World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
57
Citations
14395
World Ranking
3802
National Ranking
507

Overview

Yu Zhang is affiliated with the Southern University of Science and Technology in China, focusing on research within computer science, with particular emphasis on artificial intelligence. Their scholarly output encompasses a wide range of topics including domain adaptation and few-shot learning, topic modeling, speech recognition and synthesis, natural language processing techniques, multimodal machine learning applications, quantum information and cryptography, and speech and audio processing.

The scientist has contributed extensively to the literature, with notable recent publications including:

  • A Survey on Multi-Task Learning, 2021, IEEE Transactions on Knowledge and Data Engineering
  • Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages, 2023, arXiv (Cornell University)

Other significant works linked to Yu Zhang include papers published in venues such as Proceedings of the AAAI Conference on Artificial Intelligence and Frontiers in Pharmacology, demonstrating interdisciplinary engagement with machine learning applications in pharmacology and artificial intelligence.

Yu Zhang frequently collaborates with a number of researchers, the most frequent co-authors including Qiang Yang, Wenyuan Dai, Sinno Jialin Pan, Jiawei Han, and Chui-Ping Yang. These collaborations reflect sustained partnerships across several areas of computer science research.

The majority of Yu Zhang's research papers are published on arXiv (Cornell University), with additional publications appearing in Physical Review A, SSRN Electronic Journal, Proceedings of the AAAI Conference on Artificial Intelligence, and Interspeech 2022. The diverse set of publication venues illustrates a focus on both theoretical foundations and applied methodologies in computer science.

Yu Zhang has also contributed to academic publishing through book authorship, with a publication titled Transfer Learning released by Cambridge University Press in 2020.

The researcher's expertise crosses multiple subfields of study including artificial intelligence, computer vision and pattern recognition, signal processing, atomic and molecular physics and optics, as well as industrial and manufacturing engineering. This multidisciplinary approach supports wide-ranging investigations into computational techniques and their applications.

Best Publications

  • A Survey on Multi-Task Learning

    Yu Zhang;Qiang Yang

  • An Overview of Multi-task Learning

    Yu Zhang;Qiang Yang

  • A Survey on Multi-Task Learning

    Yu Zhang;Qiang Yang

  • A convex formulation for learning task relationships in multi-task learning

    Yu Zhang;Dit-Yan Yeung

  • Learning from facial aging patterns for automatic age estimation

    Xin Geng;Zhi-Hua Zhou;Yu Zhang;Gang Li

  • Comprehensive Learning Particle Swarm Optimization Algorithm With Local Search for Multimodal Functions

    Yulian Cao;Han Zhang;Wenfeng Li;Mengchu Zhou

  • CoNet: Collaborative Cross Networks for Cross-Domain Recommendation

    Guangneng Hu;Yu Zhang;Qiang Yang

  • Plan explanations as model reconciliation: Moving beyond explanation as soliloquy

    Tathagata Chakraborti;Sarath Sreedharan;Yu Zhang;Subbarao Kambhampati

  • Multi-task warped Gaussian process for personalized age estimation

    Yu Zhang;Dit-Yan Yeung

  • Overlapping community detection via bounded nonnegative matrix tri-factorization

    Yu Zhang;Dit-Yan Yeung

  • Transfer Learning

    Unknown

  • End-to-end adversarial memory network for cross-domain sentiment classification

    Zheng Li;Yu Zhang;Ying Wei;Yuxiang Wu

  • Differentially Private High-Dimensional Data Publication via Sampling-Based Inference

    Rui Chen;Qian Xiao;Yu Zhang;Jianliang Xu

  • Multi-domain collaborative filtering

    Yu Zhang;Bin Cao;Dit-Yan Yeung

  • Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages

    Unknown

  • Hierarchical Attention Transfer Network for Cross-domain Sentiment Classification

    Zheng Li;Ying Wei;Yu Zhang;Qiang Yang

  • Plan explicability and predictability for robot task planning

    Yu Zhang;Sarath Sreedharan;Anagha Kulkarni;Tathagata Chakraborti

  • Deep neural networks for high dimension, low sample size data

    Bo Liu;Ying Wei;Yu Zhang;Qiang Yang

  • Adaptive transfer learning

    Bin Cao;Sinno Jialin Pan;Yu Zhang;Dit-Yan Yeung

  • Knowledge Distillation from Internal Representations

    Unknown

  • Distant Domain Transfer Learning

    Unknown

  • Distant Domain Transfer Learning

    Ben Tan;Yu Zhang;Sinno Jialin Pan;Qiang Yang

  • A Regularization Approach to Learning Task Relationships in Multitask Learning

    Yu Zhang;Dit-Yan Yeung

  • Transfer metric learning by learning task relationships

    Yu Zhang;Dit-Yan Yeung

  • Flexible End-to-End Dialogue System for Knowledge Grounded Conversation

    Wenya Zhu;Kaixiang Mo;Yu Zhang;Zhangbin Zhu

  • Interactive Attention Transfer Network for Cross-Domain Sentiment Classification.

    Kai Zhang;Hefu Zhang;Qi Liu;Hongke Zhao

  • Transfer Learning via Learning to Transfer.

    Ying Wei;Yu Zhang;Junzhou Huang;Qiang Yang

  • Transfer Learning via Learning to Transfer: Supplementary Material

    Ying Wei;Yu Zhang;Junzhou Huang;Qiang Yang

Frequent Co-Authors

Qiang Yang
Qiang Yang Hong Kong University of Science and Technology
Dit-Yan Yeung
Dit-Yan Yeung Hong Kong University of Science and Technology
Sinno Jialin Pan
Sinno Jialin Pan Chinese University of Hong Kong
Yunming Ye
Yunming Ye Harbin Institute of Technology
Xiang Zhang
Xiang Zhang University of Hong Kong
James T. Kwok
James T. Kwok Hong Kong University of Science and Technology
Xuan Song
Xuan Song University of Tokyo
Ruigang Yang
Ruigang Yang University of Kentucky
Dinesh Manocha
Dinesh Manocha University of Maryland, College Park
Tong Zhang
Tong Zhang University of Illinois at Urbana-Champaign

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