Ishani Mondal

444 citations
17 papers · 87 indexed · h-index 6
Topics
Topic Modeling (8 papers)Biomedical Text Mining and Ontologies (4 papers)Computational Drug Discovery Methods (3 papers)
Journals
National Conference on Artificial IntelligenceProceedings of the AAAI Conference on Artificial Intelligence

In The Last Decade

Ishani Mondal

13 papers receiving 78 citations

Peers

Ishani Mondal
Comparison fields: 5 of 42
  • Artificial Intelligence 48
  • Molecular Biology 31
  • Computational Theory and Mathematics 26
  • Computer Vision and Pattern Recognition 14
  • Electrical and Electronic Engineering 6
Replace Xiaobo Liang with:
Xiaobo Liang China
Mark-A. Krogel Germany
Marco A. Valenzuela-Escárcega United States
Tom Rainforth United Kingdom
Will Smart New Zealand
Valérie Gauthier–Umaña Colombia
Takayoshi Shoudai Japan
Irina Matveeva United States
Pavel Klinov United Kingdom
Ishani Mondal relative to Xiaobo Liang China Xiaobo Liang's profile →
Citations per field
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Xiaobo Liang · 1×
Citations per year

Countries citing papers authored by Ishani Mondal

Since Specialization
Citations

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

Fields of papers citing papers by Ishani Mondal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ishani Mondal

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

All Works

17 of 17 papers shown
#WorkIndexed citations
1 0
2 1
3 1
4 2
5 7
6 7
7 1
8 17
9 2
10
BERTKG-DDI: Towards Incorporating Entity-specific Knowledge Graph Information in Predicting Drug-Drug Interactions.
4
11 4
12 1
13 1
14 25
15 8
16 1
17 5

About Ishani Mondal

Ishani Mondal is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Human-Computer Interaction, having authored 17 papers that have together received 87 indexed citations. Recurring topics across this work include Topic Modeling (8 papers), Biomedical Text Mining and Ontologies (4 papers) and Computational Drug Discovery Methods (3 papers). The work is most often cited by research in Computational Theory and Mathematics (26 citations), Artificial Intelligence (48 citations) and Computer Vision and Pattern Recognition (14 citations). Ishani Mondal has collaborated with scholars based in India, United States and Ireland. Frequent co-authors include Charles Jochim, Yufang Hou, Pawan Goyal, Sudeshna Sarkar, Md Shad Akhtar, Tanmoy Chakraborty, Sudipta Ghosh, Debasis Ganguly, Jordan Boyd‐Graber and Monojit Choudhury. Their work appears in journals such as National Conference on Artificial Intelligence and Proceedings of the AAAI Conference on Artificial Intelligence.

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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