Haruna Chiroma

5.7k citations
132 papers · 3.6k indexed · 4 hit papers · h-index 33
Topics
IoT and Edge/Fog Computing (13 papers)Market Dynamics and Volatility (13 papers)Metaheuristic Optimization Algorithms Research (12 papers)
Journals
SHILAP Revista de lepidopterologíaPLoS ONEScientific Reports

In The Last Decade

Haruna Chiroma

126 papers receiving 3.4k citations

Hit Papers

The role of big data in smart city20162026201920222016201920202021200400600

Peers

Haruna Chiroma
Comparison fields: 5 of 160
  • Artificial Intelligence 1.2k
  • Information Systems 841
  • Computer Networks and Communications 791
  • Electrical and Electronic Engineering 504
  • Computer Vision and Pattern Recognition 411
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Haruna Chiroma relative to Awais Ahmad South Korea Awais Ahmad's profile →
Citations per field
00.5×1.5×
Awais Ahmad · 1×
Citations per year

Countries citing papers authored by Haruna Chiroma

Since Specialization
Citations

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

Fields of papers citing papers by Haruna Chiroma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Haruna Chiroma

This figure shows the co-authorship network connecting the top 25 collaborators of Haruna Chiroma. A scholar is included among the top collaborators of Haruna Chiroma 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 Haruna Chiroma. Haruna Chiroma 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
#WorkIndexed citations
1 0
2 0
3 5
4 2
5 4
6 14
7 2
8 46
9 2
10 45
11 27
12 110
13 37
14 5
15 30
16
Neuro-genetic model for crude oil price prediction while considering the impact of uncertainties
6
17
Intelligent Decision Support Systems for Oil Price Forecasting
2
18
A framework for the design of cloud based Collaborative Virtual Environment architecture
12
19
Performance evaluation of TCP congestion control algorithms throughput for CVE based on cloud computing model
1
20 10

About Haruna Chiroma

Haruna Chiroma is a scholar working on Health Informatics, Signal Processing and Computer Vision and Pattern Recognition, having authored 132 papers that have together received 3.6k indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (13 papers), Market Dynamics and Volatility (13 papers) and Metaheuristic Optimization Algorithms Research (12 papers). The work is most often cited by research in Media Technology (408 citations), Transportation (293 citations) and Artificial Intelligence (1.2k citations). Haruna Chiroma has collaborated with scholars based in Nigeria, Malaysia and Saudi Arabia. Frequent co-authors include Shafi’i Muhammad Abdulhamid, Tutut Herawan, Mohamed Hashem, Kayode S. Adewole, Abdullah Gani, Adamu Abubakar, Ibrar Yaqoob, Ejaz Ahmed, Nor Badrul Anuar and Victor Chang. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

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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