World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
61
Citations
14918
World Ranking
3074
National Ranking
412

Overview

Nan Duan is affiliated with Microsoft Research Asia (China) and has contributed extensively to the field of computer science, particularly focusing on artificial intelligence and multimodal machine learning. Their research encompasses various subfields, including computer vision and pattern recognition, information systems, signal processing, and software engineering.

The scientist's publication record includes nearly 500 papers primarily in computer science. Their work often centers on topics such as topic modeling, natural language processing techniques, and multimodal machine learning applications. Additional areas of specialization include domain adaptation and few-shot learning, software engineering research, advanced image and video retrieval techniques, and video analysis and summarization.

Frequent co-authors collaborating with Nan Duan include:

  • Yeyun Gong
  • Daxin Jiang
  • Ming Zhou
  • Chenfei Wu
  • Weizhu Chen

The scientist's work has appeared in prominent publication venues with repeated contributions to:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • Neurocomputing
  • Findings of the Association for Computational Linguistics: ACL 2022

Some recent papers showcasing the breadth of Nan Duan's research include:

  • Unicoder-VL: A Universal Encoder for Vision and Language by Cross-Modal Pre-Training (2020), published in the Proceedings of the AAAI Conference on Artificial Intelligence
  • scGPT: toward building a foundation model for single-cell multi-omics using generative AI (2024), published in Nature Methods
  • CLIP4Clip: An empirical study of CLIP for end to end video clip retrieval and captioning (2022), published in Neurocomputing
  • UniXcoder: Unified Cross-Modal Pre-training for Code Representation (2022), published in the Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation (2021), published in arXiv (Cornell University)

Best Publications

  • CodeBERT: A Pre-Trained Model for Programming and Natural Languages

    Zhangyin Feng;Daya Guo;Duyu Tang;Nan Duan

  • CLIP4Clip: An Empirical Study of CLIP for End to End Video Clip Retrieval

    Unknown

  • Unicoder-VL: A Universal Encoder for Vision and Language by Cross-Modal Pre-Training.

    Gen Li;Nan Duan;Yuejian Fang;Ming Gong

  • K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters

    Ruize Wang;Duyu Tang;Nan Duan;zhongyu wei

  • GraphCodeBERT: Pre-training Code Representations with Data Flow

    Daya Guo;Shuo Ren;Shuai Lu;Zhangyin Feng

  • CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation

    Shuai Lu;Daya Guo;Shuo Ren;Junjie Huang

  • ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-training.

    Weizhen Qi;Yu Yan;Yeyun Gong;Dayiheng Liu

  • Question Generation for Question Answering

    Nan Duan;Duyu Tang;Peng Chen;Ming Zhou

  • XGLUE: A New Benchmark Datasetfor Cross-lingual Pre-training, Understanding and Generation

    Yaobo Liang;Nan Duan;Yeyun Gong;Ning Wu

  • Progress in Neural NLP: Modeling, Learning, and Reasoning

    Ming Zhou;Nan Duan;Shujie Liu;Heung Yeung Shum

  • Unicoder: A Universal Language Encoder by Pre-training with Multiple Cross-lingual Tasks

    Haoyang Huang;Yaobo Liang;Nan Duan;Ming Gong

  • Question Answering and Question Generation as Dual Tasks

    Duyu Tang;Nan Duan;Tao Qin;Zhao Yan

  • Constraint-Based Question Answering with Knowledge Graph

    Junwei Bao;Nan Duan;Zhao Yan;Ming Zhou

  • Graph-Based Reasoning over Heterogeneous External Knowledge for Commonsense Question Answering

    Shangwen Lv;Daya Guo;Jingjing Xu;Duyu Tang

  • Building Task-Oriented Dialogue Systems for Online Shopping.

    Zhao Yan;Nan Duan;Peng Chen;Ming Zhou

  • Reasoning Over Semantic-Level Graph for Fact Checking

    Wanjun Zhong;Jingjing Xu;Duyu Tang;Zenan Xu

  • Automating code review activities by large-scale pre-training

    Unknown

  • Knowledge-Based Question Answering as Machine Translation

    Junwei Bao;Nan Duan;Ming Zhou;Tiejun Zhao

  • AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models

    Unknown

  • Unicoder-VL: A Universal Encoder for Vision and Language by Cross-modal Pre-training

    Gen Li;Nan Duan;Yuejian Fang;Ming Gong

  • Visual Question Generation as Dual Task of Visual Question Answering

    Yikang Li;Nan Duan;Bolei Zhou;Xiao Chu

  • UniViLM: A Unified Video and Language Pre-Training Model for Multimodal Understanding and Generation.

    Huaishao Luo;Lei Ji;Botian Shi;Haoyang Huang

  • XGLUE: A New Benchmark Dataset for Cross-lingual Pre-training, Understanding and Generation

    Yaobo Liang;Nan Duan;Yeyun Gong;Ning Wu

Frequent Co-Authors

Ming Zhou
Ming Zhou Langboat Technology
Duyu Tang
Duyu Tang Fudan University
Daxin Jiang
Daxin Jiang Microsoft (United States)
Shujie Liu
Shujie Liu Microsoft Research Asia (China)
Bing Qin
Bing Qin Harbin Institute of Technology
Houqiang Li
Houqiang Li University of Science and Technology of China
Xuanjing Huang
Xuanjing Huang Fudan University
Zhoujun Li
Zhoujun Li Beihang University
Ting Liu
Ting Liu Harbin Institute of Technology
Jianfeng Gao
Jianfeng Gao Microsoft (United States)

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring online degrees opens up flexible pathways for those interested in Computer Science careers in the USA. Many students start with an associate degree online, which offers a quick and affordable route into IT support or programming roles. For more advanced specialization, earning a master’s degree can significantly boost job prospects.

In fact, determining which master's degree is most in demand in usa can help future-proof your career. Computer Science consistently ranks among the top choices due to high employer demand and diverse job options.

Affordability is a key concern. Many students seek out the cheapest online college options to minimize debt while earning their credentials. Flexible admissions is also important—luckily, there are now online graduate programs that accept 2.0 gpa, allowing more people the chance to advance regardless of previous academic hurdles.

Whether you’re starting with an associate degree, looking at affordable programs, or aiming for an in-demand master’s, online education can provide a convenient and robust path into the computer science field.

Best Scientists Citing Nan Duan

Trending Scientists

Recently Published Articles