Po Yang

7.9k citations
176 papers · 5.5k indexed · 3 hit papers · h-index 36

Po Yang

166 papers receiving 5.3k citations

Hit Papers

Comparison and Modelling of Country-level Microblog User ...5102017202620202023100200300400500

Peers

Po Yang
Comparison fields: 5 of 172
  • Computer Vision and Pattern Recognition 1.6k
  • Health Informatics 61
  • Artificial Intelligence 1.4k
  • Computer Networks and Communications 968
  • Health Information Management 169
Replace Marcin Woźniak with:
Marcin Woźniak Poland
Nianyin Zeng China
Weibo Liu China
V. Subramaniyaswamy India
Irfan Mehmood South Korea
Bijaya Ketan Panigrahi India
Usman Tariq Saudi Arabia
João Paulo Papa Brazil
Vasile Palade United Kingdom
Mehedi Masud Saudi Arabia
Po Yang relative to Marcin Woźniak Poland Marcin Woźniak's profile →
Citations per field
00.5×2.9×
Marcin Woźniak · 1×
Citations per year

Countries citing papers authored by Po Yang

Since Specialization
Citations

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

Fields of papers citing papers by Po Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20241
2 20245
3 202410
4 202311
5 20237
6 20225
7 20225
8 202210
9 202128
10 2021163
11 202111
12 202080
13 202066
14 201977
15 20197
16 2019212
17 201815
18 2018152
19 201861
20 200725

About Po Yang

Po Yang is a scholar working on Computational Mathematics, Computer Vision and Pattern Recognition and Health Information Management, having authored 176 papers that have together received 5.5k indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (23 papers), IoT and Edge/Fog Computing (17 papers), Smart Agriculture and AI (14 papers), Non-Invasive Vital Sign Monitoring (14 papers), Machine Learning in Healthcare (14 papers), Dementia and Cognitive Impairment Research (14 papers), Underwater Vehicles and Communication Systems (9 papers) and Domain Adaptation and Few-Shot Learning (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.6k citations), Health Informatics (61 citations) and Artificial Intelligence (1.4k citations). Po Yang has collaborated with scholars based in United Kingdom, China and Hong Kong. Frequent co-authors include Jun Qi, Yun Yang, Zhihan Lv, Khan Muhammad, Ping Li, Wenyan Wu, Dagan Feng, Xulong Wang, Jing Liu and Rujing Wang. Their work appears in journals such as IEEE Transactions on Industrial Informatics, IEEE Internet of Things Journal, IEEE Access, Future Generation Computer Systems and Computers & Electrical Engineering.

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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