T. Gal
Impact in
-
- Parallel Computing and Optimization Techniques
-
- stochastic dynamics and bifurcation
Papers in ⓘ
-
- Parallel Computing and Optimization Techniques 2
-
- Scientific Computing and Data Management 2
- Co-authors
- George Datseris (1 shared paper)Jerry Ling (4 shared papers)Benedikt Hegner (2 shared papers)J. Pivarski (1 shared paper)P. Gras (2 shared papers)S. Kluth (1 shared paper)O. Schulz (2 shared papers)J. Strube (1 shared paper)
- Journals
- SHILAP Revista de lepidopterología (2 papers)EPJ Web of Conferences (1 paper)arXiv (Cornell University) (1 paper)Open Research Europe (1 paper)The Journal of Open Source Software (2 papers)
- Partner nations
- GermanyUnited StatesSwitzerland
In The Last Decade
T. Gal
4 papers receiving 33 citations
Peers
Comparison fields: 5 of 31
- Hardware and Architecture 5
- Statistical and Nonlinear Physics 8
- Computer Networks and Communications 11
- Nuclear and High Energy Physics 6
- Cognitive Neuroscience 7
Countries citing papers authored by T. Gal
This map shows the geographic impact of T. Gal'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. Gal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T. Gal more than expected).
Fields of papers citing papers by T. Gal
This network shows the impact of papers produced by T. Gal. 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. Gal. The network helps show where T. Gal may publish in the future.
Co-authors
The 23 scholars most cited alongside T. Gal, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 22 | |
| 2 | 2023 | 7 | |
| 3 | 2022 | 4 | |
| 4 | 2023 | 1 | |
| 5 | 2025 | 0 | |
| 6 | 2023 | 0 | |
| 7 | 2024 | 0 |
About T. Gal
T. Gal is a scholar working on Hardware and Architecture, Information Systems and Management, Nuclear and High Energy Physics, Computer Networks and Communications and Statistics, Probability and Uncertainty, having authored 7 papers that have together received 34 indexed citations. Recurring topics across this work include Advanced Data Storage Technologies (3 papers), Distributed and Parallel Computing Systems (3 papers), Parallel Computing and Optimization Techniques (2 papers), Particle Detector Development and Performance (2 papers), Scientific Computing and Data Management (2 papers), Research Data Management Practices (2 papers), Particle physics theoretical and experimental studies (2 papers) and Clinical Laboratory Practices and Quality Control (1 paper). The work is most often cited by research in Hardware and Architecture (5 citations), Statistical and Nonlinear Physics (8 citations), Computer Networks and Communications (11 citations), Nuclear and High Energy Physics (6 citations) and Cognitive Neuroscience (7 citations). T. Gal has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include George Datseris, Jerry Ling, Benedikt Hegner, J. Pivarski, P. Gras, S. Kluth, O. Schulz, J. Strube, Enrique Alonso García and L. Heinrich. Their work appears in journals such as SHILAP Revista de lepidopterología, EPJ Web of Conferences, arXiv (Cornell University), Open Research Europe and The Journal of Open Source Software.
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.