J. Kevin Lanctot
- Artificial Intelligence top 5%
- Molecular Biology
- Computational Theory and Mathematics top 5%
- Computer Networks and Communications top 10%
- Genetics
- Co-authors
- B. John OommenLouxin ZhangBin MaMing LiEn‐hui YangSantosh PuttaJohn EksterowiczErin K. Bradley
- Topics
- Machine Learning and Algorithms (5 papers)Optimization and Search Problems (4 papers)Computational Drug Discovery Methods (3 papers)
- Cited by
- Computational Theory and MathematicsArtificial IntelligenceComputer Networks and Communications
- Journals
- Journal of Medicinal ChemistryInformation and ComputationJournal of Molecular Graphics and Modelling
- Partner nations
- CanadaUnited StatesSingapore
In The Last Decade
J. Kevin Lanctot
10 papers receiving 416 citations
Peers
Comparison fields: 5 of 75
- Artificial Intelligence 256
- Molecular Biology 205
- Computational Theory and Mathematics 147
- Computer Networks and Communications 146
- Genetics 38
Countries citing papers authored by J. Kevin Lanctot
This map shows the geographic impact of J. Kevin Lanctot'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 J. Kevin Lanctot with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites J. Kevin Lanctot more than expected).
Fields of papers citing papers by J. Kevin Lanctot
This network shows the impact of papers produced by J. Kevin Lanctot. 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 J. Kevin Lanctot. The network helps show where J. Kevin Lanctot may publish in the future.
Co-authorship network of co-authors of J. Kevin Lanctot
This figure shows the co-authorship network connecting the top 25 collaborators of J. Kevin Lanctot. A scholar is included among the top collaborators of J. Kevin Lanctot 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 J. Kevin Lanctot. J. Kevin Lanctot is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 73 | |
| 2 | 99 | |
| 3 | 2 | |
| 4 | 17 | |
| 5 | 6 | |
| 6 | 22 | |
| 7 | 55 | |
| 8 | Distinguishing string selection problems | 34 |
| 9 | 52 | |
| 10 | 96 |
About J. Kevin Lanctot
J. Kevin Lanctot is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Computer Networks and Communications, having authored 10 papers that have together received 456 indexed citations. Recurring topics across this work include Machine Learning and Algorithms (5 papers), Optimization and Search Problems (4 papers) and Computational Drug Discovery Methods (3 papers). The work is most often cited by research in Computational Theory and Mathematics (147 citations), Artificial Intelligence (256 citations) and Computer Networks and Communications (146 citations). J. Kevin Lanctot has collaborated with scholars based in Canada, United States and Singapore. Frequent co-authors include B. John Oommen, Louxin Zhang, Bin Ma, Ming Li, En‐hui Yang, Santosh Putta, John Eksterowicz, Erin K. Bradley, Peter D. J. Grootenhuis and Robert V. Stanton. Their work appears in journals such as Journal of Medicinal Chemistry, Information and Computation and Journal of Molecular Graphics and Modelling.
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.