World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
62
Citations
13249
World Ranking
1917
National Ranking
386

Overview

Tao Tang is affiliated with Beijing Jiaotong University in China and has contributed extensively to the field of engineering, particularly focused on transportation systems and railway technology. Their research encompasses a range of topics within industrial and manufacturing engineering, mechanical engineering, transportation, automotive engineering, and control and systems engineering.

The scientist's recent papers reflect diverse interests in transportation systems, operational research, and biomedical applications. Notable publications include:

  • "Hypoxia-pretreated ADSC-derived exosome-embedded hydrogels promote angiogenesis and accelerate diabetic wound healing" (2022) published in Acta Biomaterialia
  • "Timetable coordination in a rail transit network with time-dependent passenger demand" (2021) published in European Journal of Operational Research
  • "An analytical optimal control approach for virtually coupled high-speed trains with local and string stability" (2021) published in Transportation Research Part C Emerging Technologies
  • "Edge Intelligence in Intelligent Transportation Systems: A Survey" (2023) published in IEEE Transactions on Intelligent Transportation Systems
  • "Quantitative analysis for resilience-based urban rail systems: A hybrid knowledge-based and data-driven approach" (2021) published in Reliability Engineering & System Safety

Their frequent co-authors include Shuai Su, Hongjie Liu, Jiateng Yin, Li Zhu, and F. Richard Yu, each collaborating on multiple projects that have contributed to expanding knowledge in transportation and engineering disciplines.

Common publication venues for Tao Tang's work include:

  • IEEE Transactions on Intelligent Transportation Systems
  • arXiv (Cornell University)
  • Transportation Research Part C Emerging Technologies
  • IEEE Transactions on Vehicular Technology
  • Transportation Research Part B Methodological

The scientist's research mainly focuses on key areas such as:

  • Railway Systems and Energy Efficiency
  • Transportation Planning and Optimization
  • Railway Engineering and Dynamics
  • Electrical Contact Performance and Analysis
  • Traffic Prediction and Management Techniques
  • Electric and Hybrid Vehicle Technologies
  • Occupational Health and Safety Research

Tao Tang has contributed a significant body of work, with 247 publications grouped under the broad umbrella of engineering. Within this extensive portfolio, 65 publications relate specifically to industrial and manufacturing engineering, 47 focus on mechanical engineering, and 34 involve transportation topics.

The diversity of subfields and frequent collaborations reflect a multidisciplinary approach to addressing technical challenges in transportation and control systems. Research outcomes span both theoretical analyses and practical applications, highlighting a comprehensive engagement with the field's current issues and advancements.

Best Publications

  • Big Data Analytics in Intelligent Transportation Systems: A Survey

    Li Zhu;Fei Richard Yu;Yige Wang;Bin Ning

  • A Survey on Energy-Efficient Train Operation for Urban Rail Transit

    Xin Yang;Xiang Li;Bin Ning;Tao Tang

  • A Subway Train Timetable Optimization Approach Based on Energy-Efficient Operation Strategy

    Shuai Su;Xiang Li;Tao Tang;Ziyou Gao

  • Research and development of automatic train operation for railway transportation systems: A survey

    Jiateng Yin;Tao Tang;Lixing Yang;Jing Xun

  • A Cooperative Scheduling Model for Timetable Optimization in Subway Systems

    Xin Yang;Xiang Li;Ziyou Gao;Hongwei Wang

  • Dynamic passenger demand oriented metro train scheduling with energy-efficiency and waiting time minimization: Mixed-integer linear programming approaches

    Jiateng Yin;Lixing Yang;Tao Tang;Ziyou Gao

  • Energy-efficient metro train rescheduling with uncertain time-variant passenger demands: An approximate dynamic programming approach

    Jiateng Yin;Tao Tang;Lixing Yang;Ziyou Gao

  • Design of Running Grades for Energy-Efficient Train Regulation: A Case Study for Beijing Yizhuang Line

    Unknown

  • Passenger-demands-oriented train scheduling for an urban rail transit network

    Yihui Wang;Yihui Wang;Tao Tang;Bin Ning;Ton J.J. van den Boom

  • A Two-Objective Timetable Optimization Model in Subway Systems

    Xing Yang;Bin Ning;Xiang Li;Tao Tang

  • Cross-Layer Handoff Design in MIMO-Enabled WLANs for Communication-Based Train Control (CBTC) Systems

    Li Zhu;F. R. Yu;Bin Ning;Tao Tang

  • Passenger demand oriented train scheduling and rolling stock circulation planning for an urban rail transit line

    Yihui Wang;Andrea D’Ariano;Jiateng Yin;Lingyun Meng

  • An energy-efficient scheduling approach to improve the utilization of regenerative energy for metro systems

    Xin Yang;Xin Yang;Anthony Chen;Xiang Li;Bin Ning

  • Computationally Inexpensive Tracking Control of High-Speed Trains With Traction/Braking Saturation

    Qi Song;Yong-duan Song;Tao Tang;Bin Ning

  • Terminal iterative learning control based station stop control of a train

    Zhongsheng Hou;Yi Wang;Chenkun Yin;Tao Tang

  • Timetable coordination in a rail transit network with time-dependent passenger demand

    Jiateng Yin;Andrea D’Ariano;Yihui Wang;Lixing Yang

  • A Cooperative Train Control Model for Energy Saving

    Shuai Su;Tao Tang;Clive Roberts

  • Bilevel Feature Extraction-Based Text Mining for Fault Diagnosis of Railway Systems

    Feng Wang;Tianhua Xu;Tao Tang;MengChu Zhou

  • Optimization of Multitrain Operations in a Subway System

    Shuai Su;Tao Tang;Xiang Li;Ziyou Gao

  • An analytical optimal control approach for virtually coupled high-speed trains with local and string stability

    Yafei Liu;Yang Zhou;Shuai Su;Jing Xun

  • An Introduction to Parallel Control and Management for High-Speed Railway Systems

    Bin Ning;Tao Tang;Hairong Dong;Ding Wen

  • A Subway Train Timetable Optimization Approach Based on Energy-Efficient Operation Strategy

    Shuai Su;Xiang Li;Tao Tang

Frequent Co-Authors

Bin Ning
Bin Ning Beijing Jiaotong University
F. Richard Yu
F. Richard Yu Carleton University
Lixing Yang
Lixing Yang Beijing Jiaotong University
Anthony Chen
Anthony Chen Hong Kong Polytechnic University
Yongduan Song
Yongduan Song Chongqing University
Clive J. Roberts
Clive J. Roberts University of Nottingham
Bart De Schutter
Bart De Schutter Delft University of Technology
Lingjia Liu
Lingjia Liu Virginia Tech
B. De Schutter
B. De Schutter Delft University of Technology
Bin Ran
Bin Ran University of Wisconsin–Madison

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