Mike Rabbat

649 total citations
2 papers, 24 citations indexed

About

Mike Rabbat is a scholar working on Artificial Intelligence, Information Systems and Infectious Diseases. According to data from OpenAlex, Mike Rabbat has authored 2 papers receiving a total of 24 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Artificial Intelligence, 1 paper in Information Systems and 0 papers in Infectious Diseases. Recurrent topics in Mike Rabbat's work include Intelligent Tutoring Systems and Adaptive Learning (1 paper), Recommender Systems and Techniques (1 paper) and Privacy-Preserving Technologies in Data (1 paper). Mike Rabbat is often cited by papers focused on Intelligent Tutoring Systems and Adaptive Learning (1 paper), Recommender Systems and Techniques (1 paper) and Privacy-Preserving Technologies in Data (1 paper). Mike Rabbat collaborates with scholars based in United States. Mike Rabbat's co-authors include Kiwan Maeng, Carole-Jean Wu, John Nguyen, Luca Melis, Haiyu Lu, Brandon Lucia, Caroline Trippel, Jiyan Yang, Bor-Yiing Su and Vikram Saraph and has published in prestigious journals such as .

In The Last Decade

Mike Rabbat

2 papers receiving 23 citations

Peers

Mike Rabbat
Joyce Cahoon United States
Julia Hesse Switzerland
Po-Wei Wang United States
Ward Beullens Switzerland
Lan Nguyen Australia
Musarat Hussain United Kingdom
Joyce Cahoon United States
Mike Rabbat
Citations per year, relative to Mike Rabbat Mike Rabbat (= 1×) peers Joyce Cahoon

Countries citing papers authored by Mike Rabbat

Since Specialization
Citations

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

Fields of papers citing papers by Mike Rabbat

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mike Rabbat

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

All Works

2 of 2 papers shown
1.
Maeng, Kiwan, Haiyu Lu, Luca Melis, et al.. (2022). Towards Fair Federated Recommendation Learning: Characterizing the Inter-Dependence of System and Data Heterogeneity. 156–167. 18 indexed citations
2.
Maeng, Kiwan, Vikram Saraph, Bor-Yiing Su, et al.. (2021). Understanding and Improving Failure Tolerant Training for Deep Learning Recommendation with Partial Recovery. 3. 637–651. 6 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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