World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
10532
World Ranking
9537
National Ranking
4043

Overview

Zhaowen Wang is affiliated with Adobe Systems in the United States. Their research spans across multiple disciplines, primarily focusing on engineering and computer science fields. Within these areas, Wang's work concentrates on subfields such as computer vision and pattern recognition, fluid flow and transfer processes, mechanical engineering, computational mechanics, and electrical and electronic engineering.

The scientist's publication record includes research on various topics related to combustion, fluid dynamics, and chemical processes. Key subjects covered in their work include molten salt chemistry and electrochemical processes, advanced combustion engine technologies, combustion and flame dynamics, combustion and detonation processes, plasma applications and diagnostics, extraction and separation processes, and inorganic fluorides and related compounds.

Wang frequently publishes in several academic venues, with a notable number of papers appearing in arXiv (Cornell University), SSRN Electronic Journal, Combustion and Flame, Separation and Purification Technology, and the Journal of Molecular Liquids.

Recent papers authored or co-authored by Wang include:

  • Progress in experimental investigations on evaporation characteristics of a fuel droplet, 2022, Fuel Processing Technology
  • A new shift mechanism for micro-explosion of water-diesel emulsion droplets at different ambient temperatures, 2022, Applied Energy
  • An experimental and kinetic modeling study of ammonia/n-heptane blends, 2022, Combustion and Flame
  • Development of a reduced chemical mechanism for ammonia/n-heptane blends, 2023, Fuel
  • Mixture formation characteristics and feasibility of methanol as an alternative fuel for gasoline in port fuel injection engines: Droplet evaporation and spray visualization, 2023, Energy Conversion and Management

Wang frequently collaborates with several coauthors, including Xianwei Hu, Xiaobei Cheng, Zhongning Shi, Aimin Liu, and Huimin Wu. These collaborations reflect a consistent involvement in multidisciplinary projects that integrate expertise across combustion science, fluid mechanics, and computational methods.

Best Publications

  • Image Captioning with Semantic Attention

    Quanzeng You;Hailin Jin;Zhaowen Wang;Chen Fang

  • Coupled Dictionary Training for Image Super-Resolution

    Jianchao Yang;Zhaowen Wang;Zhe Lin;S. Cohen

  • Deep Networks for Image Super-Resolution with Sparse Prior

    Zhaowen Wang;Ding Liu;Jianchao Yang;Wei Han

  • Universal Style Transfer via Feature Transforms

    Yijun Li;Chen Fang;Jimei Yang;Zhaowen Wang

  • CamShift guided particle filter for visual tracking

    Zhaowen Wang;Xiaokang Yang;Yi Xu;Songyu Yu

  • Image Super-Resolution by Neural Texture Transfer

    Zhifei Zhang;Zhaowen Wang;Zhe Lin;Hairong Qi

  • Wide Activation for Efficient and Accurate Image Super-Resolution.

    Jiahui Yu;Yuchen Fan;Jianchao Yang;Ning Xu

  • Multi-content GAN for Few-Shot Font Style Transfer

    Samaneh Azadi;Matthew Fisher;Vladimir Kim;Zhaowen Wang

  • Diversified Texture Synthesis with Feed-Forward Networks

    Yijun Li;Chen Fang;Jimei Yang;Zhaowen Wang

  • Visually-Aware Fashion Recommendation and Design with Generative Image Models

    Wang-Cheng Kang;Chen Fang;Zhaowen Wang;Julian McAuley

  • Robust Single Image Super-Resolution via Deep Networks With Sparse Prior

    Ding Liu;Zhaowen Wang;Bihan Wen;Jianchao Yang

  • Robust Video Super-Resolution with Learned Temporal Dynamics

    Ding Liu;Zhaowen Wang;Yuchen Fan;Xianming Liu

  • Visual to Sound: Generating Natural Sound for Videos in the Wild

    Yipin Zhou;Zhaowen Wang;Chen Fang;Trung Bui

  • Towards Privacy-Preserving Visual Recognition via Adversarial Training: A Pilot Study

    Zhenyu Wu;Zhangyang Wang;Zhaowen Wang;Hailin Jin

  • Re-weighted Adversarial Adaptation Network for Unsupervised Domain Adaptation

    Qingchao Chen;Yang Liu;Zhaowen Wang;Ian Wassell

  • Vista: A Visually, Socially, and Temporally-aware Model for Artistic Recommendation

    Ruining He;Chen Fang;Zhaowen Wang;Julian McAuley

  • Flow-Grounded Spatial-Temporal Video Prediction from Still Images

    Yijun Li;Chen Fang;Jimei Yang;Zhaowen Wang

  • Learning Super-Resolution Jointly From External and Internal Examples

    Zhangyang Wang;Yingzhen Yang;Zhaowen Wang;Shiyu Chang

  • Controllable Artistic Text Style Transfer via Shape-Matching GAN

    Shuai Yang;Zhangyang Wang;Zhaowen Wang;Ning Xu

  • Bilevel sparse coding for coupled feature spaces

    Jianchao Yang;Zhaowen Wang;Zhe Lin;Xianbiao Shu

  • Spatial–Spectral Classification of Hyperspectral Images Using Discriminative Dictionary Designed by Learning Vector Quantization

    Zhaowen Wang;Nasser M. Nasrabadi;Thomas S. Huang

Frequent Co-Authors

Hailin Jin
Hailin Jin Adobe Systems (United States)
Thomas S. Huang
Thomas S. Huang University of Illinois at Urbana-Champaign
Jianchao Yang
Jianchao Yang ByteDance
Zhe Lin
Zhe Lin Adobe Systems (United States)
Jimei Yang
Jimei Yang Adobe Systems (United States)
Zhangyang Wang
Zhangyang Wang The University of Texas at Austin
Shiyu Chang
Shiyu Chang University of California, Santa Barbara
Yun Fu
Yun Fu Northeastern University
Julian McAuley
Julian McAuley University of California, San Diego
Jonathan Brandt
Jonathan Brandt Adobe Systems (United States)

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