Sertan Girgin
- Artificial Intelligence top 10%
- Signal Processing
- Management Science and Operations Research
- Electrical and Electronic Engineering
- Control and Systems Engineering
- Co-authors
- Reda AlhajjFaruk PolatOlivier PietquinRaphaël MarinierEugene KharitonovDamien VincentZalán BorsosNeil Zeghidour
- Topics
- Reinforcement Learning in Robotics (9 papers)Evolutionary Algorithms and Applications (4 papers)Topic Modeling (3 papers)
- Journals
- Waste ManagementMachine LearningIEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)
- Partner nations
- United StatesTürkiyeLebanon
In The Last Decade
Sertan Girgin
15 papers receiving 147 citations
Peers
Comparison fields: 5 of 51
- Artificial Intelligence 112
- Signal Processing 24
- Management Science and Operations Research 13
- Electrical and Electronic Engineering 10
- Control and Systems Engineering 9
Countries citing papers authored by Sertan Girgin
This map shows the geographic impact of Sertan Girgin'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 Sertan Girgin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sertan Girgin more than expected).
Fields of papers citing papers by Sertan Girgin
This network shows the impact of papers produced by Sertan Girgin. 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 Sertan Girgin. The network helps show where Sertan Girgin may publish in the future.
Co-authorship network of co-authors of Sertan Girgin
This figure shows the co-authorship network connecting the top 25 collaborators of Sertan Girgin. A scholar is included among the top collaborators of Sertan Girgin 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 Sertan Girgin. Sertan Girgin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 54 | |
| 2 | 10 | |
| 3 | 2 | |
| 4 | What Matters for On-Policy Deep Actor-Critic Methods? A Large-Scale Study | 26 |
| 5 | 0 | |
| 6 | 3 | |
| 7 | 0 | |
| 8 | 4 | |
| 9 | 10 | |
| 10 | Abstraction in Reinforcement Learning | 2 |
| 11 | 11 | |
| 12 | 3 | |
| 13 | Incremental Basis Function Expansion in Reinforcement Learning using Cascade-Correlation Networks | 1 |
| 14 | 9 | |
| 15 | State similarity based approach for improving performance in RL | 6 |
| 16 | 9 | |
| 17 | 3 |
About Sertan Girgin
Sertan Girgin is a scholar working on Artificial Intelligence, Management Science and Operations Research and Computer Vision and Pattern Recognition, having authored 17 papers that have together received 153 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (9 papers), Evolutionary Algorithms and Applications (4 papers) and Topic Modeling (3 papers). The work is most often cited by research in Artificial Intelligence (112 citations), Signal Processing (24 citations) and Health Informatics (3 citations). Sertan Girgin has collaborated with scholars based in United States, Türkiye and Lebanon. Frequent co-authors include Reda Alhajj, Faruk Polat, Olivier Pietquin, Raphaël Marinier, Eugene Kharitonov, Damien Vincent, Zalán Borsos, Neil Zeghidour, Marco Tagliasacchi and Matt Sharifi. Their work appears in journals such as Waste Management, Machine Learning and IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics).
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.