Todor Markov
Impact in
- Automotive Engineering top 1%
- Advanced Battery Technologies Research
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- Advancements in Battery Materials
- Advanced Battery Materials and Technologies
- Electric Vehicles and Infrastructure
- Fuel Cells and Related Materials
Papers in
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- Hate Speech and Cyberbullying Detection 1
- Reinforcement Learning in Robotics 1
- Evolutionary Algorithms and Applications 1
- Artificial Intelligence in Games 1
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- Advanced Battery Technologies Research 1
- Co-authors
- Stefano Ermon (1 shared paper)Patrick K. Herring (1 shared paper)Bryan Cheong (1 shared paper)Michael H. Chen (1 shared paper)Muratahan Aykol (1 shared paper)Aditya Grover (1 shared paper)William C. Chueh (1 shared paper)Richard D. Braatz (1 shared paper)
- Journals
- Nature (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United States
In The Last Decade
Todor Markov
3 papers receiving 793 citations
Todor Markov's Hit Papers
Peers
Comparison fields: 5 of 73
- Automotive Engineering 549
- Electrical and Electronic Engineering 597
- Safety, Risk, Reliability and Quality 67
- Health Informatics 6
- Control and Systems Engineering 86
Countries citing papers authored by Todor Markov
This map shows the geographic impact of Todor Markov'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 Todor Markov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Todor Markov more than expected).
Fields of papers citing papers by Todor Markov
This network shows the impact of papers produced by Todor Markov. 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 Todor Markov. The network helps show where Todor Markov may publish in the future.
Co-authors
The 23 scholars most cited alongside Todor Markov, 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 | Closed-loop optimization of fast-charging protocols for batteries with machine learning Hit paper breakdown → | 2020 | 748 |
| 2 | 2023 | 53 | |
| 3 | Emergent Tool Use From Multi-Agent Autocurricula | 2020 | 20 |
About Todor Markov
Todor Markov is a scholar working on Artificial Intelligence, Automotive Engineering, Electrical and Electronic Engineering, Infectious Diseases and Organic Chemistry, having authored 3 papers that have together received 821 indexed citations. Recurring topics across this work include Fuel Cells and Related Materials (1 paper), Hate Speech and Cyberbullying Detection (1 paper), Advancements in Battery Materials (1 paper), Reinforcement Learning in Robotics (1 paper), Evolutionary Algorithms and Applications (1 paper), Artificial Intelligence in Games (1 paper) and Advanced Battery Technologies Research (1 paper). The work is most often cited by research in Automotive Engineering (549 citations), Electrical and Electronic Engineering (597 citations), Safety, Risk, Reliability and Quality (67 citations), Health Informatics (6 citations) and Control and Systems Engineering (86 citations). Todor Markov has collaborated with scholars based in United States. Frequent co-authors include Stefano Ermon, Patrick K. Herring, Bryan Cheong, Michael H. Chen, Muratahan Aykol, Aditya Grover, William C. Chueh, Richard D. Braatz, Stephen J. Harris and Peter M. Attia. Their work appears in journals such as Nature, Proceedings of the AAAI Conference on Artificial Intelligence and arXiv (Cornell University).
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.