Michał Podstawski
- Artificial Intelligence top 10%
- Information Systems top 5%
- Computer Networks and Communications top 10%
- Computer Vision and Pattern Recognition top 10%
- Hardware and Architecture top 10%
- Co-authors
- Maciej BestaTorsten HoeflerRobert GerstenbergerEdgar SolomonikAles KubicekPiotr NyczykGrzegorz KwaśniewskiH. Niewiadomski
- Topics
- Graph Theory and Algorithms (3 papers)Cloud Computing and Resource Management (2 papers)Advanced Graph Neural Networks (2 papers)
- Journals
- ACM Computing SurveysInstitutional Research Information System (Università degli Studi di Trento)Proceedings of the AAAI Conference on Artificial Intelligence
- Partner nations
- SwitzerlandPolandUnited States
In The Last Decade
Michał Podstawski
6 papers receiving 348 citations
Hit Papers
Peers
Comparison fields: 5 of 55
- Artificial Intelligence 172
- Information Systems 117
- Computer Networks and Communications 112
- Computer Vision and Pattern Recognition 107
- Hardware and Architecture 49
Countries citing papers authored by Michał Podstawski
This map shows the geographic impact of Michał Podstawski'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 Michał Podstawski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michał Podstawski more than expected).
Fields of papers citing papers by Michał Podstawski
This network shows the impact of papers produced by Michał Podstawski. 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 Michał Podstawski. The network helps show where Michał Podstawski may publish in the future.
Co-authorship network of co-authors of Michał Podstawski
This figure shows the co-authorship network connecting the top 25 collaborators of Michał Podstawski. A scholar is included among the top collaborators of Michał Podstawski 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 Michał Podstawski. Michał Podstawski is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Graph of Thoughts: Solving Elaborate Problems with Large Language Modelsbreakdown → | 161 |
| 2 | 7 | |
| 3 | 30 | |
| 4 | 2 | |
| 5 | 75 | |
| 6 | 82 |
About Michał Podstawski
Michał Podstawski is a scholar working on Hardware and Architecture, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 6 papers that have together received 357 indexed citations. Recurring topics across this work include Graph Theory and Algorithms (3 papers), Cloud Computing and Resource Management (2 papers) and Advanced Graph Neural Networks (2 papers). The work is most often cited by research in Health Informatics (10 citations), Hardware and Architecture (49 citations) and Artificial Intelligence (172 citations). Michał Podstawski has collaborated with scholars based in Switzerland, Poland and United States. Frequent co-authors include Maciej Besta, Torsten Hoefler, Robert Gerstenberger, Edgar Solomonik, Ales Kubicek, Piotr Nyczyk, Grzegorz Kwaśniewski, H. Niewiadomski, Lukas Gianinazzi and Nils Blach. Their work appears in journals such as ACM Computing Surveys, Institutional Research Information System (Università degli Studi di Trento) and Proceedings of the AAAI Conference on Artificial Intelligence.
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.