Haochen Wang

1.5k citations
34 papers · 765 indexed · 1 hit paper · h-index 12

Impact in

Papers in

Haochen Wang

28 papers receiving 750 citations

Hit Papers

Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation 2023 · 165 citations
165202320262024202550100150

Peers

Haochen Wang
Comparison fields: 5 of 116
  • Computer Graphics and Computer-Aided Design 101
  • Computer Vision and Pattern Recognition 272
  • Molecular Biology 305
  • Computational Mechanics 85
  • Neurology 32
Replace Hao Su with:
Hao Su China
Yu Qiao China
Chaoyi Zhang Australia
J Buckingham United States
Qingqiong Deng China
Yuwang Liu China
Qiao Gu China
Yuan Yuan China
Pan Zhang China
A.M. Vossepoel Netherlands
Haochen Wang relative to Hao Su China Hao Su's profile →
Citations per field
00.5×6.4×
Hao Su · 1×
Citations per year

Countries citing papers authored by Haochen Wang

Since Specialization
Citations

This map shows the geographic impact of Haochen Wang's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Haochen Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haochen Wang more than expected).

Fields of papers citing papers by Haochen Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Haochen Wang. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Haochen Wang. The network helps show where Haochen Wang may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Haochen Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Haochen Wang Line = papers co-authored together Haochen Wang links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
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19 201799
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Analysis on the natural property of Yangzhou Garden regional characteristics.
20141

About Haochen Wang

Haochen Wang is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Molecular Biology, Cancer Research and Geology, having authored 34 papers that have together received 765 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (4 papers), RNA Interference and Gene Delivery (3 papers), Multimodal Machine Learning Applications (3 papers), RNA and protein synthesis mechanisms (3 papers), Bacterial Genetics and Biotechnology (3 papers), Advanced Image and Video Retrieval Techniques (3 papers), Visual Attention and Saliency Detection (2 papers) and Generative Adversarial Networks and Image Synthesis (2 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (101 citations), Computer Vision and Pattern Recognition (272 citations), Molecular Biology (305 citations), Computational Mechanics (85 citations) and Neurology (32 citations). Haochen Wang has collaborated with scholars based in China, United States and Belgium. Frequent co-authors include Greg Shakhnarovich, Xiaowo Wang, Lei Wei, Jiahao Li, Raymond A. Yeh, Liyang Liu, Ye Wang, Yao Hu, Xiaolong Jiang and Song Bai. Their work appears in journals such as Advanced Healthcare Materials, Briefings in Bioinformatics, Nucleic Acids Research, iScience and Nutrients.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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