I. Yu

12 papers receiving 172 citations

Peers

I. Yu
Comparison fields: 5 of 64
  • Modeling and Simulation 23
  • Critical Care and Intensive Care Medicine 17
  • Pulmonary and Respiratory Medicine 64
  • Infectious Diseases 31
  • Applied Microbiology and Biotechnology 3
Replace Hua-jian Xu with:
Hua-jian Xu China
Arnaud Robert Belgium
Lin Luo China
Graham Gibson United States
Vahid Khaloo Iran
Michail Mamalakis United Kingdom
B. Shi China
Chaolin Huang China
Luca Mingardi United States
N’dri Juliette Kadiane-Oussou France
I. Yu relative to Hua-jian Xu China Hua-jian Xu's profile →
Citations per field
00.5×3.3×
Hua-jian Xu · 1×
Citations per year

Countries citing papers authored by I. Yu

Since Specialization
Citations

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

Fields of papers citing papers by I. Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside I. Yu, 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 I. Yu Line = papers co-authored together I. Yu links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 2007124
2 202121
3 20207
4 20225
5 20204
6 20223
7 20203
8
An Overlap Measure based on Species Proportions
20013
9 20201
10 20211
11 20061
12
Mean-Variance Analysis in Bayesian Optimization under Uncertainty
20211
13 20210

About I. Yu

I. Yu is a scholar working on Artificial Intelligence, Management Science and Operations Research, Computational Theory and Mathematics, Statistics, Probability and Uncertainty and Biomedical Engineering, having authored 13 papers that have together received 174 indexed citations. Recurring topics across this work include Machine Learning and Algorithms (4 papers), Advanced Multi-Objective Optimization Algorithms (3 papers), Advanced Statistical Methods and Models (2 papers), Neural dynamics and brain function (2 papers), Photoreceptor and optogenetics research (2 papers), Probabilistic and Robust Engineering Design (2 papers), Machine Learning and Data Classification (2 papers) and Molecular Communication and Nanonetworks (2 papers). The work is most often cited by research in Modeling and Simulation (23 citations), Critical Care and Intensive Care Medicine (17 citations), Pulmonary and Respiratory Medicine (64 citations), Infectious Diseases (31 citations) and Applied Microbiology and Biotechnology (3 citations). I. Yu has collaborated with scholars based in Japan, Israel and Hong Kong. Frequent co-authors include Xiaoping Tang, Nelson Lee, David S.C. Hui, Joseph J.�Y. Sung, T W Wong, Nan Zhong, Zhitong Huang, Kelvin Tsoi, Ichiro Takeuchi and Kei Yura. Their work appears in journals such as Neural Computation, Communications Biology, Clinical Infectious Diseases, IEEE Access and Annals of the Institute of Statistical Mathematics.

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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