Yunhan Jia

752 citations
16 papers · 386 indexed · h-index 10
Topics
Adversarial Robustness in Machine Learning (5 papers)Advanced Malware Detection Techniques (4 papers)Security and Verification in Computing (3 papers)
Partner nations
United StatesChinaMexico

In The Last Decade

Yunhan Jia

15 papers receiving 373 citations

Peers

Yunhan Jia
Comparison fields: 5 of 46
  • Signal Processing 199
  • Artificial Intelligence 178
  • Computer Networks and Communications 142
  • Information Systems 99
  • Computer Vision and Pattern Recognition 65
Replace Ilaria Matteucci with:
Ilaria Matteucci Italy
Phu H. Phung United States
Chaoran Li Australia
Michele Carminati Italy
Yisroel Mirsky Israel
Qingchuan Zhao Hong Kong
Les Miller United States
Nargiz Humbatova Switzerland
Junyang Qiu China
Yanjie Zhao China
Yunhan Jia relative to Ilaria Matteucci Italy Ilaria Matteucci's profile →
Citations per field
00.5×3.6×
Ilaria Matteucci · 1×
Citations per year

Countries citing papers authored by Yunhan Jia

Since Specialization
Citations

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

Fields of papers citing papers by Yunhan Jia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Yunhan Jia

This figure shows the co-authorship network connecting the top 25 collaborators of Yunhan Jia. A scholar is included among the top collaborators of Yunhan Jia 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 Yunhan Jia. Yunhan Jia is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
#WorkIndexed citations
1 0
2 3
3 2
4 9
5 13
6 4
7
Fooling Detection Alone is Not Enough: Adversarial Attack against Multiple Object Tracking
27
8 2
9 174
10 38
11 25
12 20
13 29
14 17
15 19
16 4

About Yunhan Jia

Yunhan Jia is a scholar working on Signal Processing, Toxicology and Software, having authored 16 papers that have together received 386 indexed citations. Recurring topics across this work include Adversarial Robustness in Machine Learning (5 papers), Advanced Malware Detection Techniques (4 papers) and Security and Verification in Computing (3 papers). The work is most often cited by research in Signal Processing (199 citations), Software (45 citations) and Computer Networks and Communications (142 citations). Yunhan Jia has collaborated with scholars based in United States, China and Mexico. Frequent co-authors include Qi Alfred Chen, Z. Morley Mao, Earlence Fernandes, Atul Prakash, Amir Rahmati, Ding Zhao, Yuru Shao, Zhiyun Qian, Junjie Shen and Zeyu Mao. Their work appears in journals such as Journal of Pragmatics, International Journal of Intelligent Systems and arXiv (Cornell University).

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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