Riashat Islam
- Artificial Intelligence top 1%
- Electrical and Electronic Engineering top 10%
- Control and Systems Engineering top 2%
- Computer Networks and Communications top 5%
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Joëlle PineauPeter HendersonVincent François-LavetMarc G. BellemareDoina PrecupPhilip BachmanDavid MegerDip Nandi
- Topics
- Reinforcement Learning in Robotics (3 papers)Evolutionary Algorithms and Applications (2 papers)Medical Imaging and Analysis (1 paper)
- Journals
- now publishers, Inc. eBooksarXiv (Cornell University)Proceedings of the AAAI Conference on Artificial Intelligence
- Partner nations
- CanadaUnited KingdomUnited States
In The Last Decade
Riashat Islam
9 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 139
- Artificial Intelligence 910
- Electrical and Electronic Engineering 418
- Control and Systems Engineering 411
- Computer Networks and Communications 395
- Computer Vision and Pattern Recognition 293
Countries citing papers authored by Riashat Islam
This map shows the geographic impact of Riashat Islam'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 Riashat Islam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Riashat Islam more than expected).
Fields of papers citing papers by Riashat Islam
This network shows the impact of papers produced by Riashat Islam. 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 Riashat Islam. The network helps show where Riashat Islam may publish in the future.
Co-authorship network of co-authors of Riashat Islam
This figure shows the co-authorship network connecting the top 25 collaborators of Riashat Islam. A scholar is included among the top collaborators of Riashat Islam 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 Riashat Islam. Riashat Islam is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | InfoBot: Transfer and Exploration via the Information Bottleneck | 8 |
| 3 | InfoBot: Structured Exploration in ReinforcementLearning Using Information Bottleneck | 1 |
| 4 | An Introduction to Deep Reinforcement Learningbreakdown → | 811 |
| 5 | Deep Reinforcement Learning That Mattersbreakdown → | 814 |
| 6 | 31 | |
| 7 | RE-EVALUATE: Reproducibility in Evaluating Reinforcement Learning Algorithms | 8 |
| 8 | An Introduction to Deep Reinforcement Learningbreakdown → | 343 |
| 9 | 111 |
About Riashat Islam
Riashat Islam is a scholar working on Software, Artificial Intelligence and Neurology, having authored 9 papers that have together received 2.1k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (3 papers), Evolutionary Algorithms and Applications (2 papers) and Medical Imaging and Analysis (1 paper). The work is most often cited by research in Artificial Intelligence (910 citations), Health Informatics (29 citations) and Control and Systems Engineering (411 citations). Riashat Islam has collaborated with scholars based in Canada, United Kingdom and United States. Frequent co-authors include Joëlle Pineau, Peter Henderson, Vincent François-Lavet, Marc G. Bellemare, Doina Precup, Philip Bachman, David Meger, Dip Nandi, Hidayat Ullah and Zafarali Ahmed. Their work appears in journals such as now publishers, Inc. eBooks, arXiv (Cornell University) 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.