Daniel Omeiza

434 total citations
11 papers, 101 citations indexed

About

Daniel Omeiza is a scholar working on Artificial Intelligence, Safety Research and Social Psychology. According to data from OpenAlex, Daniel Omeiza has authored 11 papers receiving a total of 101 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 4 papers in Safety Research and 3 papers in Social Psychology. Recurrent topics in Daniel Omeiza's work include Explainable Artificial Intelligence (XAI) (8 papers), Ethics and Social Impacts of AI (4 papers) and Human-Automation Interaction and Safety (3 papers). Daniel Omeiza is often cited by papers focused on Explainable Artificial Intelligence (XAI) (8 papers), Ethics and Social Impacts of AI (4 papers) and Human-Automation Interaction and Safety (3 papers). Daniel Omeiza collaborates with scholars based in United Kingdom, United States and Sweden. Daniel Omeiza's co-authors include Lars Kunze, Marina Jirotka, Lili Jiang, Shuyang Sun, Daniele De Martini, Paul Newman, Matthew Gadd, Seyun Kim, Martim Brandão and Malte Jung and has published in prestigious journals such as Image and Vision Computing, Transportation Research Part F Traffic Psychology and Behaviour and Research Publications (Maastricht University).

In The Last Decade

Daniel Omeiza

11 papers receiving 97 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Daniel Omeiza United Kingdom	6	56	23	22	18	9	11	101
Klaus Broelemann Germany	6	29 0.5×	26 1.1×	9 0.4×	23 1.3×	3 0.3×	16	116
Stephanie Milani United States	5	57 1.0×	7 0.3×	13 0.6×	8 0.4×	1 0.1×	9	141
Célia Martinie France	7	39 0.7×	10 0.4×	29 1.3×	19 1.1×	9 1.0×	23	114
Juanwu Lu United States	5	22 0.4×	26 1.1×	7 0.3×	27 1.5×	4 0.4×	7	62
Joakim Johnander Sweden	4	20 0.4×	18 0.8×	4 0.2×	18 1.0×	2 0.2×	8	52
Karol Zieba United States	3	58 1.0×	36 1.6×	3 0.1×	49 2.7×	4 0.4×	4	96
Iqra Ameer Mexico	7	140 2.5×	7 0.3×	23 1.0×	9 0.5×	20 2.2×	19	192
Gurkirt Singh Switzerland	4	48 0.9×	23 1.0×	5 0.2×	74 4.1×	3 0.3×	6	102
Bolin Gao Canada	6	24 0.4×	45 2.0×	8 0.4×	43 2.4×	7 0.8×	13	128
Nur Yildirim United States	4	33 0.6×	8 0.3×	12 0.5×	11 0.6×	1 0.1×	7	99

Countries citing papers authored by Daniel Omeiza

Since Specialization

Citations

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

Fields of papers citing papers by Daniel Omeiza

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Omeiza

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

All Works

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11 of 11 papers shown

1.

Omeiza, Daniel, et al.. (2025). A transparency paradox? Investigating the impact of explanation specificity and autonomous vehicle imperfect detection capabilities on passengers. Transportation Research Part F Traffic Psychology and Behaviour. 109. 1275–1292. 2 indexed citations

2.

Sun, Shuyang, et al.. (2024). RAG-Driver: Generalisable Driving Explanations with Retrieval-Augmented In-Context Multi-Modal Large Language Model Learning. 15 indexed citations

3.

Martini, Daniele De, et al.. (2023). Explainable Action Prediction through Self-Supervision on Scene Graphs. 1479–1485. 7 indexed citations

4.

Omeiza, Daniel, et al.. (2023). Textual Explanations for Automated Commentary Driving. 1–6. 4 indexed citations

5.

Kim, Seyun, et al.. (2022). Fairness and Transparency in Human-Robot Interaction. 2022 17th ACM/IEEE International Conference on Human-Robot Interaction (HRI). 1244–1246. 4 indexed citations

6.

Omeiza, Daniel, et al.. (2021). Context-based image explanations for deep neural networks. Image and Vision Computing. 116. 104310–104310. 12 indexed citations

7.

Omeiza, Daniel, et al.. (2021). Towards Explainable and Trustworthy Autonomous Physical Systems. Research Publications (Maastricht University). 1–3. 2 indexed citations

8.

Omeiza, Daniel, et al.. (2021). Why Not Explain? Effects of Explanations on Human Perceptions of Autonomous Driving. Research Publications (Maastricht University). 194–199. 6 indexed citations

9.

Omeiza, Daniel, et al.. (2021). Towards Accountability: Providing Intelligible Explanations in Autonomous Driving. Oxford University Research Archive (ORA) (University of Oxford). 231–237. 22 indexed citations

10.

Omeiza, Daniel, et al.. (2021). Assessing and Explaining Collision Risk in Dynamic Environments for Autonomous Driving Safety. Oxford University Research Archive (ORA) (University of Oxford). 223–230. 22 indexed citations

11.

Binns, Reuben, Max Van Kleek, Ge Wang, et al.. (2021). A Fait Accompli? An Empirical Study into the Absence of Consent to Third-Party Tracking in Android Apps. Lirias (KU Leuven). 5 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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