Maciej Liśkiewicz

2.8k total citations · 1 hit paper
41 papers, 1.7k citations indexed

About

Maciej Liśkiewicz is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Maciej Liśkiewicz has authored 41 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Artificial Intelligence, 15 papers in Computational Theory and Mathematics and 10 papers in Computer Vision and Pattern Recognition. Recurrent topics in Maciej Liśkiewicz's work include Bayesian Modeling and Causal Inference (13 papers), Cryptography and Data Security (8 papers) and Advanced Causal Inference Techniques (7 papers). Maciej Liśkiewicz is often cited by papers focused on Bayesian Modeling and Causal Inference (13 papers), Cryptography and Data Security (8 papers) and Advanced Causal Inference Techniques (7 papers). Maciej Liśkiewicz collaborates with scholars based in Germany, Netherlands and Poland. Maciej Liśkiewicz's 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 and has published in prestigious journals such as International Journal of Epidemiology, Artificial Intelligence and SIAM Journal on Computing.

In The Last Decade

Maciej Liśkiewicz

36 papers receiving 1.7k citations

Hit Papers

Robust causal inference using directed acyclic graphs: th... 2016 2026 2019 2022 2016 500 1000 1.5k
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.

  1. Robust causal inference using directed acyclic graphs: the R package ‘dagitty’
    2016 1.5k citations Johannes Textor, Benito van der Zander et al. International Journal of Epidemiology profile →

Peers

Maciej Liśkiewicz
Benito van der Zander Germany
Vanja Dukić United States
Eleanor J. Murray United States
Marco Carone United States
Luisa Bernardinelli Italy
Sander Greenland United States
Annette J. Dobson Australia
William D. Finkle United States
Jing Cheng United States
Carmén Cadarso-Suárez Spain
Benito van der Zander Germany
Maciej Liśkiewicz
Citations per year, relative to Maciej Liśkiewicz Maciej Liśkiewicz (= 1×) peers Benito van der Zander

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
1.
Zander, Benito van der, et al.. (2024). Linear-Time Algorithms for Front-Door Adjustment in Causal Graphs. Proceedings of the AAAI Conference on Artificial Intelligence. 38(18). 20577–20584. 1 indexed citations
2.
Liśkiewicz, Maciej, et al.. (2023). Efficient Enumeration of Markov Equivalent DAGs. Proceedings of the AAAI Conference on Artificial Intelligence. 37(10). 12313–12320.
3.
Zander, Benito van der, Markus Bläser, & Maciej Liśkiewicz. (2023). The Hardness of Reasoning about Probabilities and Causality. 5730–5738. 1 indexed citations
4.
Liśkiewicz, Maciej, et al.. (2021). Extendability of Causal Graphical Models: Algorithms and Computational Complexity. Uncertainty in Artificial Intelligence. 2 indexed citations
5.
Zander, Benito van der & Maciej Liśkiewicz. (2019). Finding Minimal d-separators in Linear Time and Applications.. Uncertainty in Artificial Intelligence. 637–647. 1 indexed citations
6.
Liśkiewicz, Maciej, et al.. (2019). Proper learning of k-term DNF formulas from satisfying assignments. Journal of Computer and System Sciences. 106. 129–144.
7.
Liśkiewicz, Maciej, et al.. (2017). Security levels in steganography – Insecurity does not imply detectability. Theoretical Computer Science. 692. 25–45. 5 indexed citations
8.
Zander, Benito van der & Maciej Liśkiewicz. (2016). On Searching for Generalized Instrumental Variables. International Conference on Artificial Intelligence and Statistics. 1214–1222. 6 indexed citations
9.
Textor, Johannes, Benito van der Zander, Mark S. Gilthorpe, Maciej Liśkiewicz, & George T. H. Ellison. (2016). Robust causal inference using directed acyclic graphs: the R package ‘dagitty’. International Journal of Epidemiology. 45(6). dyw341–dyw341. 1526 indexed citations breakdown →
10.
Zander, Benito van der & Maciej Liśkiewicz. (2016). Separators and Adjustment Sets in Markov Equivalent DAGs. Proceedings of the AAAI Conference on Artificial Intelligence. 30(1). 10 indexed citations
11.
Liśkiewicz, Maciej, et al.. (2016). Provable Secure Universal Steganography of Optimal Rate. 81–92. 3 indexed citations
12.
Zander, Benito van der, Johannes Textor, & Maciej Liśkiewicz. (2015). Efficiently finding conditional instruments for causal inference. Utrecht University Repository (Utrecht University). 3243–3249. 9 indexed citations
13.
Zander, Benito van der, Maciej Liśkiewicz, & Johannes Textor. (2014). Constructing separators and adjustment sets in ancestral graphs. Uncertainty in Artificial Intelligence. 11–24. 30 indexed citations
14.
Liśkiewicz, Maciej, et al.. (2014). A new upper bound for the traveling salesman problem in cubic graphs. Journal of Discrete Algorithms. 27. 1–20. 7 indexed citations
15.
Liśkiewicz, Maciej, et al.. (2012). Grey-box steganography. Theoretical Computer Science. 505. 27–41. 4 indexed citations
16.
Hundt, Christian & Maciej Liśkiewicz. (2010). New complexity bounds for image matching under rotation and scaling. Journal of Discrete Algorithms. 9(1). 122–136. 2 indexed citations
17.
Liśkiewicz, Maciej & Johannes Textor. (2010). Negative selection algorithms without generating detectors. 1047–1054. 12 indexed citations
18.
Hundt, Christian, et al.. (2009). A combinatorial geometrical approach to two-dimensional robust pattern matching with scaling and rotation. Theoretical Computer Science. 410(51). 5317–5333. 9 indexed citations
19.
Liśkiewicz, Maciej, Mitsunori Ogihara, & Seinosuke Toda. (2003). The complexity of counting self-avoiding walks in subgraphs of two-dimensional grids and hypercubes. Theoretical Computer Science. 304(1-3). 129–156. 10 indexed citations
20.
Liśkiewicz, Maciej, et al.. (1987). On reversal bounded alternating Turing machines. Theoretical Computer Science. 54(2-3). 331–339. 3 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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