World's Best Scientists 2026 revealed!

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Computer Science

D-Index
56
Citations
13558
World Ranking
4050
National Ranking
1928

Overview

Feng Zhou is affiliated with the University of Michigan-Ann Arbor in the United States. Their research activities primarily focus on the field of Engineering, contributing extensively to multiple subfields including Social Psychology, Artificial Intelligence, Materials Chemistry, Safety, Risk, Reliability and Quality, and Automotive Engineering.

The scientist's work spans several core topics such as Human-Automation Interaction and Safety, Traffic and Road Safety, Sleep and Work-Related Fatigue, Autonomous Vehicle Technology and Safety, Crystallization and Solubility Studies, X-ray Diffraction in Crystallography, and Safety Warnings and Signage.

Feng Zhou has published numerous papers in various academic venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • The Cambridge Structural Database
  • SSRN Electronic Journal
  • Proceedings of the Human Factors and Ergonomics Society Annual Meeting
  • IEEE Transactions on Intelligent Transportation Systems

Some of the recent papers authored or co-authored by Feng Zhou are:

  • Using Eye-Tracking Data to Predict Situation Awareness in Real Time During Takeover Transitions in Conditionally Automated Driving, 2021, IEEE Transactions on Intelligent Transportation Systems
  • Examining the effects of emotional valence and arousal on takeover performance in conditionally automated driving, 2020, Transportation Research Part C Emerging Technologies
  • Predicting driver takeover performance in conditionally automated driving, 2020, Accident Analysis & Prevention

The scientist has collaborated frequently with several co-authors, including:

  • X. Jessie Yang
  • Baiying Lei
  • Lilit Avetisyan
  • Jackie Ayoub
  • Na Du

Best Publications

  • Trends in augmented reality tracking, interaction and display: A review of ten years of ISMAR

    Feng Zhou;Henry Been-Lirn Duh;Mark Billinghurst

  • Detecting depression from facial actions and vocal prosody

    Jeffrey F. Cohn;Tomas Simon Kruez;Iain Matthews;Ying Yang

  • Searching Central Difference Convolutional Networks for Face Anti-Spoofing

    Zitong Yu;Chenxu Zhao;Zezheng Wang;Yunxiao Qin

  • MagFace: A Universal Representation for Face Recognition and Quality Assessment

    Qiang Meng;Shichao Zhao;Zhida Huang;Feng Zhou

  • Deep Metric Learning with Angular Loss

    Jian Wang;Feng Zhou;Shilei Wen;Xiao Liu

  • Factorized Graph Matching

    Feng Zhou;Fernando De la Torre

  • Hierarchical Aligned Cluster Analysis for Temporal Clustering of Human Motion

    Feng Zhou;F. De la Torre;J. K. Hodgins

  • Multi-Attention Multi-Class Constraint for Fine-grained Image Recognition

    Ming Sun;Yuchen Yuan;Feng Zhou;Errui Ding

  • Kernel Pooling for Convolutional Neural Networks

    Yin Cui;Feng Zhou;Jiang Wang;Xiao Liu

  • Canonical Time Warping for Alignment of Human Behavior

    Feng Zhou;Fernando Torre

  • Deep Learning Framework for Alzheimer’s Disease Diagnosis via 3D-CNN and FSBi-LSTM

    Chiyu Feng;Ahmed Elazab;Peng Yang;Tianfu Wang

  • Fine-Grained Categorization and Dataset Bootstrapping Using Deep Metric Learning with Humans in the Loop

    Yin Cui;Feng Zhou;Yuanqing Lin;Serge Belongie

  • Melanoma Recognition in Dermoscopy Images via Aggregated Deep Convolutional Features

    Zhen Yu;Xudong Jiang;Feng Zhou;Jing Qin

  • Aligned Cluster Analysis for temporal segmentation of human motion

    Feng Zhou;F. Torre;J.K. Hodgins

  • Embedding Label Structures for Fine-Grained Feature Representation

    Xiaofan Zhang;Feng Zhou;Yuanqing Lin;Shaoting Zhang

  • Deep Spatial Gradient and Temporal Depth Learning for Face Anti-Spoofing

    Zezheng Wang;Zitong Yu;Chenxu Zhao;Xiangyu Zhu

  • Generalized time warping for multi-modal alignment of human motion

    Feng Zhou;Fernando De la Torre

  • Fine-Grained Image Classification by Exploring Bipartite-Graph Labels

    Feng Zhou;Yuanqing Lin

  • Deformable Graph Matching

    Feng Zhou;Fernando De la Torre

  • Learning meta model for zero- and few-shot face anti-spoofing

    Yunxiao Qin;Chenxu Zhao;Xiangyu Zhu;Zezheng Wang

  • Affective and cognitive design for mass personalization: status and prospect

    Feng Zhou;Yangjian Ji;Roger Jianxin Jiao

Frequent Co-Authors

Baiying Lei
Baiying Lei Shenzhen University
Tianfu Wang
Tianfu Wang Shenzhen University
Fernando De la Torre
Fernando De la Torre Carnegie Mellon University
Xiao Liu
Xiao Liu Baidu (China)
Dawn M. Tilbury
Dawn M. Tilbury University of Michigan–Ann Arbor
Errui Ding
Errui Ding Baidu (China)
Yuanqing Lin
Yuanqing Lin Aibee Inc.
Dong Ni
Dong Ni Shenzhen University
Zhen Lei
Zhen Lei Chinese Academy of Sciences
Jing Qin
Jing Qin Hong Kong Polytechnic University

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