Mor Vered

428 total citations
24 papers, 219 citations indexed

About

Mor Vered is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Mor Vered has authored 24 papers receiving a total of 219 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 6 papers in Computer Vision and Pattern Recognition and 4 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Mor Vered's work include AI-based Problem Solving and Planning (9 papers), Robotic Path Planning Algorithms (6 papers) and Logic, Reasoning, and Knowledge (4 papers). Mor Vered is often cited by papers focused on AI-based Problem Solving and Planning (9 papers), Robotic Path Planning Algorithms (6 papers) and Logic, Reasoning, and Knowledge (4 papers). Mor Vered collaborates with scholars based in Australia, Israel and Brazil. Mor Vered's co-authors include Gal A. Kaminka, Felipe Meneguzzi, Tim Miller, Noa Agmon, Ramon Fraga Pereira, Alan Petersen, Adrian Carter, Liz Sonenberg, Bárbara Barbosa Neves and Piers D. L. Howe and has published in prestigious journals such as Social Science & Medicine, Journal of the American Geriatrics Society and Artificial Intelligence.

In The Last Decade

Mor Vered

24 papers receiving 211 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Mor Vered Australia	8	135	39	26	24	18	24	219
Izidor Mlakar Slovenia	9	68 0.5×	22 0.6×	16 0.6×	6 0.3×	52 2.9×	52	209
Rina Azoulay Israel	6	114 0.8×	23 0.6×	15 0.6×	7 0.3×	26 1.4×	24	226
Ivan Donadello Italy	10	181 1.3×	28 0.7×	32 1.2×	15 0.6×	7 0.4×	22	261
Shubo Tian United States	9	171 1.3×	114 2.9×	7 0.3×	9 0.4×	7 0.4×	19	356
Elisa Nguyen Netherlands	5	171 1.3×	40 1.0×	21 0.8×	18 0.8×	9 0.5×	5	294
Larry Chan United States	5	183 1.4×	40 1.0×	22 0.8×	62 2.6×	51 2.8×	7	298
Cindy Mason United States	7	78 0.6×	51 1.3×	16 0.6×	5 0.2×	19 1.1×	18	232
Ashwin Kalyan United States	9	150 1.1×	18 0.5×	25 1.0×	24 1.0×	8 0.4×	13	212
Samuel Jenkins United States	2	184 1.4×	39 1.0×	24 0.9×	88 3.7×	14 0.8×	2	267
Sebastian Farquhar United Kingdom	4	86 0.6×	51 1.3×	9 0.3×	15 0.6×	9 0.5×	8	215

Countries citing papers authored by Mor Vered

Since Specialization

Citations

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

Fields of papers citing papers by Mor Vered

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mor Vered

This figure shows the co-authorship network connecting the top 25 collaborators of Mor Vered. A scholar is included among the top collaborators of Mor Vered 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 Mor Vered. Mor Vered 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

Li, Boying, Lizhen Qu, Julián Gutiérrez, et al.. (2025). NEUSIS: A Compositional Neuro-Symbolic Framework for Autonomous Perception, Reasoning, and Planning in Complex UAV Search Missions. IEEE Robotics and Automation Letters. 10(9). 9502–9509. 1 indexed citations

Teshale, Achamyeleh Birhanu, Htet Lin Htun, Mor Vered, et al.. (2025). Integrating Social Determinants of Health and Established Risk Factors to Predict Cardiovascular Disease Risk Among Healthy Older Adults. Journal of the American Geriatrics Society. 73(6). 1797–1807. 2 indexed citations

Teshale, Achamyeleh Birhanu, Htet Lin Htun, Alice Owen, et al.. (2024). Gender-specific aspects of socialisation and risk of cardiovascular disease among community-dwelling older adults: a prospective cohort study using machine learning algorithms and a conventional method. Journal of Epidemiology & Community Health. 78(12). 737–744. 5 indexed citations

Teshale, Achamyeleh Birhanu, Htet Lin Htun, Mor Vered, et al.. (2024). Artificial intelligence improves risk prediction in cardiovascular disease. GeroScience. 47(4). 5497–5502. 1 indexed citations

Neves, Bárbara Barbosa, et al.. (2024). Navigating artificial intelligence in care homes: Competing stakeholder views of trust and logics of care. Social Science & Medicine. 358. 117187–117187. 4 indexed citations

Teshale, Achamyeleh Birhanu, Htet Lin Htun, Mor Vered, Alice Owen, & Rosanne Freak‐Poli. (2024). A Systematic Review of Artificial Intelligence Models for Time-to-Event Outcome Applied in Cardiovascular Disease Risk Prediction. Journal of Medical Systems. 48(1). 68–68. 7 indexed citations

Miller, Tim, et al.. (2023). Explainable Goal Recognition: A Framework Based on Weight of Evidence. Proceedings of the International Conference on Automated Planning and Scheduling. 33(1). 7–16. 1 indexed citations

Vered, Mor, et al.. (2023). The effects of explanations on automation bias. Artificial Intelligence. 322. 103952–103952. 14 indexed citations

Graziani, Mara, Davide Calvaresi, Mor Vered, et al.. (2022). A global taxonomy of interpretable AI: unifying the terminology for the technical and social sciences. Artificial Intelligence Review. 56(4). 3473–3504. 65 indexed citations

10.

Miller, Tim, et al.. (2021). Human centered explanation for goal recognition system.. Monash University Research Portal (Monash University). 2 indexed citations

11.

Vered, Mor, et al.. (2021). What’s the Context? Implicit and Explicit Assumptions in Model-Based Goal Recognition. Monash University Research Portal (Monash University). 4516–4523. 7 indexed citations

12.

Lipovetzky, Nir, et al.. (2021). Behaviour Recognition with Kinodynamic Planning Over Continuous Domains. Frontiers in Artificial Intelligence. 4. 717003–717003. 5 indexed citations

13.

Vered, Mor, Piers D. L. Howe, Tim Miller, Liz Sonenberg, & Eduardo Velloso. (2020). Demand-Driven Transparency for Monitoring Intelligent Agents. IEEE Transactions on Human-Machine Systems. 50(3). 264–275. 11 indexed citations

14.

Vered, Mor, et al.. (2018). Online Goal Recognition as Reasoning over Landmarks. National Conference on Artificial Intelligence. 638–645. 2 indexed citations

15.

Vered, Mor, et al.. (2018). Towards online goal recognition combining goal mirroring and landmarks: extended abstract. Adaptive Agents and Multi-Agents Systems. 2112–2114. 1 indexed citations

16.

Vered, Mor, et al.. (2018). Towards Online Goal Recognition Combining Goal Mirroring and Landmarks. Research Explorer (The University of Manchester). 3. 2112–2114. 10 indexed citations

17.

Vered, Mor & Gal A. Kaminka. (2017). Online Recognition of Navigation Goals Through Goal Mirroring. Adaptive Agents and Multi-Agents Systems. 3. 1748–1750. 1 indexed citations

18.

Vered, Mor & Gal A. Kaminka. (2017). Online recognition of navigation goals through goal mirroring: (extended abstract). Adaptive Agents and Multi-Agents Systems. 1748–1750. 1 indexed citations

19.

Vered, Mor, et al.. (2016). Online goal recognition through mirroring: humans and agents. 25 indexed citations

20.

Vered, Mor, et al.. (2015). [Medical image enhancement: Sharpening].. PubMed. 32(2). 10–2, 36. 2 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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