Arnab Bhattacharya
- Artificial Intelligence top 5%
- Molecular Biology
- Information Systems top 5%
- Signal Processing top 5%
- Computer Networks and Communications top 10%
- Co-authors
- Niko BeerenwinkelOsvaldo ZagordiNicholas ErikssonSamuel MaddenAmbuj K. SinghPraveen Kumar SinghAmey KarkareKripabandhu Ghosh
- Topics
- Data Management and Algorithms (20 papers)Topic Modeling (8 papers)Artificial Intelligence in Law (8 papers)
- Partner nations
- IndiaUnited StatesAustralia
In The Last Decade
Arnab Bhattacharya
62 papers receiving 732 citations
Peers
Comparison fields: 5 of 117
- Artificial Intelligence 230
- Molecular Biology 160
- Information Systems 157
- Signal Processing 122
- Computer Networks and Communications 114
Countries citing papers authored by Arnab Bhattacharya
This map shows the geographic impact of Arnab Bhattacharya'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 Arnab Bhattacharya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Arnab Bhattacharya more than expected).
Fields of papers citing papers by Arnab Bhattacharya
This network shows the impact of papers produced by Arnab Bhattacharya. 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 Arnab Bhattacharya. The network helps show where Arnab Bhattacharya may publish in the future.
Co-authorship network of co-authors of Arnab Bhattacharya
This figure shows the co-authorship network connecting the top 25 collaborators of Arnab Bhattacharya. A scholar is included among the top collaborators of Arnab Bhattacharya 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 Arnab Bhattacharya. Arnab Bhattacharya is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 3 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | Overview of the FIRE 2019 AILA Track: Artificial Intelligence for Legal Assistance. | 6 |
| 11 | Overview of the FIRE 2017 IRLeD Track: Information Retrieval from Legal Documents. | 9 |
| 12 | 9 | |
| 13 | SkyCover: Finding Range-Constrained Approximate Skylines with Bounded Quality Guarantees. | 3 |
| 14 | A Plant Identification System using Shape and Morphological Features on Segmented Leaflets: Team IITK, CLEF 2012. | 21 |
| 15 | Aggregate Skyline Join Queries: Skylines with Aggregate Operations over Multiple Relations | 3 |
| 16 | 15 | |
| 17 | Proceedings of the 8th international conference on Simulated evolution and learning | 3 |
| 18 | 38 | |
| 19 | 1 | |
| 20 | MIST: distributed indexing and querying in sensor networks using statistical models | 15 |
About Arnab Bhattacharya
Arnab Bhattacharya is a scholar working on Signal Processing, Geography, Planning and Development and Transportation, having authored 67 papers that have together received 768 indexed citations. Recurring topics across this work include Data Management and Algorithms (20 papers), Topic Modeling (8 papers) and Artificial Intelligence in Law (8 papers). The work is most often cited by research in Computer Science Applications (62 citations), Signal Processing (122 citations) and Virology (46 citations). Arnab Bhattacharya has collaborated with scholars based in India, United States and Australia. Frequent co-authors include Niko Beerenwinkel, Osvaldo Zagordi, Nicholas Eriksson, Samuel Madden, Ambuj K. Singh, Praveen Kumar Singh, Amey Karkare, Kripabandhu Ghosh, C. Oswald and Sayan Ranu. Their work appears in journals such as Journal of Biological Chemistry, BMC Bioinformatics and Physics of Fluids.
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.