Kaustuv Chaudhuri
- Artificial Intelligence
- Computational Theory and Mathematics top 10%
- Computer Networks and Communications
- Sociology and Political Science
- Information Systems
- Co-authors
- Frank PfenningDamien DoligezStephan MerzLeslie LamportBor-Yuh Evan ChangJoëlle DespeyrouxElaine PimentelCarlos Olarte
- Topics
- Logic, programming, and type systems (10 papers)Formal Methods in Verification (9 papers)Logic, Reasoning, and Knowledge (6 papers)
- Journals
- SHILAP Revista de lepidopterologíaTheoretical Computer ScienceJournal of Automated Reasoning
- Partner nations
- FranceUnited StatesBrazil
In The Last Decade
Kaustuv Chaudhuri
8 papers receiving 49 citations
Peers
Comparison fields: 5 of 13
- Artificial Intelligence 56
- Computational Theory and Mathematics 37
- Computer Networks and Communications 10
- Sociology and Political Science 3
- Information Systems 3
Countries citing papers authored by Kaustuv Chaudhuri
This map shows the geographic impact of Kaustuv Chaudhuri'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 Kaustuv Chaudhuri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kaustuv Chaudhuri more than expected).
Fields of papers citing papers by Kaustuv Chaudhuri
This network shows the impact of papers produced by Kaustuv Chaudhuri. 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 Kaustuv Chaudhuri. The network helps show where Kaustuv Chaudhuri may publish in the future.
Co-authorship network of co-authors of Kaustuv Chaudhuri
This figure shows the co-authorship network connecting the top 25 collaborators of Kaustuv Chaudhuri. A scholar is included among the top collaborators of Kaustuv Chaudhuri 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 Kaustuv Chaudhuri. Kaustuv Chaudhuri is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 4 | |
| 3 | 3 | |
| 4 | 5 | |
| 5 | 0 | |
| 6 | 2 | |
| 7 | Compact Proof Certicates for Linear Logic | 1 |
| 8 | 6 | |
| 9 | 21 | |
| 10 | The focused inverse method for linear logic | 14 |
About Kaustuv Chaudhuri
Kaustuv Chaudhuri is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Software, having authored 10 papers that have together received 58 indexed citations. Recurring topics across this work include Logic, programming, and type systems (10 papers), Formal Methods in Verification (9 papers) and Logic, Reasoning, and Knowledge (6 papers). The work is most often cited by research in Computational Theory and Mathematics (37 citations), Artificial Intelligence (56 citations) and Theoretical Computer Science (1 citation). Kaustuv Chaudhuri has collaborated with scholars based in France, United States and Brazil. Frequent co-authors include Frank Pfenning, Damien Doligez, Stephan Merz, Leslie Lamport, Bor-Yuh Evan Chang, Joëlle Despeyroux, Elaine Pimentel and Carlos Olarte. Their work appears in journals such as SHILAP Revista de lepidopterología, Theoretical Computer Science and Journal of Automated Reasoning.
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.