Mojtaba Khomami Abadi

1.7k total citations · 2 hit papers
12 papers, 1.2k citations indexed

About

Mojtaba Khomami Abadi is a scholar working on Experimental and Cognitive Psychology, Social Psychology and Cognitive Neuroscience. According to data from OpenAlex, Mojtaba Khomami Abadi has authored 12 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Experimental and Cognitive Psychology, 4 papers in Social Psychology and 4 papers in Cognitive Neuroscience. Recurrent topics in Mojtaba Khomami Abadi's work include Emotion and Mood Recognition (10 papers), EEG and Brain-Computer Interfaces (4 papers) and Mental Health Research Topics (4 papers). Mojtaba Khomami Abadi is often cited by papers focused on Emotion and Mood Recognition (10 papers), EEG and Brain-Computer Interfaces (4 papers) and Mental Health Research Topics (4 papers). Mojtaba Khomami Abadi collaborates with scholars based in Italy, United States and Singapore. Mojtaba Khomami Abadi's co-authors include Nicu Sebe, Ioannis Patras, Ramanathan Subramanian, Stefan Winkler, Radu L. Vieriu, Paolo Avesani, Seyed Mostafa Kia, Heng Yang, Tiago H. Falk and Rishabh Gupta and has published in prestigious journals such as IEEE Transactions on Affective Computing, Edinburgh Research Explorer and arXiv (Cornell University).

In The Last Decade

Mojtaba Khomami Abadi

12 papers receiving 1.1k citations

Hit Papers

AMIGOS: A Dataset for Affect, Personality and Mood Resear... 2016 2026 2019 2022 2018 2016 100 200 300 400
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. AMIGOS: A Dataset for Affect, Personality and Mood Research on Individuals and Groups
    2018 438 citations Mojtaba Khomami Abadi, Nicu Sebe et al. IEEE Transactions on Affective Computing profile →
  2. ASCERTAIN: Emotion and Personality Recognition Using Commercial Sensors
    2016 354 citations Ramanathan Subramanian, Mojtaba Khomami Abadi et al. IEEE Transactions on Affective Computing profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mojtaba Khomami Abadi Italy 10 899 714 251 195 158 12 1.2k
Soraia M. Alarcão Portugal 6 605 0.7× 696 1.0× 118 0.5× 68 0.3× 86 0.5× 12 862
Pasin Israsena Thailand 15 426 0.5× 777 1.1× 152 0.6× 46 0.2× 108 0.7× 45 1.0k
Ziyi Li China 4 419 0.5× 354 0.5× 111 0.4× 122 0.6× 67 0.4× 7 643
Sharifa Alghowinem United States 15 660 0.7× 272 0.4× 50 0.2× 359 1.8× 219 1.4× 42 1.1k
Setha Pan-ngum Thailand 11 410 0.5× 732 1.0× 139 0.6× 43 0.2× 86 0.5× 30 945
Mingyue Yang China 5 413 0.5× 351 0.5× 111 0.4× 94 0.5× 66 0.4× 9 621
Ateke Goshvarpour Iran 17 405 0.5× 777 1.1× 481 1.9× 56 0.3× 40 0.3× 84 1.0k
Robert Jenke Germany 6 563 0.6× 671 0.9× 100 0.4× 63 0.3× 97 0.6× 7 849
Atefeh Goshvarpour Iran 17 394 0.4× 747 1.0× 463 1.8× 53 0.3× 37 0.2× 76 973
Yisi Liu Singapore 16 365 0.4× 565 0.8× 130 0.5× 98 0.5× 46 0.3× 33 767

Countries citing papers authored by Mojtaba Khomami Abadi

Since Specialization
Citations

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

Fields of papers citing papers by Mojtaba Khomami Abadi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mojtaba Khomami Abadi. 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 Mojtaba Khomami Abadi. The network helps show where Mojtaba Khomami Abadi may publish in the future.

Co-authorship network of co-authors of Mojtaba Khomami Abadi

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

All Works

12 of 12 papers shown
1.
Abadi, Mojtaba Khomami, et al.. (2018). AMIGOS: A Dataset for Affect, Personality and Mood Research on Individuals and Groups. IEEE Transactions on Affective Computing. 12(2). 479–493. 438 indexed citations breakdown →
2.
Abadi, Mojtaba Khomami, et al.. (2017). AMIGOS: A dataset for Mood, personality and affect research on Individuals and GrOupS.. arXiv (Cornell University). 15 indexed citations
3.
Gupta, Rishabh, et al.. (2016). A Quality Adaptive Multimodal Affect Recognition System for User-Centric Multimedia Indexing. Institutional Research Information System (Università degli Studi di Trento). 317–320. 15 indexed citations
4.
Subramanian, Ramanathan, et al.. (2016). ASCERTAIN: Emotion and Personality Recognition Using Commercial Sensors. IEEE Transactions on Affective Computing. 9(2). 147–160. 354 indexed citations breakdown →
5.
Subramanian, Ramanathan, et al.. (2015). Implicit User-centric Personality Recognition Based on Physiological Responses to Emotional Videos. 239–246. 20 indexed citations
6.
Abadi, Mojtaba Khomami, Ramanathan Subramanian, Seyed Mostafa Kia, et al.. (2015). DECAF: MEG-Based Multimodal Database for Decoding Affective Physiological Responses. IEEE Transactions on Affective Computing. 6(3). 209–222. 253 indexed citations
7.
Rostamzadeh, Negar, et al.. (2015). Cluster encoding for modelling temporal variation in video. Edinburgh Research Explorer. 2 indexed citations
8.
Abadi, Mojtaba Khomami, et al.. (2015). Inference of personality traits and affect schedule by analysis of spontaneous reactions to affective videos. Institutional Research Information System (Università degli Studi di Trento). 1–8. 29 indexed citations
9.
Abadi, Mojtaba Khomami, Ramanathan Subramanian, Negar Rostamzadeh, et al.. (2014). A Multi-task Learning Framework for Time-continuous Emotion Estimation from Crowd Annotations. 17–23. 3 indexed citations
10.
Abadi, Mojtaba Khomami, et al.. (2013). Decoding affect in videos employing the MEG brain signal. Institutional Research Information System (Università degli Studi di Trento). 2004. 1–6. 12 indexed citations
11.
Abadi, Mojtaba Khomami, Seyed Mostafa Kia, Ramanathan Subramanian, Paolo Avesani, & Nicu Sebe. (2013). User-centric Affective Video Tagging from MEG and Peripheral Physiological Responses. Institutional Research Information System (Università degli Studi di Trento). 15 indexed citations
12.
Abadi, Mojtaba Khomami, Jacopo Staiano, Alessandro Cappelletti, Massimo Zancanaro, & Nicu Sebe. (2013). Multimodal Engagement Classification for Affective Cinema. Institutional Research Information System (Università degli Studi di Trento). 411–416. 10 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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