World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
9534
World Ranking
7494
National Ranking
3260

Overview

Yan Huang is affiliated with the University of North Texas in the United States. Their research primarily spans the fields of Computer Science and Engineering, with a substantial focus on Artificial Intelligence, explored in 45 publications, along with contributions to Sociology and Political Science, Computer Science Applications, Electrical and Electronic Engineering, and Information Systems.

Their work addresses several specialized topics, including:

  • Privacy-Preserving Technologies in Data
  • Mobile Crowdsensing and Crowdsourcing
  • Adversarial Robustness in Machine Learning
  • Cryptography and Data Security
  • Privacy, Security, and Data Protection
  • Advanced Graph Neural Networks
  • Recommender Systems and Techniques

Yan Huang has published in multiple venues, with notable contributions to:

  • arXiv (Cornell University)
  • IEEE Internet of Things Journal
  • High-Confidence Computing
  • Future Generation Computer Systems
  • Big Data Mining and Analytics

Frequent collaborators include:

  • Zhenzhen Xie (9 joint publications)
  • Junjie Pang (8 joint publications)
  • Zhipeng Cai (6 joint publications)
  • Liang Wang (3 joint publications)
  • Reza M. Parizi (2 joint publications)

Among recent research outputs, several papers highlight the scope and evolution of Yan Huang's work:

  • A survey on security and privacy of federated learning, 2020, Future Generation Computer Systems
  • Security and Privacy in Metaverse: A Comprehensive Survey, 2023, Big Data Mining and Analytics
  • Realizing the Heterogeneity: A Self-Organized Federated Learning Framework for IoT, 2020, IEEE Internet of Things Journal
  • Exploring personalization via federated representation Learning on non-IID data, 2023, Neural Networks
  • Computational Approaches to Detect Illicit Drug Ads and Find Vendor Communities Within Social Media Platforms, 2020, IEEE/ACM Transactions on Computational Biology and Bioinformatics

The research emphasis on privacy, security, and federated learning is evident, illustrated by topics such as personalized learning on non-IID data and privacy-preserving mechanisms in decentralized environments. Yan Huang's studies also cover the intersection of machine learning with social and biological data contexts, as indicated by their work on illicit drug ad detection via computational methods.

Best Publications

  • T-drive: driving directions based on taxi trajectories

    Jing Yuan;Yu Zheng;Chengyang Zhang;Wenlei Xie

  • Map-matching for low-sampling-rate GPS trajectories

    Yin Lou;Chengyang Zhang;Yu Zheng;Xing Xie

  • Discovering colocation patterns from spatial data sets: a general approach

    Y. Huang;S. Shekhar;H. Xiong

  • Advances in Spatial and Temporal Databases

    Michael Gertz;Matthias Renz;Xiaofang Zhou;Erik Hoel

  • Discovering Spatial Co-location Patterns: A Summary of Results

    Shashi Shekhar;Yan Huang

  • Digital game-based vocabulary learning: where are we and where are we going?

    Di Zou;Yan Huang;Haoran Xie

  • Efficient Privacy-Preserving Biometric Identification

    Yan Huang;Lior Malka;David Evans;Jonathan Katz

  • Mining Co-Location Patterns with Rare Events from Spatial Data Sets

    Yan Huang;Jian Pei;Hui Xiong

  • Propagation networks for recognition of partially ordered sequential action

    Yifan Shi;Yan Huang;D. Minnen;A. Bobick

  • Large scale real-time ridesharing with service guarantee on road networks

    Yan Huang;Favyen Bastani;Ruoming Jin;Xiaoyang Sean Wang

  • A Framework for Mining Sequential Patterns from Spatio-Temporal Event Data Sets

    Yan Huang;Liqin Zhang;Pusheng Zhang

  • Towards reducing taxicab cruising time using spatio-temporal profitability maps

    Jason W. Powell;Yan Huang;Favyen Bastani;Minhe Ji

  • Evacuation planning: a capacity constrained routing approach

    Qingsong Lu;Yan Huang;Shashi Shekhar

  • A Framework for Discovering Co-location Patterns in Data Sets with Extended Spatial Objects

    Hui Xiong;Shashi Shekhar;Yan Huang;Vipin Kumar

  • Mining confident co-location rules without a support threshold

    Yan Huang;Hui Xiong;Shashi Shekhar;Jian Pei

  • Terahertz emission and detection both based on high-Tc superconductors: Towards an integrated receiver

    D. Y. An;J. Yuan;N. Kinev;M. Y. Li

  • Discovering Co-location Patterns from Spatial Datasets: A General Approach

    Yan Huang;Shashi Shekhar;Hui Xiong

  • Notice of Removal: VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation

    Unknown

  • Relational Network for Skeleton-Based Action Recognition

    Wu Zheng;Lin Li;Zhaoxiang Zhang;Yan Huang

  • Integration of wireless sensor networks in environmental monitoring cyber infrastructure

    Jue Yang;Chengyang Zhang;Xinrong Li;Yan Huang

  • Cloaking locations for anonymous location based services: a hybrid approach

    Chengyang Zhang;Yan Huang

  • Semi-Supervised GMM and DNN Acoustic Model Training with Multi-system Combination and Confidence Re-calibration

    Yan Huang;Dong Yu;Yifan Gong;Chaojun Liu

  • On the Relationships between Clustering and Spatial Co-location Pattern Mining

    Yan Huang;Pusheng Zhang

  • SPOT: locating social media users based on social network context

    Longbo Kong;Zhi Liu;Yan Huang

  • Multi-pseudo Regularized Label for Generated Samples in Person Re-Identification

    Yan Huang;Jinsong Xu;Qiang Wu;Zhedong Zheng

Frequent Co-Authors

Yifan Gong
Yifan Gong Microsoft (United States)
Shashi Shekhar
Shashi Shekhar University of Minnesota
Jinyu Li
Jinyu Li Microsoft (United States)
Hui Xiong
Hui Xiong Rutgers, The State University of New Jersey
Xiaoshuang Chen
Xiaoshuang Chen Chinese Academy of Sciences
Ruoming Jin
Ruoming Jin Kent State University
Youngryel Ryu
Youngryel Ryu Seoul National University
Chang-Tien Lu
Chang-Tien Lu Virginia Tech
Dong Yu
Dong Yu Tencent (China)
Zhimou Yang
Zhimou Yang Nankai University

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