Anupama Chadha

408 citations
15 papers · 154 indexed · h-index 6
Topics
Advanced Clustering Algorithms Research (4 papers)Face and Expression Recognition (3 papers)Data Mining Algorithms and Applications (3 papers)
Journals
Computational IntelligenceInternational Journal of Advanced Computer Science and ApplicationsInternational Journal of Database Theory and Application
Partner nations
IndiaNepalOman

In The Last Decade

Anupama Chadha

9 papers receiving 122 citations

Peers

Anupama Chadha
Comparison fields: 5 of 52
  • Computer Science Applications 82
  • Artificial Intelligence 70
  • Information Systems 64
  • Health Information Management 24
  • Computer Networks and Communications 20
Replace Zailani Abdullah with:
Zailani Abdullah Malaysia
Emad Al‐Shawakfa Jordan
Diego García‐Saiz Spain
Mirza Suljić Bosnia and Herzegovina
Edin Osmanbegović Bosnia and Herzegovina
Shade O. Kuyoro Nigeria
Julien Tane Germany
Sadia Ali Pakistan
Antonius Rachmat Chrismanto Indonesia
Mahiéddine Djoudi Algeria
Anupama Chadha relative to Zailani Abdullah Malaysia Zailani Abdullah's profile →
Citations per field
00.5×2.7×
Zailani Abdullah · 1×
Citations per year

Countries citing papers authored by Anupama Chadha

Since Specialization
Citations

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

Fields of papers citing papers by Anupama Chadha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anupama Chadha

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

All Works

15 of 15 papers shown
#WorkIndexed citations
1 0
2 0
3 5
4 16
5 1
6 0
7 2
8 0
9 2
10 5
11 0
12 1
13 17
14
Mining Association Rules in Student's Assessment Data
31
15 74

About Anupama Chadha

Anupama Chadha is a scholar working on Computer Science Applications, Human-Computer Interaction and Signal Processing, having authored 15 papers that have together received 154 indexed citations. Recurring topics across this work include Advanced Clustering Algorithms Research (4 papers), Face and Expression Recognition (3 papers) and Data Mining Algorithms and Applications (3 papers). The work is most often cited by research in Computer Science Applications (82 citations), Health Information Management (24 citations) and Information Systems (64 citations). Anupama Chadha has collaborated with scholars based in India, Nepal and Oman. Frequent co-authors include Varun Kumar, Suresh Kumar, Rajesh Singh, Amandeep Nagpal, Anand Sharma, Gaurav Raj, Melanie Lourens, Durgaprasad Gangodkar, Bhasker Pant and Gaurav Dubey. Their work appears in journals such as Computational Intelligence, International Journal of Advanced Computer Science and Applications and International Journal of Database Theory and Application.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026