Srivatsan Laxman
- Artificial Intelligence top 5%
- Information Systems top 2%
- Signal Processing top 2%
- Computer Networks and Communications top 10%
- Computational Theory and Mathematics top 5%
- Co-authors
- P. S. SastryUnnikrishnan KuzhiumparambilAdam SmithRaghav BhaskarAbhradeep ThakurtaRyen W. WhiteNiloy GangulyMonojit Choudhury
- Topics
- Data Mining Algorithms and Applications (13 papers)Algorithms and Data Compression (7 papers)Rough Sets and Fuzzy Logic (5 papers)
- Journals
- IEEE Transactions on Knowledge and Data EngineeringData Mining and Knowledge DiscoveryKnowledge and Information Systems
- Partner nations
- IndiaUnited StatesUnited Kingdom
In The Last Decade
Srivatsan Laxman
26 papers receiving 739 citations
Peers
Comparison fields: 5 of 79
- Artificial Intelligence 445
- Information Systems 434
- Signal Processing 338
- Computer Networks and Communications 146
- Computational Theory and Mathematics 97
Countries citing papers authored by Srivatsan Laxman
This map shows the geographic impact of Srivatsan Laxman'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 Srivatsan Laxman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Srivatsan Laxman more than expected).
Fields of papers citing papers by Srivatsan Laxman
This network shows the impact of papers produced by Srivatsan Laxman. 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 Srivatsan Laxman. The network helps show where Srivatsan Laxman may publish in the future.
Co-authorship network of co-authors of Srivatsan Laxman
This figure shows the co-authorship network connecting the top 25 collaborators of Srivatsan Laxman. A scholar is included among the top collaborators of Srivatsan Laxman 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 Srivatsan Laxman. Srivatsan Laxman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 11 | |
| 2 | Verito: A Practical System for Transparency and Accountability in Virtual Economies. | 1 |
| 3 | 2 | |
| 4 | 6 | |
| 5 | 3 | |
| 6 | 13 | |
| 7 | 15 | |
| 8 | 4 | |
| 9 | 27 | |
| 10 | 6 | |
| 11 | 11 | |
| 12 | 146 | |
| 13 | Pattern Mining for Future Attacks | 10 |
| 14 | 4 | |
| 15 | 77 | |
| 16 | 49 | |
| 17 | 81 | |
| 18 | Fast algorithms for frequent episode discovery in event sequences | 6 |
| 19 | 2 | |
| 20 | Generalized frequent episodes in Event Sequences | 4 |
About Srivatsan Laxman
Srivatsan Laxman is a scholar working on Signal Processing, Information Systems and Artificial Intelligence, having authored 28 papers that have together received 798 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (13 papers), Algorithms and Data Compression (7 papers) and Rough Sets and Fuzzy Logic (5 papers). The work is most often cited by research in Signal Processing (338 citations), Information Systems (434 citations) and Artificial Intelligence (445 citations). Srivatsan Laxman has collaborated with scholars based in India, United States and United Kingdom. Frequent co-authors include P. S. Sastry, Unnikrishnan Kuzhiumparambil, Adam Smith, Raghav Bhaskar, Abhradeep Thakurta, Ryen W. White, Niloy Ganguly, Monojit Choudhury, Rishiraj Saha Roy and Naren Ramakrishnan. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, Data Mining and Knowledge Discovery and Knowledge and Information Systems.
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.