Indrajit Bhattacharya
- Artificial Intelligence top 5%
- Information Systems top 10%
- Sociology and Political Science
- Computer Networks and Communications
- Management Science and Operations Research
- Co-authors
- Chiranjib BhattacharyyaHimabindu LakkarajuRoy Bar-HaimAmrita SahaNoam SlonimFrancesco DinuzzoSrujana MeruguAshish Verma
- Topics
- Topic Modeling (13 papers)Natural Language Processing Techniques (5 papers)Bayesian Methods and Mixture Models (3 papers)
- Journals
- SHILAP Revista de lepidopterologíaHuman Resources for HealthACM Transactions on Knowledge Discovery from Data
- Partner nations
- IndiaUnited StatesIsrael
In The Last Decade
Indrajit Bhattacharya
22 papers receiving 274 citations
Peers
Comparison fields: 5 of 53
- Artificial Intelligence 216
- Information Systems 82
- Sociology and Political Science 36
- Computer Networks and Communications 22
- Management Science and Operations Research 20
Countries citing papers authored by Indrajit Bhattacharya
This map shows the geographic impact of Indrajit 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 Indrajit Bhattacharya with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Indrajit Bhattacharya more than expected).
Fields of papers citing papers by Indrajit Bhattacharya
This network shows the impact of papers produced by Indrajit 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 Indrajit Bhattacharya. The network helps show where Indrajit Bhattacharya may publish in the future.
Co-authorship network of co-authors of Indrajit Bhattacharya
This figure shows the co-authorship network connecting the top 25 collaborators of Indrajit Bhattacharya. A scholar is included among the top collaborators of Indrajit 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 Indrajit Bhattacharya. Indrajit 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 | 3 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 3 | |
| 6 | 1 | |
| 7 | 9 | |
| 8 | 80 | |
| 9 | Proceedings of the Second ACM IKDD Conference on Data Sciences | 10 |
| 10 | 29 | |
| 11 | Healthcare Data Analytics on the Cloud | 5 |
| 12 | 9 | |
| 13 | 0 | |
| 14 | 2 | |
| 15 | 2 | |
| 16 | 7 | |
| 17 | 0 | |
| 18 | 19 | |
| 19 | The University of Maryland Senseval-3 system descriptions | 1 |
| 20 | 16 |
About Indrajit Bhattacharya
Indrajit Bhattacharya is a scholar working on Artificial Intelligence, General Social Sciences and Health Information Management, having authored 26 papers that have together received 299 indexed citations. Recurring topics across this work include Topic Modeling (13 papers), Natural Language Processing Techniques (5 papers) and Bayesian Methods and Mixture Models (3 papers). The work is most often cited by research in Artificial Intelligence (216 citations), Information Systems (82 citations) and Health Information Management (9 citations). Indrajit Bhattacharya has collaborated with scholars based in India, United States and Israel. Frequent co-authors include Chiranjib Bhattacharyya, Himabindu Lakkaraju, Roy Bar-Haim, Amrita Saha, Noam Slonim, Francesco Dinuzzo, Srujana Merugu, Ashish Verma, Shantanu Godbole and Ajay Gupta. Their work appears in journals such as SHILAP Revista de lepidopterología, Human Resources for Health and ACM Transactions on Knowledge Discovery from Data.
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.