Nasim Sonboli

469 total citations
16 papers, 177 citations indexed

About

Nasim Sonboli is a scholar working on Information Systems, Artificial Intelligence and Safety Research. According to data from OpenAlex, Nasim Sonboli has authored 16 papers receiving a total of 177 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Information Systems, 5 papers in Artificial Intelligence and 5 papers in Safety Research. Recurrent topics in Nasim Sonboli's work include Recommender Systems and Techniques (9 papers), Ethics and Social Impacts of AI (5 papers) and Advanced Bandit Algorithms Research (4 papers). Nasim Sonboli is often cited by papers focused on Recommender Systems and Techniques (9 papers), Ethics and Social Impacts of AI (5 papers) and Advanced Bandit Algorithms Research (4 papers). Nasim Sonboli collaborates with scholars based in United States, Netherlands and Japan. Nasim Sonboli's co-authors include Robin Burke, Weiwen Liu, Jun Guo, Shengyu Zhang, Bamshad Mobasher, Michael D. Ekstrand, Masoud Mansoury, Rishabh Mehrotra, Mohammad Aliannejadi and Daniela Raicu and has published in prestigious journals such as AI Magazine, ACM SIGKDD Explorations Newsletter and Proceedings of the 31st ACM International Conference on Information & Knowledge Management.

In The Last Decade

Nasim Sonboli

16 papers receiving 174 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nasim Sonboli United States 7 126 77 59 34 30 16 177
Meike Zehlike Germany 5 58 0.5× 65 0.8× 46 0.8× 55 1.6× 24 0.8× 8 193
Preston McAfee United States 6 49 0.4× 76 1.0× 110 1.9× 27 0.8× 123 4.1× 8 232
Amra Delić Bosnia and Herzegovina 9 128 1.0× 62 0.8× 18 0.3× 5 0.1× 20 0.7× 29 204
A. Feder Cooper United States 6 76 0.6× 142 1.8× 17 0.3× 80 2.4× 32 1.1× 21 267
Vitalik Buterin United States 8 168 1.3× 47 0.6× 21 0.4× 8 0.2× 8 0.3× 13 234
Frances Ann Hubis Switzerland 3 38 0.3× 148 1.9× 42 0.7× 5 0.1× 31 1.0× 4 198
Rohan Ramanath United States 7 100 0.8× 144 1.9× 23 0.4× 11 0.3× 29 1.0× 10 245
Xiaowei Mei United States 4 77 0.6× 79 1.0× 11 0.2× 4 0.1× 18 0.6× 6 179
Navid Rekabsaz Austria 9 115 0.9× 173 2.2× 27 0.5× 29 0.9× 8 0.3× 30 280
Boris Düdder Denmark 7 104 0.8× 85 1.1× 11 0.2× 52 1.5× 25 0.8× 31 243

Countries citing papers authored by Nasim Sonboli

Since Specialization
Citations

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

Fields of papers citing papers by Nasim Sonboli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nasim Sonboli

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

All Works

16 of 16 papers shown
1.
Ekstrand, Michael D., et al.. (2023). FAccTRec 2023: The 6th Workshop on Responsible Recommendation. 1267–1268. 1 indexed citations
2.
Rahmani, Hossein A., et al.. (2022). Towards Confidence-aware Calibrated Recommendation. Proceedings of the 31st ACM International Conference on Information & Knowledge Management. 4344–4348. 6 indexed citations
3.
Sonboli, Nasim, Robin Burke, Michael D. Ekstrand, & Rishabh Mehrotra. (2022). The multisided complexity of fairness in recommender systems. AI Magazine. 43(2). 164–176. 13 indexed citations
4.
Burke, Robin, et al.. (2022). Multi-agent Social Choice for Dynamic Fairness-aware Recommendation. 234–244. 6 indexed citations
5.
Sonboli, Nasim, et al.. (2022). FAccTRec 2022: The 5th Workshop on Responsible Recommendation. 686–687. 2 indexed citations
6.
Ekstrand, Michael D., et al.. (2021). FAccTRec 2021: The 4th Workshop on Responsible Recommendation. 778–779. 2 indexed citations
7.
Sonboli, Nasim, Masoud Mansoury, Ziyue Guo, et al.. (2021). librec-auto: A Tool for Recommender Systems Experimentation. 4584–4593. 9 indexed citations
8.
Ekstrand, Michael D., et al.. (2020). 3rd FAccTRec Workshop: Responsible Recommendation. 607–608. 5 indexed citations
9.
Garcı́a, Marı́a N. Moreno, et al.. (2020). Using Social Tag Embedding in a Collaborative Filtering Approach for Recommender Systems. 502–507. 7 indexed citations
10.
Burke, Robin, Masoud Mansoury, & Nasim Sonboli. (2020). Experimentation with fairness-aware recommendation using librec-auto. 700–700. 2 indexed citations
11.
Sonboli, Nasim, et al.. (2020). Calibration in Collaborative Filtering Recommender Systems. 197–206. 12 indexed citations
12.
Sonboli, Nasim, et al.. (2020). Fairness-aware Recommendation with librec-auto. 594–596. 6 indexed citations
13.
Mobasher, Bamshad, et al.. (2019). Data Science Summer Academy for Chicago Public School Students. ACM SIGKDD Explorations Newsletter. 21(1). 49–52. 11 indexed citations
14.
Sonboli, Nasim & Robin Burke. (2019). Localized Fairness in Recommender Systems. 295–300. 6 indexed citations
15.
Liu, Weiwen, Jun Guo, Nasim Sonboli, Robin Burke, & Shengyu Zhang. (2019). Personalized fairness-aware re-ranking for microlending. 467–471. 40 indexed citations
16.
Burke, Robin, et al.. (2018). Balanced Neighborhoods for Multi-sided Fairness in Recommendation. 202–214. 49 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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