Murtaza Dalal
- Artificial Intelligence
- Control and Systems Engineering
- Computer Vision and Pattern Recognition
- Computational Theory and Mathematics
- Management Science and Operations Research
- Co-authors
- Vitchyr H. PongSergey LevineShixiang GuAshvin NairShikhar BahlSteven LinSaurabh GuptaDevendra Singh Chaplot
- Topics
- Domain Adaptation and Few-Shot Learning (2 papers)Reinforcement Learning in Robotics (2 papers)Multimodal Machine Learning Applications (1 paper)
- Cited by
- Artificial IntelligenceControl and Systems EngineeringComputer Vision and Pattern Recognition
- Journals
- arXiv (Cornell University)MPG.PuRe (Max Planck Society)
- Partner nations
- United StatesIndiaGermany
In The Last Decade
Murtaza Dalal
3 papers receiving 95 citations
Peers
Comparison fields: 5 of 32
- Artificial Intelligence 74
- Control and Systems Engineering 35
- Computer Vision and Pattern Recognition 27
- Computational Theory and Mathematics 9
- Management Science and Operations Research 9
Countries citing papers authored by Murtaza Dalal
This map shows the geographic impact of Murtaza Dalal'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 Murtaza Dalal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Murtaza Dalal more than expected).
Fields of papers citing papers by Murtaza Dalal
This network shows the impact of papers produced by Murtaza Dalal. 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 Murtaza Dalal. The network helps show where Murtaza Dalal may publish in the future.
Co-authorship network of co-authors of Murtaza Dalal
This figure shows the co-authorship network connecting the top 25 collaborators of Murtaza Dalal. A scholar is included among the top collaborators of Murtaza Dalal 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 Murtaza Dalal. Murtaza Dalal 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 | 7 | |
| 3 | Visual Reinforcement Learning with Imagined Goals | 38 |
| 4 | Temporal Difference Models: Model-Free Deep RL for Model-Based Control | 57 |
About Murtaza Dalal
Murtaza Dalal is a scholar working on Instrumentation, Artificial Intelligence and Renewable Energy, Sustainability and the Environment, having authored 4 papers that have together received 102 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (2 papers), Reinforcement Learning in Robotics (2 papers) and Multimodal Machine Learning Applications (1 paper). The work is most often cited by research in Artificial Intelligence (74 citations), Control and Systems Engineering (35 citations) and Computer Vision and Pattern Recognition (27 citations). Murtaza Dalal has collaborated with scholars based in United States, India and Germany. Frequent co-authors include Vitchyr H. Pong, Sergey Levine, Shixiang Gu, Ashvin Nair, Shikhar Bahl, Steven Lin, Saurabh Gupta, Devendra Singh Chaplot, Jitendra Malik and Russ R. Salakhutdinov. Their work appears in journals such as arXiv (Cornell University) and MPG.PuRe (Max Planck Society).
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.