World's Best Scientists 2026 revealed!
Hang Li

Hang Li

D-Index & Metrics

Computer Science

D-Index
72
Citations
27183
World Ranking
1646
National Ranking
222

Research.com Recognitions

  • 2015 - ACM Distinguished Member

Overview

Hang Li is affiliated with ByteDance in China and has an extensive publication record in the fields of computer science and engineering, with particular focus on artificial intelligence and computer vision. Their contributions span a range of topics including advanced neural network applications, domain adaptation, few-shot learning, and multimodal machine learning.

Their research output includes the following recent papers:

  • Artificial intelligence and blockchain technology for secure smart grid and power distribution Automation: A State-of-the-Art Review, 2023, Sustainable Energy Technologies and Assessments
  • Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs, 2024, ACM SIGKDD Explorations Newsletter
  • Multi-Grained Vision Language Pre-Training: Aligning Texts with Visual Concepts, 2021, arXiv (Cornell University)
  • Airport Detection Based on Improved Faster RCNN in Large Scale Remote Sensing Images, 2020, Sensing and Imaging
  • Hot Region Selection Based on Selective Search and Modified Fuzzy C-Means in Remote Sensing Images, 2020, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

The scientist collaborates frequently with a number of co-authors including Shoulin Yin, Asif Ali Laghari, Shahid Karim, Zhuang Miao, and Volker Tresp.

The most frequent publication venues for Hang Li's work are:

  • arXiv (Cornell University)
  • International Journal of Electronic Security and Digital Forensics
  • Processes
  • IEEE Access
  • Computer Science and Information Systems

Hang Li has contributed books published by Springer Science+Business Media, notably Management of Digital EcoSystems (2024).

The scientist's main fields of study include:

  • Computer Science
  • Engineering

Their subfields of study encompass:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Control and Systems Engineering
  • Media Technology

Key topics central to their work are:

  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning
  • Multimodal Machine Learning Applications
  • Advanced Image and Video Retrieval Techniques
  • Advanced Image Fusion Techniques
  • Video Surveillance and Tracking Methods
  • Topic Modeling

In recognition of their contributions, Hang Li was awarded the ACM Distinguished Member honor in 2015.

Best Publications

  • Learning to rank: from pairwise approach to listwise approach

    Zhe Cao;Tao Qin;Tie-Yan Liu;Ming-Feng Tsai

  • Incorporating Copying Mechanism in Sequence-to-Sequence Learning

    Jiatao Gu;Zhengdong Lu;Hang Li;Victor O.K. Li

  • Convolutional Neural Network Architectures for Matching Natural Language Sentences

    Baotian Hu;Zhengdong Lu;Hang Li;Qingcai Chen

  • Neural Responding Machine for Short-Text Conversation

    Lifeng Shang;Zhengdong Lu;Hang Li

  • AdaRank: a boosting algorithm for information retrieval

    Jun Xu;Hang Li

  • Meta-SGD: Learning to Learn Quickly for Few Shot Learning.

    Zhenguo Li;Fengwei Zhou;Fei Chen;Hang Li

  • Listwise approach to learning to rank: theory and algorithm

    Fen Xia;Tie-Yan Liu;Jue Wang;Wensheng Zhang

  • Modeling Coverage for Neural Machine Translation

    Zhaopeng Tu;Zhengdong Lu;Yang Liu;Xiaohua Liu

  • Adapting ranking SVM to document retrieval

    Yunbo Cao;Jun Xu;Tie-Yan Liu;Hang Li

  • Context-aware query suggestion by mining click-through and session data

    Huanhuan Cao;Daxin Jiang;Jian Pei;Qi He

  • LETOR: A benchmark collection for research on learning to rank for information retrieval

    Tao Qin;Tie-Yan Liu;Jun Xu;Hang Li

  • LETOR: Benchmark Dataset for Research on Learning to Rank for Information Retrieval

    Tie-Yan Liu;Jun Xu;Tao Qin;Wenying Xiong

  • Named entity recognition in query

    Jiafeng Guo;Gu Xu;Xueqi Cheng;Hang Li

  • Learning to Rank for Information Retrieval and Natural Language Processing

    Hang Li

  • Multimodal Convolutional Neural Networks for Matching Image and Sentence

    Lin Ma;Zhengdong Lu;Lifeng Shang;Hang Li

  • Feature selection for ranking

    Xiubo Geng;Tie-Yan Liu;Tao Qin;Hang Li

  • Learning to answer questions from image using convolutional neural network

    Lin Ma;Zhengdong Lu;Hang Li

  • Generalizing case frames using a thesaurus and the MDL principle

    Hang Li;Naoki Abe

  • An Information Retrieval Approach to Short Text Conversation

    Zongcheng Ji;Zhengdong Lu;Hang Li

  • A Deep Architecture for Matching Short Texts

    Zhengdong Lu;Hang Li

  • Convolutional Neural Network Architectures for Matching Natural Language Sentences

    Baotian Hu;Zhengdong Lu;Hang Li;Qingcai Chen

  • Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval

    Noriko Kando;Tetsuya Sakai;Hideo Joho;Hang Li

Frequent Co-Authors

Tie-Yan Liu
Tie-Yan Liu Microsoft (United States)
Zhengdong Lu
Zhengdong Lu Huawei Technologies (China)
Jun Xu
Jun Xu Renmin University of China
Zhaopeng Tu
Zhaopeng Tu Tencent (China)
Tao Qin
Tao Qin Microsoft (United States)
Qun Liu
Qun Liu Huawei Technologies (China)
Daxin Jiang
Daxin Jiang Microsoft (United States)
Naoki Abe
Naoki Abe IBM (United States)
Jian Pei
Jian Pei Duke University
Enhong Chen
Enhong Chen University of Science and Technology of China

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