Michael Cochez

3.5k total citations · 1 hit paper
46 papers, 1.6k citations indexed

About

Michael Cochez is a scholar working on Artificial Intelligence, Molecular Biology and Information Systems. According to data from OpenAlex, Michael Cochez has authored 46 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Artificial Intelligence, 8 papers in Molecular Biology and 8 papers in Information Systems. Recurrent topics in Michael Cochez's work include Advanced Graph Neural Networks (14 papers), Topic Modeling (12 papers) and Semantic Web and Ontologies (7 papers). Michael Cochez is often cited by papers focused on Advanced Graph Neural Networks (14 papers), Topic Modeling (12 papers) and Semantic Web and Ontologies (7 papers). Michael Cochez collaborates with scholars based in Germany, Netherlands and Finland. Michael Cochez's co-authors include Stefan Decker, Md. Rezaul Karim, Oya Beyan, Dietrich Rebholz‐Schuhmann, Steffen Staab, Eva Blomqvist, Antoine Zimmermann, Juan Sequeda, Axel-Cyrille Ngonga Ngomo and Sebastian Neumaier and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and ACM Computing Surveys.

In The Last Decade

Michael Cochez

44 papers receiving 1.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Knowledge Graphs

2021 632 citations Aidan Hogan, Eva Blomqvist et al. ACM Computing Surveys profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Michael Cochez Germany	16	881	277	228	186	172	46	1.6k
Yun Xiong China	21	779 0.9×	245 0.9×	420 1.8×	93 0.5×	115 0.7×	116	1.4k
Md. Rezaul Karim Germany	16	464 0.5×	196 0.7×	119 0.5×	170 0.9×	122 0.7×	38	1.1k
Herna L. Viktor Canada	14	656 0.7×	186 0.7×	203 0.9×	34 0.2×	118 0.7×	85	1.3k
Liang Yao China	18	1.4k 1.6×	233 0.8×	275 1.2×	115 0.6×	33 0.2×	36	1.9k
Ninghao Liu United States	19	1.4k 1.6×	103 0.4×	365 1.6×	72 0.4×	50 0.3×	71	2.2k
Alexey Tsymbal Finland	19	1.4k 1.6×	105 0.4×	326 1.4×	130 0.7×	90 0.5×	58	1.9k
Zeyar Aung United Arab Emirates	22	538 0.6×	179 0.6×	204 0.9×	64 0.3×	40 0.2×	106	1.5k
Richard E. Neapolitan United States	18	766 0.9×	272 1.0×	134 0.6×	52 0.3×	114 0.7×	56	1.5k
Kamal Berahmand Australia	33	1.2k 1.4×	419 1.5×	325 1.4×	79 0.4×	135 0.8×	54	2.5k

Countries citing papers authored by Michael Cochez

Since Specialization

Citations

This map shows the geographic impact of Michael Cochez'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 Michael Cochez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Cochez more than expected).

Fields of papers citing papers by Michael Cochez

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Cochez

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

All Works

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20 of 20 papers shown

Mitra, Payal, et al.. (2023). BioBLP: a modular framework for learning on multimodal biomedical knowledge graphs. Journal of Biomedical Semantics. 14(1). 20–20. 5 indexed citations

Karim, Md. Rezaul, Md Shajalal, Oya Beyan, et al.. (2023). Explainable AI for Bioinformatics: Methods, Tools and Applications. Briefings in Bioinformatics. 24(5). 70 indexed citations

Renaux, Alexandre, et al.. (2023). A knowledge graph approach to predict and interpret disease-causing gene interactions. BMC Bioinformatics. 24(1). 324–324. 14 indexed citations

Cochez, Michael, Stefania Dumbrava, Matteo Lissandrini, et al.. (2023). Knowledge Graph Embeddings: Open Challenges and Opportunities. SHILAP Revista de lepidopterología.

Alam, Mehwish, Davide Buscaldi, Michael Cochez, et al.. (2022). Editorial of the Special Issue on Deep Learning and Knowledge Graphs. Semantic Web. 13(3). 293–297. 1 indexed citations

Hogan, Aidan, Eva Blomqvist, Michael Cochez, et al.. (2021). Knowledge Graphs. ACM Computing Surveys. 54(4). 1–37. 632 indexed citations breakdown →

Karim, Md. Rezaul, Bharathi Raja Chakravarthi, John P. McCrae, & Michael Cochez. (2020). Classification Benchmarks for Under-resourced Bengali Language based on Multichannel Convolutional-LSTM Network. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 48 indexed citations

Karim, Md Rezaul, Till Döhmen, Dietrich Rebholz‐Schuhmann, et al.. (2020). DeepCOVIDExplainer: Explainable COVID-19 Predictions Based on Chest X-ray Images. arXiv (Cornell University). 44 indexed citations

Cochez, Michael, et al.. (2020). Message Passing for Query Answering over Knowledge Graphs. arXiv (Cornell University). 1 indexed citations

10.

Karim, Md. Rezaul, Till Döhmen, Michael Cochez, et al.. (2020). DeepCOVIDExplainer: Explainable COVID-19 Diagnosis from Chest X-ray Images. VU Research Portal. 1034–1037. 96 indexed citations

11.

Karim, Md. Rezaul, Michael Cochez, Oya Beyan, Stefan Decker, & Christoph Lange. (2019). OncoNetExplainer: Explainable predictions of cancer types based on gene expression data. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 15 indexed citations

12.

Karim, Md. Rezaul, et al.. (2019). Drug-drug interaction prediction based on knowledge graph embeddings and convolutional-LSTM network. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 99 indexed citations

13.

Wang, Ruijie, Meng Wang, Jun Liu, Michael Cochez, & Stefan Decker. (2019). Structured query construction via knowledge graph embedding. Knowledge and Information Systems. 62(5). 1819–1846. 4 indexed citations

14.

Karim, Md. Rezaul, Oya Beyan, Achille Zappa, et al.. (2019). Deep learning-based clustering approaches for bioinformatics. Briefings in Bioinformatics. 22(1). 393–415. 179 indexed citations

15.

Karim, Md Rezaul, Michael Cochez, Oya Beyan, et al.. (2018). Recurrent Deep Embedding Networks for Genotype Clustering and Ethnicity Prediction.. arXiv (Cornell University). 2 indexed citations

16.

Cochez, Michael, et al.. (2017). The Future of the Semantic Web: Prototypes on a Global Distributed Filesystem. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 6. 1997–2006. 3 indexed citations

17.

Cochez, Michael, et al.. (2015). Indeterminacy Reduction in Agent Communication Using a Semantic Language. Jyväskylä University Digital Archive (University of Jyväskylä). 14. 3 indexed citations

18.

Cochez, Michael, et al.. (2014). Evolutionary Cloud for Cooperative UAV Coordination. Jyväskylä University Digital Archive (University of Jyväskylä). 5 indexed citations

19.

Cochez, Michael, et al.. (2013). The Use of Distributed Version Control Systems in Advanced Programming Courses.. 221–235. 2 indexed citations

20.

Cochez, Michael. (2012). Semantic agent programming language : use and formalization. Jyväskylä University Digital Archive (University of Jyväskylä). 5 indexed citations

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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