World's Best Scientists 2026 revealed!
Hua-Jun Zeng

Hua-Jun Zeng

D-Index & Metrics

Computer Science

D-Index
52
Citations
10041
World Ranking
5116
National Ranking
2359

Overview

Hua-Jun Zeng is affiliated with Rulai, Inc. in the United States and engages primarily in research intersecting engineering and physics. Their work spans both theoretical and applied aspects of the fields, emphasizing computational and nonlinear physical phenomena.

Their recent publications include:

  • Fractional solitons: New phenomena and exact solutions (2023, Frontiers in Physics)
  • Thermal performance of fractal metasurface and its mathematical model (2024, Thermal Science)
  • Exact solutions of a class of generalized nanofluidic models (2024, Open Physics)

Zeng's research contributions focus significantly on nonlinear wave behaviors and fractional differential equation solutions, reflecting interests in complex dynamical systems.

Main topics addressed in their work are:

  • Nonlinear Waves and Solitons
  • Fractional Differential Equations Solutions
  • Nonlinear Photonic Systems
  • Surface Modification and Superhydrophobicity
  • Fluid Dynamics Simulations and Interactions
  • Adhesion, Friction, and Surface Interactions
  • Lattice Boltzmann Simulation Studies

Zeng's studies align with several subfields, including computational mechanics and statistical and nonlinear physics. Their expertise extends into modeling and simulation, as well as investigations into surfaces, coatings, films, and materials mechanics.

Frequent coauthors appearing in their publications are:

  • Yu-Xia Wang
  • Min Xiao
  • Ying Wang
  • Abdulrahman Ali Alsolami
  • Ji-Huan He

Key venues for Zeng's research dissemination include:

  • Frontiers in Physics
  • Thermal Science
  • Open Physics

This profile presents an overview of Hua-Jun Zeng's academic contributions characterized by interdisciplinary approaches in engineering and physics, with a distinctive focus on nonlinear phenomena, fractal and fractional mathematics, and nanofluidic system modeling.

Best Publications

  • Scalable collaborative filtering using cluster-based smoothing

    Gui-Rong Xue;Chenxi Lin;Qiang Yang;WenSi Xi

  • Learning to cluster web search results

    Hua-Jun Zeng;Qi-Cai He;Zheng Chen;Wei-Ying Ma

  • CubeSVD: a novel approach to personalized Web search

    Jian-Tao Sun;Hua-Jun Zeng;Huan Liu;Yuchang Lu

  • Demographic prediction based on user's browsing behavior

    Jian Hu;Hua-Jun Zeng;Hua Li;Cheng Niu

  • Support vector machines classification with a very large-scale taxonomy

    Tie-Yan Liu;Yiming Yang;Hao Wan;Hua-Jun Zeng

  • Optimizing web search using web click-through data

    Gui-Rong Xue;Hua-Jun Zeng;Zheng Chen;Yong Yu

  • Web-page classification through summarization

    Dou Shen;Zheng Chen;Qiang Yang;Hua-Jun Zeng

  • Enhancing text clustering by leveraging Wikipedia semantics

    Jian Hu;Lujun Fang;Yang Cao;Hua-Jun Zeng

  • Method and computing device used for identifying item relative to content of Web site

    Zheng Chen;Li Li;Ying Li;Tarek Najm

  • Query-based snippet clustering for search result grouping

    Hua-Jun Zeng;Qicai He;Guimei Liu;Zheng Chen

  • Using Wikipedia knowledge to improve text classification

    Pu Wang;Jian Hu;Hua-Jun Zeng;Zheng Chen

  • Identifying influential persons in a social network

    Dong Zhuang;Benyu Zhang;Heng Zhang;Jeremy Tantrum

  • METHOD AND SYSTEM FOR DETECTING TIME WHEN OUTGOING COMMUNICATION INCLUDES SPECIFIED CONTENT

    Zhang Benyu;Zeng Hua-Jun;Ma Wei-Ying;Chen Zheng

  • Reinforced clustering of multi-type data objects for search term suggestion

    Hua-Jun Zeng;Benyu Zhang;Zheng Chen;Wei-Ying Ma

  • ReCoM: reinforcement clustering of multi-type interrelated data objects

    Jidong Wang;Huajun Zeng;Zheng Chen;Hongjun Lu

  • Web-page summarization using clickthrough data

    Jian-Tao Sun;Dou Shen;Hua-Jun Zeng;Qiang Yang

  • System and method for utilizing the content of audio/video files to select advertising content for display

    Ying Li;Li Li;Tarek Najm;Hongbin Gao

  • Search engine enhancement using mined implicit links

    Hua-Jun Zeng;Gui-Rong Xue;Zheng Chen;Wei-Ying Ma

  • Exploiting the hierarchical structure for link analysis

    Gui-Rong Xue;Qiang Yang;Hua-Jun Zeng;Yong Yu

  • Implicit link analysis for small web search

    Gui-Rong Xue;Hua-Jun Zeng;Zheng Chen;Wei-Ying Ma

  • LCQMC:A Large-scale Chinese Question Matching Corpus

    Xin Liu;Qingcai Chen;Chong Deng;Huajun Zeng

Frequent Co-Authors

Zheng Chen
Zheng Chen Microsoft Research Asia (China)
Benyu Zhang
Benyu Zhang Ant Group
Wei-Ying Ma
Wei-Ying Ma Tsinghua University
Gui-Rong Xue
Gui-Rong Xue Alibaba Group (China)
Ying Li
Ying Li Microsoft (United States)
Yong Yu
Yong Yu Shanghai Jiao Tong University
Jian-Tao Sun
Jian-Tao Sun Microsoft (United States)
Qiang Yang
Qiang Yang Hong Kong University of Science and Technology
Xuanhui Wang
Xuanhui Wang Google (United States)
Tie-Yan Liu
Tie-Yan Liu 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

Studying Computer Science in the USA opens doors to a vast range of related online degrees and career opportunities. For students interested in broadening their technical expertise, an online degree in mechanical engineering is a logical step, blending computational skills with hands-on engineering principles.

If you have a passion for fundamental science, pursuing the best online physics degree can deepen your theoretical understanding and open up research or teaching careers.

Data-driven roles are in high demand, and many students ask, what is the cheapest data science course in the US? Affordable online data science programs make it possible to build sought-after skills in analytics, machine learning, and artificial intelligence without a heavy financial burden.

For those aiming for work in networks, power systems, or hardware design, the online electrical engineering career outcomes are strong, thanks to the ongoing need for expertise across industries.

Exploring these online degrees can expand your career options, build new skills, and create a flexible academic pathway within or alongside Computer Science.

Best Scientists Citing Hua-Jun Zeng

Trending Scientists

Recently Published Articles