconv-step-capacitive-sensor-readout-circuit-incremental-zoomed-time-domain)

Zilong Shen, Xiyuan Tang, Zhongyi Wu, Haoyang Luo, Zongnan Wang, [Mingjie Liu](/person/mingjie-liu), Xing Zhang, Yuan Wang



[2023 IEEE Custom Integrated Circuits Conference (CICC)](https://ieeexplore.ieee.org/document/10121301)









### 2022 

[An Adversarial Active Sampling-based Data Augmentation Framework for Manufacturable Chip Design](/publication/2022-12_adversarial-active-sampling-based-data-augmentation-framework-manufacturable)

[Mingjie Liu](/person/mingjie-liu), [Haoyu Yang](/person/haoyu-yang), Zongyi Li, Kumara Sastry, Saumyadip Mukhopadhyay, Selim Dogru, Anima Anandkumar, David Z. Pan, [Brucek Khailany](/person/brucek-khailany), Mark Haoxing Ren



[Workshop on ML for Systems at NeurIPS](http://mlforsystems.org/)









[Why are Graph Neural Networks Effective for EDA Problems?](/publication/2022-10_why-are-graph-neural-networks-effective-eda-problems)

Mark Haoxing Ren, Siddhartha Nath, [Yanqing Zhang](/person/yanqing-zhang), Hao Chen, [Mingjie Liu](/person/mingjie-liu)



[2022 International Conference on Computer-Aided Design](https://iccad.com/)