Chengrui Gao (高成睿) Ph.D. Student LAMDA Group School of Artificial Intelligence National Key Laboratory for Novel Software Technology Nanjing University email: gaocr at lamda.nju.edu.cn

Currently I am a Ph.D. student of School of Artificial Intelligence in Nanjing University, supervised by Associate Prof. Chao Qian, and a member of LAMDA Group, led by professor Zhi-Hua Zhou.

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Education

Sep 2018 - Jun 2022 : B.Sc. in Artificial Intelligence, School of Computer Science and Engineering, Southeast University;

Sep 2022 - Now : Ph.D. candidate in Computer Science, School of Artificial Intelligence, Nanjing University.

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Research Interest

My primary research focus lies in Learning to Optimize (L2O), particularly leveraging deep learning techniques to solve combinatorial optimization problems. My current work centers on the challenging discrete problems from two key domains: Operations Research (OR) and Electronic Design Automation (EDA).

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Publications

(* indicates equal contribution)

[OR] Chengrui Gao*, Haopu Shang*, Ke Xue, and Chao Qian. Neural Solver Selection for Combinatorial Optimization.
In: Proceedings of the 42nd International Conference on Machine Learning (ICML'25), Vancouver, Canada, 2025. [PDF]

[EDA] Yunqi Shi*, Chengrui Gao*, Wanqi Ren, Siyuan Xu, Ke Xue, Mingxuan Yuan, Chao Qian, Zhi-Hua Zhou. Open3DBench: Open-Source Benchmark for 3D-IC Backend Implementation and PPA Evaluation. In: Arxiv preprint (submitted to ICCAD'25), 2025. [PDF]

[OR] Chengrui Gao, Haopu Shang, Ke Xue, Dong Li, and Chao Qian. Towards Generalizable Neural Solvers for Vehicle Routing Problems via Ensemble with Transferrable Local Policy.
In: Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI'24), Jeju, South Korea, 2024. [PDF]

Contact:
National Key Laboratory for Novel Software Technology, Nanjing University, Xianlin Campus Mailbox 603, 163 Xianlin Avenue, Qixia District, Nanjing 210023, China
(南京市栖霞区仙林大道163号，南京大学仙林校区603信箱，软件新技术国家重点实验室，210023)

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