Philip L. H. Yu

4.5k total citations · 1 hit paper
166 papers, 2.7k citations indexed

About

Philip L. H. Yu is a scholar working on Artificial Intelligence, Statistics and Probability and Finance. According to data from OpenAlex, Philip L. H. Yu has authored 166 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Artificial Intelligence, 42 papers in Statistics and Probability and 36 papers in Finance. Recurrent topics in Philip L. H. Yu's work include Financial Risk and Volatility Modeling (29 papers), Statistical Methods and Inference (18 papers) and Financial Markets and Investment Strategies (14 papers). Philip L. H. Yu is often cited by papers focused on Financial Risk and Volatility Modeling (29 papers), Statistical Methods and Inference (18 papers) and Financial Markets and Investment Strategies (14 papers). Philip L. H. Yu collaborates with scholars based in Hong Kong, United States and China. Philip L. H. Yu's co-authors include Mike K. P. So, Paul H. Lee, Charles W. Slemenda, J. C. Christian, C. Conrad Johnston, Mayer Alvo, Jianhua Zhao, Jia Wu, Weixiong Zhang and Di Jin and has published in prestigious journals such as SHILAP Revista de lepidopterología, Hepatology and Analytical Biochemistry.

In The Last Decade

Philip L. H. Yu

153 papers receiving 2.6k citations

Hit Papers

A Survey of Community Detection Approaches: From Statisti... 2021 2026 2022 2024 2021 50 100 150 200 250
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 Survey of Community Detection Approaches: From Statistical Modeling to Deep Learning
    2021 259 citations Philip L. H. Yu et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Philip L. H. Yu Hong Kong 28 715 405 370 335 308 166 2.7k
Dimitris Karlis Greece 30 927 1.3× 691 1.7× 1.3k 3.6× 525 1.6× 140 0.5× 124 3.3k
Sangit Chätterjee United States 18 236 0.3× 337 0.8× 225 0.6× 188 0.6× 49 0.2× 75 1.6k
Tian Zheng China 33 345 0.5× 237 0.6× 244 0.7× 137 0.4× 1.4k 4.7× 346 4.7k
Aloïs Kneip Germany 29 340 0.5× 870 2.1× 879 2.4× 213 0.6× 127 0.4× 60 2.8k
Paulo Lisböa United Kingdom 31 1.1k 1.5× 119 0.3× 132 0.4× 27 0.1× 396 1.3× 181 3.6k
Zhiliang Ying United States 39 939 1.3× 234 0.6× 2.1k 5.7× 109 0.3× 436 1.4× 139 4.8k
Campbell B. Read United States 11 308 0.4× 156 0.4× 700 1.9× 86 0.3× 138 0.4× 37 2.4k
Youngjo Lee South Korea 29 383 0.5× 419 1.0× 1.3k 3.5× 55 0.2× 145 0.5× 192 3.6k
Joe Whittaker United Kingdom 18 708 1.0× 133 0.3× 509 1.4× 74 0.2× 227 0.7× 57 2.1k
Lisa R. Goldberg United States 20 403 0.6× 383 0.9× 156 0.4× 684 2.0× 136 0.4× 92 2.4k

Countries citing papers authored by Philip L. H. Yu

Since Specialization
Citations

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

Fields of papers citing papers by Philip L. H. Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Philip L. H. Yu. 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 Philip L. H. Yu. The network helps show where Philip L. H. Yu may publish in the future.

Co-authorship network of co-authors of Philip L. H. Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Philip L. H. Yu. A scholar is included among the top collaborators of Philip L. H. Yu 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 Philip L. H. Yu. Philip L. H. Yu 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.
Peng, Cheng-Zhi, Philip L. H. Yu, Jian‐Liang Lu, et al.. (2025). Opportunistic Detection of Hepatocellular Carcinoma Using Noncontrast CT and Deep Learning Artificial Intelligence. Journal of the American College of Radiology. 22(3). 249–259. 2 indexed citations
2.
Ruggeri, Fabrizio, David Banks, William S. Cleveland, et al.. (2025). Is There a Future for Stochastic Modeling in Business and Industry in the Era of Machine Learning and Artificial Intelligence?. Applied Stochastic Models in Business and Industry. 41(2).
3.
Zhang, Tianyu, et al.. (2025). Generative artificial intelligence in K-12 education: A systematic review. Research and Practice in Technology Enhanced Learning. 21. 34–34.
4.
Zhao, Ruibin, et al.. (2025). Enhancing language learning through generative AI feedback on picture-cued writing tasks. Computers and Education Artificial Intelligence. 9. 100450–100450.
5.
Sun, Daner, et al.. (2025). Designing a generative AI enabled learning environment for mathematics word problem solving in primary schools: Learning performance, attitudes and interaction. Computers and Education Artificial Intelligence. 9. 100438–100438. 2 indexed citations
6.
Lo, Chung Kwan, et al.. (2024). Exploring the application of ChatGPT in ESL/EFL education and related research issues: a systematic review of empirical studies. Smart Learning Environments. 11(1). 29 indexed citations
7.
Hui, Rex Wan‐Hin, K.W. Chiu, Ho Ming Cheng, et al.. (2024). Multimodal multiphasic preoperative image-based deep-learning predicts HCC outcomes after curative surgery. Hepatology. 82(2). 344–356. 1 indexed citations
8.
Yu, Philip L. H., et al.. (2024). On buffered moving average models. Journal of Time Series Analysis. 46(4). 599–622.
9.
10.
Yu, Philip L. H., et al.. (2023). Variable selection for high-dimensional incomplete data. Computational Statistics & Data Analysis. 192. 107877–107877. 1 indexed citations
11.
Hu, Xuming, et al.. (2022). CHEF: A Pilot Chinese Dataset for Evidence-Based Fact-Checking. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 3362–3376. 13 indexed citations
12.
You, Jia, Philip L. H. Yu, Anderson Chun On Tsang, et al.. (2021). 3D dissimilar-siamese-u-net for hyperdense Middle cerebral artery sign segmentation. Computerized Medical Imaging and Graphics. 90. 101898–101898. 10 indexed citations
13.
Yu, Philip L. H., et al.. (2020). An alternative nonparametric tail risk measure. Quantitative Finance. 21(4). 685–696.
14.
Chiu, K.W., Varut Vardhanabhuti, Philip L. H. Yu, et al.. (2020). Detection of COVID-19 Using Deep Learning Algorithms on Chest Radiographs. Journal of Thoracic Imaging. 35(6). 369–376. 11 indexed citations
15.
Xia, Congying, Chenwei Zhang, Xiaohui Yan, Yi Chang, & Philip L. H. Yu. (2018). Zero-shot User Intent Detection via Capsule Neural Networks. 3090–3099. 129 indexed citations
16.
Fung, Joseph K. W. & Philip L. H. Yu. (2010). Order imbalance and the dynamics of index and futures prices. The HKU Scholars Hub (University of Hong Kong). 17 indexed citations
17.
Lam, Kin, Philip L. H. Yu, & Ling Xin. (2009). Accumulator pricing. The HKU Scholars Hub (University of Hong Kong). 72–79.
18.
Yu, Philip L. H., et al.. (2006). ICLUS: A robust and scalable clustering model for time series via independent component analysis. International Journal of Systems Science. 37(13). 987–1001. 4 indexed citations
19.
Yu, Philip L. H., et al.. (2001). BAYESIAN ANALYSIS OF WANDERING VECTOR MODELS FOR DISPLAYING RANKING DATA. Statistica Sinica. 11(2). 445–461. 4 indexed citations
20.
Friedman, Richard D., et al.. (1980). Heritable Salivary Proteins and Dental Disease. Human Heredity. 30(6). 372–375. 13 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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