World's Best Scientists 2026 revealed!
Award Badge
Computer Science
China
2025

D-Index & Metrics

Computer Science

D-Index
85
Citations
27662
World Ranking
806
National Ranking
123

Research.com Recognitions

  • 2025 - Research.com Computer Science in China Leader Award
  • 2020 - ACM Distinguished Member
  • 2020 - IEEE Fellow For contributions to the methodology and application of machine learning and data mining

Overview

Jieping Ye is affiliated with Alibaba Group in China and has contributed extensively to the fields of computer science and engineering. The main areas of research include artificial intelligence, computer vision and pattern recognition, transportation, automotive engineering, and building and construction.

The scholar's work spans several core research topics:

  • Transportation and Mobility Innovations
  • Transportation Planning and Optimization
  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning
  • Sharing Economy and Platforms
  • Traffic Prediction and Management Techniques
  • Topic Modeling

Published papers cover multiple influential venues, with frequent contributions to:

  • arXiv (Cornell University)
  • Transportation Research Part C Emerging Technologies
  • IEEE Transactions on Knowledge and Data Engineering
  • IEEE Transactions on Image Processing
  • bioRxiv (Cold Spring Harbor Laboratory)

Recent notable publications include:

  • "Object Detection in 20 Years: A Survey" (2023) in Proceedings of the IEEE
  • "A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications" (2021) in IEEE Transactions on Knowledge and Data Engineering
  • "A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications" (2020) in arXiv (Cornell University)
  • "Pricing and equilibrium in on-demand ride-pooling markets" (2020) in Transportation Research Part B Methodological
  • "An Attention-Based Graph Neural Network for Heterogeneous Structural Learning" (2020) in Proceedings of the AAAI Conference on Artificial Intelligence

The researcher has collaborated frequently with colleagues including Hongtu Zhu, Zhiwei Qin, Yuhong Guo, Shuang Qiu, and Deyi Ji.

In addition to journal articles and conference papers, Jieping Ye has authored a book titled Reinforcement Learning in the Ridesharing Marketplace, published by Morgan & Claypool Publishers in 2024.

Professional recognition includes the ACM Distinguished Member award in 2020 and the IEEE Fellow honor the same year, the latter awarded for contributions to the methodology and application of machine learning and data mining.

Best Publications

  • Tensor completion for estimating missing values in visual data

    Ji Liu;Przemyslaw Musialski;Peter Wonka;Jieping Ye

  • Fast and Accurate Matrix Completion via Truncated Nuclear Norm Regularization

    Yao Hu;Debing Zhang;Jieping Ye;Xuelong Li

  • Spatiotemporal Multi-Graph Convolution Network for Ride-Hailing Demand Forecasting

    Xu Geng;Yaguang Li;Leye Wang;Lingyu Zhang

  • Multi-task feature learning via efficient l 2, 1 -norm minimization

    Jun Liu;Shuiwang Ji;Jieping Ye

  • Generalized Low Rank Approximations of Matrices

    Unknown

  • An accelerated gradient method for trace norm minimization

    Shuiwang Ji;Jieping Ye

  • Learning brain connectivity of Alzheimer's disease by sparse inverse covariance estimation.

    Shuai Huang;Jing Li;Liang Sun;Jieping Ye

  • On Similarity Preserving Feature Selection

    Zheng Zhao;Lei Wang;Huan Liu;Jieping Ye

  • Canonical Correlation Analysis for Multilabel Classification: A Least-Squares Formulation, Extensions, and Analysis

    Liang Sun;Shuiwang Ji;Jieping Ye

  • An optimization criterion for generalized discriminant analysis on undersampled problems

    Jieping Ye;R. Janardan;C.H. Park;H. Park

  • Least squares linear discriminant analysis

    Jieping Ye

  • Robust multi-task feature learning

    Pinghua Gong;Jieping Ye;Changshui Zhang

  • A two-stage linear discriminant analysis via QR-decomposition

    Unknown

  • Efficient Methods for Overlapping Group Lasso

    Lei Yuan;Jun Liu;Jieping Ye

  • 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

  • Hypergraph spectral learning for multi-label classification

    Liang Sun;Shuiwang Ji;Jieping Ye

  • Integrating low-rank and group-sparse structures for robust multi-task learning

    Jianhui Chen;Jiayu Zhou;Jieping Ye

  • A multi-task learning formulation for predicting disease progression

    Jiayu Zhou;Lei Yuan;Jun Liu;Jieping Ye

  • A new optimization criterion for generalized discriminant analysis on undersampled problems

    J. Ye;Ravi Janardan;C.H. Park;H. Park

  • Multi-task Representation Learning for Travel Time Estimation

    Yaguang Li;Kun Fu;Zheng Wang;Cyrus Shahabi

  • Clustered Multi-Task Learning Via Alternating Structure Optimization

    Jiayu Zhou;Jianhui Chen;Jieping Ye

  • Discriminative K-means for Clustering

    Jieping Ye;Zheng Zhao;Mingrui Wu

  • Multi-Task Feature Learning Via Efficient l2,1-Norm Minimization

    Jun Liu;Shuiwang Ji;Jieping Ye

Frequent Co-Authors

Shuiwang Ji
Shuiwang Ji Texas A&M University
Jun Liu
Jun Liu Infinia ML (United States)
Sudhir Kumar
Sudhir Kumar Temple University
Jiayu Zhou
Jiayu Zhou Michigan State University
Paul M. Thompson
Paul M. Thompson University of Southern California
Peter Wonka
Peter Wonka King Abdullah University of Science and Technology
Ji Liu
Ji Liu Facebook (United States)
Wei Fan
Wei Fan Tencent (China)
Sethuraman Panchanathan
Sethuraman Panchanathan Arizona State University
Eric M. Reiman
Eric M. Reiman Arizona State University

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

Exploring online programs in Computer Science opens doors to numerous related degrees and certifications. Many students choose to complement their studies with specialized fields. For instance, accredited online electrical engineering programs offer flexibility and practical skills that pair well with computer science expertise.

If you’re seeking a quicker entry into the tech workforce, consider easy certifications that pay well. These certifications are designed for rapid completion and can significantly boost your employment prospects and earnings potential.

For those looking to advance their qualifications without spending years in school, options like the quickest cheapest masters degree programs are ideal. These online master’s degrees offer affordability and speed, allowing you to upgrade your credentials in less time.

Finally, when considering graduate studies, explore masters degrees that are worth it. Degrees in areas such as data science, cybersecurity, and artificial intelligence are especially in demand and deliver strong career returns after graduation.

Best Scientists Citing Jieping Ye

Trending Scientists

Recently Published Articles