Budhitama Subagdja
- Artificial Intelligence top 5%
- Control and Systems Engineering top 10%
- Computer Vision and Pattern Recognition top 10%
- Electrical and Electronic Engineering
- Computer Networks and Communications top 10%
- Co-authors
- Ah‐Hwee TanShubham PateriaChai QuekJanusz A. StarzykDi WangGee-Wah NgLiz SonenbergLei Meng
- Topics
- Reinforcement Learning in Robotics (13 papers)Multi-Agent Systems and Negotiation (7 papers)Neural Networks and Applications (7 papers)
In The Last Decade
Budhitama Subagdja
37 papers receiving 536 citations
Hit Papers
Peers
Comparison fields: 5 of 82
- Artificial Intelligence 312
- Control and Systems Engineering 118
- Computer Vision and Pattern Recognition 108
- Electrical and Electronic Engineering 70
- Computer Networks and Communications 67
Countries citing papers authored by Budhitama Subagdja
This map shows the geographic impact of Budhitama Subagdja'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 Budhitama Subagdja with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Budhitama Subagdja more than expected).
Fields of papers citing papers by Budhitama Subagdja
This network shows the impact of papers produced by Budhitama Subagdja. 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 Budhitama Subagdja. The network helps show where Budhitama Subagdja may publish in the future.
Co-authorship network of co-authors of Budhitama Subagdja
This figure shows the co-authorship network connecting the top 25 collaborators of Budhitama Subagdja. A scholar is included among the top collaborators of Budhitama Subagdja 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 Budhitama Subagdja. Budhitama Subagdja is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 3 | |
| 5 | 1 | |
| 6 | 3 | |
| 7 | 1 | |
| 8 | Hierarchical Reinforcement Learningbreakdown → | 217 |
| 9 | 1 | |
| 10 | 1 | |
| 11 | 4 | |
| 12 | 22 | |
| 13 | 2 | |
| 14 | 1 | |
| 15 | 6 | |
| 16 | 2 | |
| 17 | 67 | |
| 18 | 7 | |
| 19 | 7 | |
| 20 | 6 |
About Budhitama Subagdja
Budhitama Subagdja is a scholar working on Artificial Intelligence, Computer Science Applications and Computer Vision and Pattern Recognition, having authored 41 papers that have together received 552 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (13 papers), Multi-Agent Systems and Negotiation (7 papers) and Neural Networks and Applications (7 papers). The work is most often cited by research in Artificial Intelligence (312 citations), Computer Vision and Pattern Recognition (108 citations) and Control and Systems Engineering (118 citations). Budhitama Subagdja has collaborated with scholars based in Singapore, China and Australia. Frequent co-authors include Ah‐Hwee Tan, Shubham Pateria, Chai Quek, Janusz A. Starzyk, Di Wang, Gee-Wah Ng, Liz Sonenberg, Lei Meng, Iyad Rahwan and Yue Hu. Their work appears in journals such as Expert Systems with Applications, IEEE Access and ACM Computing Surveys.
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.