Weihao Gao

770 total citations · 1 hit paper
36 papers, 240 citations indexed

About

Weihao Gao is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Weihao Gao has authored 36 papers receiving a total of 240 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computer Vision and Pattern Recognition, 10 papers in Artificial Intelligence and 10 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Weihao Gao's work include Retinal Imaging and Analysis (10 papers), Advanced Image Processing Techniques (6 papers) and Advanced Image Fusion Techniques (5 papers). Weihao Gao is often cited by papers focused on Retinal Imaging and Analysis (10 papers), Advanced Image Processing Techniques (6 papers) and Advanced Image Fusion Techniques (5 papers). Weihao Gao collaborates with scholars based in China, United States and Macao. Weihao Gao's co-authors include Sewoong Oh, Pramod Viswanath, Sreeram Kannan, Venugopal V. Veeravalli, Shaofeng Zou, Hao Zhang, Na Yin, Xiaojie Wu, Yue Cao and Lifei Chen and has published in prestigious journals such as Scientific Reports, IEEE Transactions on Information Theory and ACS Applied Materials & Interfaces.

In The Last Decade

Weihao Gao

29 papers receiving 229 citations

Hit Papers

A predictive machine learning force-field framework for l... 2025 2026 2025 5 10 15 20 25
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. A predictive machine learning force-field framework for liquid electrolyte development
    2025 29 citations Sheng Gong, Zhenliang Mu et al. Nature Machine Intelligence profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Weihao Gao China 8 84 37 37 30 27 36 240
Yuanping Zhang China 13 20 0.2× 37 1.0× 33 0.9× 9 0.3× 16 0.6× 43 483
Aurora Torrente Spain 9 54 0.6× 17 0.5× 27 0.7× 27 0.9× 16 0.6× 17 299
Federico Errica Italy 6 182 2.2× 58 1.6× 49 1.3× 10 0.3× 4 0.1× 17 322
Weikang Li China 12 213 2.5× 16 0.4× 42 1.1× 18 0.6× 4 0.1× 45 395
Min Sha Australia 6 65 0.8× 21 0.6× 20 0.5× 23 0.8× 4 0.1× 41 171
Giorgos Borboudakis Greece 8 91 1.1× 109 2.9× 17 0.5× 22 0.7× 11 0.4× 14 323
Adityanarayanan Radhakrishnan United States 8 57 0.7× 10 0.3× 27 0.7× 15 0.5× 3 0.1× 14 282
Jiajing Xu China 8 41 0.5× 9 0.2× 79 2.1× 10 0.3× 24 0.9× 22 187

Countries citing papers authored by Weihao Gao

Since Specialization
Citations

This map shows the geographic impact of Weihao Gao'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 Weihao Gao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Weihao Gao more than expected).

Fields of papers citing papers by Weihao Gao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Weihao Gao. 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 Weihao Gao. The network helps show where Weihao Gao may publish in the future.

Co-authorship network of co-authors of Weihao Gao

This figure shows the co-authorship network connecting the top 25 collaborators of Weihao Gao. A scholar is included among the top collaborators of Weihao Gao based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Weihao Gao. Weihao Gao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Gong, Sheng, Zhenliang Mu, Hongyi Wang, et al.. (2025). A predictive machine learning force-field framework for liquid electrolyte development. Nature Machine Intelligence. 7(4). 543–552. 29 indexed citations breakdown →
2.
Gao, Weihao, et al.. (2025). Revisiting the numerical feature embeddings structure in neural network-based tabular modelling. Knowledge-Based Systems. 330. 114697–114697. 1 indexed citations
3.
Wang, Hongyi, Jinzhe Liang, Li Zhai, et al.. (2025). CrysToGraph: A Comprehensive Predictive Model for Crystal Material Properties and the Benchmark. Battery energy. 4(4). 1 indexed citations
4.
Zheng, Tianze, Wenzhi Ma, Wen Yan, et al.. (2025). Enhancing GPU‐Acceleration in the Python‐Based Simulations of Chemistry Frameworks. Wiley Interdisciplinary Reviews Computational Molecular Science. 15(2). 10 indexed citations
5.
Gao, Weihao, Lei Shao, Li Dong, et al.. (2024). Fundus photograph-based cataract evaluation network using deep learning. Frontiers in Physics. 11. 2 indexed citations
6.
Gao, Weihao, et al.. (2024). Enhancing ophthalmology medical record management with multi-modal knowledge graphs. Scientific Reports. 14(1). 23221–23221. 4 indexed citations
7.
8.
9.
Gao, Weihao, Wenbin Luo, Xiaolong Yin, et al.. (2024). AMD-SD: An Optical Coherence Tomography Image Dataset for wet AMD Lesions Segmentation. Scientific Data. 11(1). 1014–1014. 7 indexed citations
10.
Gao, Weihao, et al.. (2024). OphGLM: An ophthalmology large language-and-vision assistant. Artificial Intelligence in Medicine. 157. 103001–103001. 12 indexed citations
11.
Gao, Weihao, et al.. (2024). Evaluating retinal blood vessels for predicting white matter hyperintensities in ischemic stroke: A deep learning approach. Journal of Stroke and Cerebrovascular Diseases. 33(12). 108070–108070.
12.
Zhang, Yongjun, et al.. (2024). Dual-branch feature fusion dehazing network via multispectral channel attention. International Journal of Machine Learning and Cybernetics. 15(7). 2655–2671.
13.
Kahya, Ercan, et al.. (2023). Beyond the ordinary metrics on the evaluation of historical Euro-CORDEX simulations over Türkiye: the mutual information approach. Theoretical and Applied Climatology. 153(1-2). 829–851. 1 indexed citations
14.
Gao, Weihao, et al.. (2023). A novel attention-based network for single image dehazing. The Visual Computer. 40(8). 5681–5693. 1 indexed citations
15.
Zhang, Xuexue, et al.. (2023). Sparse representation scheme with enhanced medium pixel intensity for face recognition. CAAI Transactions on Intelligence Technology. 9(1). 116–127. 1 indexed citations
16.
Gao, Weihao, et al.. (2019). Learning one-hidden-layer neural networks under general input distributions. International Conference on Artificial Intelligence and Statistics. 1950–1959. 2 indexed citations
17.
Gao, Weihao, et al.. (2018). Rate Distortion For Model Compression:From Theory To Practice. International Conference on Machine Learning. 2102–2111. 1 indexed citations
18.
Jiao, Jiantao, Weihao Gao, & Yanjun Han. (2018). The Nearest Neighbor Information Estimator is Adaptively Near Minimax Rate-Optimal. arXiv (Cornell University). 31. 3156–3167. 6 indexed citations
19.
Gao, Weihao, Sreeram Kannan, Sewoong Oh, & Pramod Viswanath. (2017). Estimating Mutual Information for Discrete-Continuous Mixtures. arXiv (Cornell University). 30. 5986–5997. 20 indexed citations
20.
Gao, Weihao, Sewoong Oh, & Pramod Viswanath. (2017). Demystifying fixed k-nearest neighbor information estimators. 1267–1271. 23 indexed citations

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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