World's Best Scientists 2026 revealed!
Yongxin Tong

Yongxin Tong

D-Index & Metrics

Computer Science

D-Index
42
Citations
11445
World Ranking
8198
National Ranking
1077

Overview

Yongxin Tong is affiliated with Beihang University in China and has a significant profile in computer science research. Their work spans across various subfields including artificial intelligence, signal processing, building and construction, automotive engineering, and information systems.

Their main research interests include privacy-preserving technologies in data, cryptography and data security, data management and algorithms, transportation and mobility innovations, advanced graph neural networks, smart parking systems research, and data quality and management.

Recent publications by Yongxin Tong encompass topics related to federated learning, combinatorial optimization, and reinforcement learning. Notable papers include:

  • "Federated Latent Dirichlet Allocation: A Local Differential Privacy Based Framework," 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • "Incorporating Multi-Source Urban Data for Personalized and Context-Aware Multi-Modal Transportation Recommendation," 2020, IEEE Transactions on Knowledge and Data Engineering
  • "A Survey on Federated Learning: A Perspective from Multi-Party Computation," 2023, Frontiers of Computer Science
  • "Combinatorial Optimization Meets Reinforcement Learning: Effective Taxi Order Dispatching at Large-Scale," 2021, IEEE Transactions on Knowledge and Data Engineering
  • "Hu-Fu," 2022, Proceedings of the VLDB Endowment

Their frequent coauthors include Zimu Zhou, Yuxiang Zeng, Lei Chen, Yexuan Shi, and Yi Xu. Collaborations with these researchers indicate sustained joint efforts in the areas of data management and intelligent systems.

Publishing venues for Yongxin Tong's research feature a diverse range of high-impact journals and conferences. These include:

  • arXiv (Cornell University)
  • IEEE Transactions on Knowledge and Data Engineering
  • Proceedings of the VLDB Endowment
  • Frontiers of Computer Science
  • ACM Transactions on Intelligent Systems and Technology

Yongxin Tong has contributed extensively to the field of computer science, with over a hundred publications emphasizing artificial intelligence. Their work intersects theoretical developments and practical applications, particularly in privacy and security aspects of data, as well as advanced algorithms for transportation and mobility.

Best Publications

  • Federated Machine Learning: Concept and Applications

    Qiang Yang;Yang Liu;Tianjian Chen;Yongxin Tong

  • Online mobile Micro-Task Allocation in spatial crowdsourcing

    Yongxin Tong;Jieying She;Bolin Ding;Libin Wang

  • The Simpler The Better: A Unified Approach to Predicting Original Taxi Demands based on Large-Scale Online Platforms

    Yongxin Tong;Yuqiang Chen;Zimu Zhou;Lei Chen

  • Spatial crowdsourcing: a survey

    Yongxin Tong;Zimu Zhou;Yuxiang Zeng;Lei Chen

  • Profit Allocation for Federated Learning

    Tianshu Song;Yongxin Tong;Shuyue Wei

  • Online minimum matching in real-time spatial data: experiments and analysis

    Yongxin Tong;Jieying She;Bolin Ding;Lei Chen

  • Mining frequent itemsets over uncertain databases

    Yongxin Tong;Lei Chen;Yurong Cheng;Philip S. Yu

  • A unified approach to route planning for shared mobility

    Yongxin Tong;Yuxiang Zeng;Zimu Zhou;Lei Chen

  • Whom to ask?: jury selection for decision making tasks on micro-blog services

    Caleb Chen Cao;Jieying She;Yongxin Tong;Lei Chen

  • gMission: a general spatial crowdsourcing platform

    Zhao Chen;Rui Fu;Ziyuan Zhao;Zheng Liu

  • Flexible online task assignment in real-time spatial data

    Yongxin Tong;Libin Wang;Zimu Zhou;Bolin Ding

  • SLADE: A Smart Large-Scale Task Decomposer in Crowdsourcing

    Yongxin Tong;Lei Chen;Zimu Zhou;Hosagrahar Visvesvaraya Jagadish

  • Trichromatic Online Matching in Real-Time Spatial Crowdsourcing

    Tianshu Song;Yongxin Tong;Libin Wang;Jieying She

  • Spatial crowdsourcing: challenges, techniques, and applications

    Yongxin Tong;Lei Chen;Cyrus Shahabi

  • Federated Latent Dirichlet Allocation: A Local Differential Privacy Based Framework

    Yansheng Wang;Yongxin Tong;Dingyuan Shi

  • Dynamic Pricing in Spatial Crowdsourcing: A Matching-Based Approach

    Yongxin Tong;Libin Wang;Zimu Zhou;Lei Chen

  • EAGRE: Towards scalable I/O efficient SPARQL query evaluation on the cloud

    Xiaofei Zhang;Lei Chen;Yongxin Tong;Min Wang

  • Utility-Aware Social Event-Participant Planning

    Jieying She;Yongxin Tong;Lei Chen

  • Conflict-Aware Event-Participant Arrangement and Its Variant for Online Setting

    Jieying She;Yongxin Tong;Lei Chen;Caleb Chen Cao

  • Discovering Threshold-based Frequent Closed Itemsets over Probabilistic Data

    Yongxin Tong;Lei Chen;Bolin Ding

Frequent Co-Authors

Lei Chen
Lei Chen Hong Kong University of Science and Technology
Zimu Zhou
Zimu Zhou City University of Hong Kong
Ke Xu
Ke Xu Beihang University
Qiang Yang
Qiang Yang Hong Kong University of Science and Technology
Hosagrahar V. Jagadish
Hosagrahar V. Jagadish University of Michigan–Ann Arbor
Lothar Thiele
Lothar Thiele ETH Zurich
Bolin Ding
Bolin Ding Alibaba Group (United States)
Philip S. Yu
Philip S. Yu University of Illinois at Chicago
João Gama
João Gama University of Porto
Cyrus Shahabi
Cyrus Shahabi University of Southern California

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