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Zeming Dong
I am an Algorithm Researcher at China Electronics Corporation (CEC), Beijing, China. Prior to that, I was a research associate (2025) at the University of Luxembourg,
working with Prof. Mike Papadakis and Prof. Maxime Cordy. I have received my Ph.D. degree (2024) from Kyushu University in Japan, under the supervision of Prof. Jianjun Zhao, my M.E. degree (2018) at Yamaguchi University, advised
by Prof. Shinya Matsufuji, and my B.E. degree (2015) at Yancheng Institute Of Technology.
I also have industrial research experience from an internship at NTT Laboratories in Tokyo, Japan, where I worked on applied research at the intersection of AI and software engineering.
My overall research goal is to make more reliable and intelligent AI systems, addressing challenges in both the model lifecycle and the application ecosystem in the real world. This involves improving the generalization and robustness to correctly detect in-distribution data and learn out-of-distribution data with novel structures and categories.
Currently, I am driven to deeply understand how large language models (LLMs) work, when LLMs fail, and effectively align them with needs from the real world.
Email /
Google Scholar /
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Linkedin
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Learning Generalizable Multimodal Representations for Software Vulnerability Detection
Zeming Dong,
Yuejun Guo,
Qiang Hu,
Yao Zhang,
Maxime Cordy,
Hao Liu,
Mike Papadakis,
Yongqiang Lyu
Preprint, 2026
arXiv
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GenCode: A Generic Data Augmentation Framework for Boosting Deep Learning-Based Code Understanding
Zeming Dong,
Qiang Hu,
Xiaofei Xie,
Maxime Cordy,
Mike Papadakis,
Yves Le Traon,
Jianjun Zhao
Empirical Software Engineering (EMSE), 2026
arXiv
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code
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Boosting Source Code Learning with Data Augmentation: An Empirical Study
Zeming Dong,
Qiang Hu,
Yuejun Guo,
Zhenya Zhang,
Maxime Cordy,
Mike Papadakis,
Yves Le Traon,
Jianjun Zhao
Empirical Software Engineering (EMSE), 2025
arXiv
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code
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On the Effectiveness of Hybrid Pooling in Mixup-Based Graph Learning for Language Processing
Zeming Dong,
Qiang Hu,
Zhenya Zhang,
Yuejun Guo,
Maxime Cordy,
Mike Papadakis,
Yves Le Traon,
Jianjun Zhao
Journal of Systems and Software (JSS), 2024
arXiv
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code
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On the Effectiveness of Graph Data Augmentation for Source Code Learning
Zeming Dong,
Qiang Hu,
Zhenya Zhang,
Jianjun Zhao
Knowledge-Based Systems (KBS), 2024
Link
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MixCode: Enhancing code classification by mixup-based data augmentation
Zeming Dong,
Qiang Hu,
Yuejun Guo,
Maxime Cordy,
Mike Papadakis,
Zhenya Zhang,
Yves Le Traon,
Jianjun Zhao
30th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), 2023
arXiv
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code
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A Study on PAPR Reduction in OFDM Using Complex Hadamard Matrices
Zeming Dong,
Shinya Matsufuji,
Yuta Ida,
Takahiro Matsumoto
8th International Workshop on Signal Design and Its Applications in Communications (IWSDA), 2017
Link
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- 2024 Google Cloud Research Credits, 5,000 USD
- 2023 SANER Travel Grant Award, 4,000 MOP
- 2017 Monbukagakusho Honors Scholarship for Privately-Financed International Students, 576,000 JPY
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