T. Salakoski

8 total papers · 512 total citations
6 papers, 314 citations indexed

About

T. Salakoski is a scholar working on Artificial Intelligence, Molecular Biology and Signal Processing. According to data from OpenAlex, T. Salakoski has authored 6 papers receiving a total of 314 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 2 papers in Molecular Biology and 1 paper in Signal Processing. Recurrent topics in T. Salakoski's work include Bayesian Modeling and Causal Inference (2 papers), Topic Modeling (1 paper) and Biomedical Text Mining and Ontologies (1 paper). T. Salakoski is often cited by papers focused on Bayesian Modeling and Causal Inference (2 papers), Topic Modeling (1 paper) and Biomedical Text Mining and Ontologies (1 paper). T. Salakoski collaborates with scholars based in Finland, Belgium and Pakistan. T. Salakoski's co-authors include Filip Ginter, Sophia Ananiadou, Sampo Pyysalo, Hans Moen, Teemu Rajala, Mikko‐Jussi Laakso, Erkki Kaila, Willem Waegeman, Bernard De Baets and Tapio Pahikkala and has published in prestigious journals such as IEEE Transactions on Biomedical Engineering, IEEE Transactions on Fuzzy Systems and Informatics in Education.

In The Last Decade

T. Salakoski

6 papers receiving 289 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
T. Salakoski	246	207	30	23	13	6	314
Jennifer Vendetti	142 0.6×	128 0.6×	14 0.5×	6 0.3×	2 0.2×	8	239
Lynne M. Fox	148 0.6×	217 1.0×	8 0.3×	6 0.3×	3 0.2×	11	308
Marco Basaldella	186 0.8×	121 0.6×	4 0.1×	15 0.7×		14	218
Katikapalli Subramanyam Kalyan	150 0.6×	45 0.2×	5 0.2×	4 0.2×	4 0.3×	6	242
Weitao Ma	213 0.9×	31 0.1×	11 0.4×	9 0.4×	5 0.4×	6	356
David Perry Greene	188 0.8×	23 0.1×	26 0.9×	6 0.3×	11 0.8×	10	299
Isabelle Moulinier	242 1.0×	32 0.2×	12 0.4×	11 0.5×	4 0.3×	11	333
Caroline Gasperin	322 1.3×	113 0.5×	4 0.1×	5 0.2×	18 1.4×	20	349
Martin Duneld	235 1.0×	156 0.8×	13 0.4×	2 0.1×		14	280
Lawrence H. Reeve	271 1.1×	102 0.5×	5 0.2×	9 0.4×	2 0.2×	8	297

Countries citing papers authored by T. Salakoski

Since Specialization

Citations

This map shows the geographic impact of T. Salakoski'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 T. Salakoski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Salakoski more than expected).

Fields of papers citing papers by T. Salakoski

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by T. Salakoski. 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 T. Salakoski. The network helps show where T. Salakoski may publish in the future.

Co-authorship network of co-authors of T. Salakoski

This figure shows the co-authorship network connecting the top 25 collaborators of T. Salakoski. A scholar is included among the top collaborators of T. Salakoski 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 T. Salakoski. T. Salakoski is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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.

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