Jivko Sinapov

2.2k total citations
63 papers, 1.3k citations indexed

About

Jivko Sinapov is a scholar working on Artificial Intelligence, Control and Systems Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Jivko Sinapov has authored 63 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Artificial Intelligence, 27 papers in Control and Systems Engineering and 18 papers in Computer Vision and Pattern Recognition. Recurrent topics in Jivko Sinapov's work include Robot Manipulation and Learning (24 papers), Reinforcement Learning in Robotics (18 papers) and AI-based Problem Solving and Planning (11 papers). Jivko Sinapov is often cited by papers focused on Robot Manipulation and Learning (24 papers), Reinforcement Learning in Robotics (18 papers) and AI-based Problem Solving and Planning (11 papers). Jivko Sinapov collaborates with scholars based in United States, United Kingdom and Austria. Jivko Sinapov's co-authors include Alexander Stoytchev, Peter Stone, Drena Dobbs, Cornelia Caragea, Vasant Honavar, Sanmit Narvekar, Ranjana Sahai, Matteo Leonetti, Jesse Thomason and Adrian Silvescu and has published in prestigious journals such as BMC Bioinformatics, Artificial Intelligence and The International Journal of Robotics Research.

In The Last Decade

Jivko Sinapov

61 papers receiving 1.2k citations

Peers

Jivko Sinapov

CSE

CVPR

Olivier Sigaud France

Owen Holland United Kingdom

Hai Nguyen United States

Satoru Hayamizu Japan

Erol Şahi̇n Türkiye

Álvaro Soto Chile

Franziska Meier United States

Mohammed Faisal Saudi Arabia

Alexander Stoytchev United States

Yutaka Nakamura Japan

Olivier Sigaud France

Jivko Sinapov

403 ×0.7

265 ×0.6

CSE

81 ×0.2

CVPR

210 ×1.1

83 ×0.5

Citations per year, relative to Jivko Sinapov Jivko Sinapov (= 1×) peers Olivier Sigaud

Countries citing papers authored by Jivko Sinapov

Since Specialization

Citations

This map shows the geographic impact of Jivko Sinapov'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 Jivko Sinapov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jivko Sinapov more than expected).

Fields of papers citing papers by Jivko Sinapov

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jivko Sinapov. 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 Jivko Sinapov. The network helps show where Jivko Sinapov may publish in the future.

Co-authorship network of co-authors of Jivko Sinapov

This figure shows the co-authorship network connecting the top 25 collaborators of Jivko Sinapov. A scholar is included among the top collaborators of Jivko Sinapov 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 Jivko Sinapov. Jivko Sinapov is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Sinapov, Jivko, Han Zhao, Muneeb Ahmad, et al.. (2024). Introduction to the Special Issue on Artificial Intelligence for Human–Robot Interaction (AI-HRI). ACM Transactions on Human-Robot Interaction. 13(3). 1–3.

Francis, Jonathan, et al.. (2024). MOSAIC: Learning Unified Multi-Sensory Object Property Representations for Robot Learning via Interactive Perception. 15381–15387. 2 indexed citations

Shukla, Yash, Abhishek Kulkarni, Robert Wright, Alvaro Velasquez, & Jivko Sinapov. (2023). Automaton-Guided Curriculum Generation for Reinforcement Learning Agents. Proceedings of the International Conference on Automated Planning and Scheduling. 33(1). 605–613. 1 indexed citations

Amiri, Saeid, et al.. (2023). Multimodal embodied attribute learning by robots for object-centric action policies. Autonomous Robots. 47(5). 505–528. 3 indexed citations

Nair, Lakshmi S., et al.. (2022). Creative Problem Solving in Artificially Intelligent Agents: A Survey and Framework. Journal of Artificial Intelligence Research. 75. 11 indexed citations

Francis, Jonathan, et al.. (2022). Knowledge-driven Scene Priors for Semantic Audio-Visual Embodied Navigation. arXiv (Cornell University). 1 indexed citations

Sinapov, Jivko, et al.. (2021). A Novelty-Centric Agent Architecture for Changing Worlds.. Autonomous Agents and Multi-Agent Systems. 925–933. 9 indexed citations

Narvekar, Sanmit, Bei Peng, Matteo Leonetti, et al.. (2020). Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey. Journal of Machine Learning Research. 21(181). 1–50. 18 indexed citations

Sinapov, Jivko, et al.. (2020). From Computational Creativity to Creative Problem Solving Agents.. ICCC. 370–373. 1 indexed citations

10.

Hughes, Michael C., et al.. (2020). A Framework for Sensorimotor Cross-Perception and Cross-Behavior Knowledge Transfer for Object Categorization. Frontiers in Robotics and AI. 7. 522141–522141. 7 indexed citations

11.

Scheutz, Matthias, et al.. (2018). A Generalized Framework for Detecting Anomalies in Real-Time Using Contextual Information.. International Joint Conference on Artificial Intelligence. 1–7. 1 indexed citations

12.

Thomason, Jesse, et al.. (2017). Opportunistic Active Learning for Grounding Natural Language Descriptions. 67–76. 16 indexed citations

13.

Sinapov, Jivko, et al.. (2016). Learning to order objects using haptic and proprioceptive exploratory behaviors. International Joint Conference on Artificial Intelligence. 3462–3468. 18 indexed citations

14.

Thomason, Jesse, et al.. (2016). Learning multi-modal grounded linguistic semantics by playing I Spy. International Joint Conference on Artificial Intelligence. 3477–3483. 39 indexed citations

15.

Narvekar, Sanmit, Jivko Sinapov, Matteo Leonetti, & Peter Stone. (2016). Source Task Creation for Curriculum Learning. Adaptive Agents and Multi-Agents Systems. 566–574. 36 indexed citations

16.

Sinapov, Jivko, Sanmit Narvekar, Matteo Leonetti, & Peter Stone. (2015). Learning Inter-Task Transferability in the Absence of Target Task Samples. Adaptive Agents and Multi-Agents Systems. 725–733. 17 indexed citations

17.

Sinapov, Jivko & Alexander Stoytchev. (2013). Grounded object individuation by a humanoid robot. 4981–4988. 5 indexed citations

18.

Caragea, Cornelia, Jivko Sinapov, Drena Dobbs, & Vasant Honavar. (2009). Mixture of experts models to exploit global sequence similarity on biomolecular sequence labeling. BMC Bioinformatics. 10(S4). S4–S4. 90 indexed citations

19.

Sinapov, Jivko & Alexander Stoytchev. (2008). Toward autonomous learning of an ontology of tool affordances by a robot. National Conference on Artificial Intelligence. 1828–1829. 1 indexed citations

20.

Caragea, Cornelia, Jivko Sinapov, Adrian Silvescu, Drena Dobbs, & Vasant Honavar. (2007). Glycosylation site prediction using ensembles of Support Vector Machine classifiers. BMC Bioinformatics. 8(1). 438–438. 132 indexed citations

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.

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