Krishna Madhavan

2.2k citations
89 papers · 1.4k · h-index 18

Impact in

    • Online Learning and Analytics
    • E-Learning and Knowledge Management
    • Electrospun Nanofibers in Biomedical Applications
    • Nanoparticle-Based Drug Delivery

Papers in

Krishna Madhavan

79 papers receiving 1.4k citations

Peers

Krishna Madhavan
Comparison fields: 5 of 159
  • Computer Science Applications 350
  • Biomaterials 287
  • Health Information Management 49
  • Molecular Medicine 40
  • Urology 42
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Wanli Xing United States
Tatsuo Nakajima Japan
Matthew Cooper United States
Andreas Martin Seitz Germany
Stefan Kolb Switzerland
Jiyong Zhang China
Lijia Chen China
Shu‐Ling Wang Taiwan
Daniel A. McAdams United States
Quang Vinh Nguyễn Australia
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Citations per field
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Citations per year

Countries citing papers authored by Krishna Madhavan

Since Specialization
Citations

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

Fields of papers citing papers by Krishna Madhavan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Krishna Madhavan, 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 Krishna Madhavan Line = papers co-authored together Krishna Madhavan 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 2016248
2 2014143
3 2014126
4 2009111
5 2013100
6 201461
7 202046
8 201444
9 201340
10 201239
11 201037
12 201129
13 202029
14 202127
15 201518
16 199817
17 201317
18 201417
19 201616
20 201713

About Krishna Madhavan

Krishna Madhavan is a scholar working on Computer Science Applications, Media Technology, Biomedical Engineering, Information Systems and Information Systems and Management, having authored 89 papers that have together received 1.4k indexed citations. Recurring topics across this work include Online Learning and Analytics (19 papers), Experimental Learning in Engineering (9 papers), Scientific Computing and Data Management (9 papers), Engineering Education and Pedagogy (6 papers), Engineering Education and Curriculum Development (6 papers), Electrospun Nanofibers in Biomedical Applications (6 papers), E-Learning and Knowledge Management (6 papers) and Innovative Teaching and Learning Methods (6 papers). The work is most often cited by research in Computer Science Applications (350 citations), Biomaterials (287 citations), Health Information Management (49 citations), Molecular Medicine (40 citations) and Urology (42 citations). Krishna Madhavan has collaborated with scholars based in United States, India and Australia. Frequent co-authors include Heidi Diefes‐Dux, Farshid Marbouti, Mihaela Vorvoreanu, Xin Chen, Wei Tan, Dae‐Won Park, Dmitry Belchenko, Antonella Motta, Wei Tan and Robin Shandas. Their work appears in journals such as Neuro-Oncology, Journal of Engineering Education, Journal of Biomedical Materials Research Part B Applied Biomaterials, Cell Reports and IEEE Computer Graphics and Applications.

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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