Jana Shafi

85 papers receiving 1.6k citations

Jana Shafi's Hit Papers

AI student success predictor: Enhancing personalized learning in campus management systems 2024 · 49 citations
490+1Years since publication10203040

Peers

Jana Shafi
Comparison fields: 5 of 150
  • Health Informatics 40
  • Health Information Management 115
  • Artificial Intelligence 457
  • Computer Networks and Communications 293
  • Computer Vision and Pattern Recognition 262
Replace Ramesh Chandra Poonia with:
Ramesh Chandra Poonia India
Vicente García‐Díaz Spain
Amandeep Kaur India
Atta Rahman Saudi Arabia
Mohammad Shorfuzzaman Saudi Arabia
Dharmendra Singh Rajput India
M. M. Kamruzzaman Saudi Arabia
Ajay Rana India
Flavio Villanustre United States
R. Manikandan India
Jana Shafi relative to Ramesh Chandra Poonia India Ramesh Chandra Poonia's profile →
Citations per field
00.5×
Ramesh Chandra Poonia · 1×
Citations per year

Countries citing papers authored by Jana Shafi

Since Specialization
Citations

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

Fields of papers citing papers by Jana Shafi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 89 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2022141
2 202172
3 202265
4 202264
5 202261
6 202160
7 202259
8
AI student success predictor: Enhancing personalized learning in campus management systems
Hit paper breakdown →
202449
9 202148
10 202447
11 202247
12 202245
13 202243
14 202140
15 202239
16 202239
17 202338
18 202232
19 202329
20 202228

About Jana Shafi

Jana Shafi is a scholar working on Artificial Intelligence, Biomedical Engineering, Computer Networks and Communications, Mechanical Engineering and Information Systems, having authored 89 papers that have together received 1.7k indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (12 papers), Nanofluid Flow and Heat Transfer (9 papers), AI in cancer detection (8 papers), Brain Tumor Detection and Classification (8 papers), Phase Change Materials Research (8 papers), Blockchain Technology Applications and Security (7 papers), Solar Thermal and Photovoltaic Systems (6 papers) and Artificial Intelligence in Healthcare (5 papers). The work is most often cited by research in Health Informatics (40 citations), Health Information Management (115 citations), Artificial Intelligence (457 citations), Computer Networks and Communications (293 citations) and Computer Vision and Pattern Recognition (262 citations). Jana Shafi has collaborated with scholars based in Saudi Arabia, India and South Korea. Frequent co-authors include Muhammad Fazal Ijaz, Marcin Woźniak, Kavita Kavita, Sahil Verma, Parvathaneni Naga Srinivasu, Jaeyoung Choi, Yogesh Kumar, Shalli Rani, S. Phani Praveen and Akash Kumar Bhoi. Their work appears in journals such as Scientific Reports, Sensors, Computational Intelligence and Neuroscience, IEEE Access and Journal of Energy Storage.

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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