Maciej Liśkiewicz

36 papers receiving 1.7k citations

Hit Papers

Robust causal inference using directed acyclic graphs: th...2016202620192022201650010001.5k

Peers

Maciej Liśkiewicz
Comparison fields: 5 of 176
  • Public Health, Environmental and Occupational Health 289
  • Health, Toxicology and Mutagenesis 268
  • Pediatrics, Perinatology and Child Health 200
  • Epidemiology 174
  • Artificial Intelligence 138
Replace Benito van der Zander with:
Benito van der Zander Germany
Eleanor J. Murray United States
George Berry United States
S J Pocock United Kingdom
Alison J. Thornton United Kingdom
Fuzhong Xue China
Gerard Borsboom Netherlands
Mohamed M. Shoukri Saudi Arabia
Stephen D. Simon United States
Maciej Liśkiewicz relative to Benito van der Zander Germany Benito van der Zander's profile →
Citations per field
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Benito van der Zander · 1×
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Countries citing papers authored by Maciej Liśkiewicz

Since Specialization
Citations

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

Fields of papers citing papers by Maciej Liśkiewicz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maciej Liśkiewicz

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

All Works

20 of 20 papers shown
#WorkIndexed citations
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Extendability of Causal Graphical Models: Algorithms and Computational Complexity
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Finding Minimal d-separators in Linear Time and Applications.
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6 0
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On Searching for Generalized Instrumental Variables
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Robust causal inference using directed acyclic graphs: the R package ‘dagitty’breakdown →
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Efficiently finding conditional instruments for causal inference
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Constructing separators and adjustment sets in ancestral graphs
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About Maciej Liśkiewicz

Maciej Liśkiewicz is a scholar working on Statistics and Probability, Artificial Intelligence and Computational Theory and Mathematics, having authored 41 papers that have together received 1.7k indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (13 papers), Cryptography and Data Security (8 papers) and Advanced Causal Inference Techniques (7 papers). The work is most often cited by research in Health, Toxicology and Mutagenesis (268 citations), Statistics and Probability (133 citations) and Speech and Hearing (74 citations). Maciej Liśkiewicz has collaborated with scholars based in Germany, Netherlands and Poland. Frequent co-authors include Johannes Textor, Benito van der Zander, Mark S. Gilthorpe, George T. H. Ellison, Rüdiger Reischuk, Thomas Eisenbarth, Christian Hundt, Mitsunori Ogihara, Seinosuke Toda and Bodo Manthey. Their work appears in journals such as International Journal of Epidemiology, Artificial Intelligence and SIAM Journal on Computing.

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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