Michael Rabbat

11.5k total citations · 5 hit papers
121 papers, 5.3k citations indexed

About

Michael Rabbat is a scholar working on Computer Networks and Communications, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Michael Rabbat has authored 121 papers receiving a total of 5.3k indexed citations (citations by other indexed papers that have themselves been cited), including 74 papers in Computer Networks and Communications, 45 papers in Artificial Intelligence and 24 papers in Electrical and Electronic Engineering. Recurrent topics in Michael Rabbat's work include Distributed Control Multi-Agent Systems (44 papers), Distributed Sensor Networks and Detection Algorithms (19 papers) and Cooperative Communication and Network Coding (18 papers). Michael Rabbat is often cited by papers focused on Distributed Control Multi-Agent Systems (44 papers), Distributed Sensor Networks and Detection Algorithms (19 papers) and Cooperative Communication and Network Coding (18 papers). Michael Rabbat collaborates with scholars based in Canada, United States and Sweden. Michael Rabbat's co-authors include Robert D. Nowak, Mark Coates, Konstantinos I. Tsianos, Jarvis Haupt, Sean Lawlor, Tuncer C. Aysal, Waheed U. Bajwa, Naveen Eluru, Ahmed El-Geneidy and Ahmadreza Faghih-Imani and has published in prestigious journals such as PLoS ONE, Proceedings of the IEEE and IEEE Transactions on Signal Processing.

In The Last Decade

Michael Rabbat

118 papers receiving 5.1k citations

Hit Papers

5 papers align trajectories

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.

Distributed optimization in sensor networks

2004 571 citations Michael Rabbat et al. profile →
How land-use and urban form impact bicycle flows: evidence from the bicycle-sharing system (BIXI) in Montreal

2014 389 citations Ahmadreza Faghih-Imani, Naveen Eluru et al. profile →
Compressed Sensing for Networked Data

2008 385 citations Michael Rabbat et al. IEEE Signal Processing Magazine profile →
Learning Graphs From Data: A Signal Representation Perspective

2019 249 citations Xiaowen Dong, Dorina Thanou et al. IEEE Signal Processing Magazine profile →
Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture

2023 117 citations Mahmoud Assran, Ishan Misra et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michael Rabbat Canada	36	2.9k	1.6k	1.1k	1.1k	491	121	5.3k
Mark Coates Canada	40	2.4k 0.8×	2.0k 1.2×	990 0.9×	288 0.3×	393 0.8×	185	4.8k
Lance Kaplan United States	37	1.1k 0.4×	1.9k 1.2×	951 0.8×	178 0.2×	535 1.1×	239	4.8k
Zhiguo Shi China	36	1.4k 0.5×	1.1k 0.7×	2.3k 2.0×	495 0.5×	211 0.4×	349	6.5k
Hairong Qi United States	46	2.3k 0.8×	2.2k 1.4×	1.3k 1.1×	321 0.3×	96 0.2×	245	9.0k
Haipeng Peng China	44	2.8k 1.0×	1.5k 0.9×	1.7k 1.5×	308 0.3×	1.7k 3.4×	233	5.9k
T. Aaron Gulliver Canada	35	2.5k 0.9×	2.4k 1.5×	4.0k 3.5×	160 0.1×	82 0.2×	731	6.9k
Kevin Jones United States	33	989 0.3×	539 0.3×	532 0.5×	1.3k 1.2×	87 0.2×	208	4.8k
Antonios Tsourdos United Kingdom	50	1.8k 0.6×	1.3k 0.8×	1.0k 0.9×	365 0.3×	215 0.4×	589	9.4k
Guoru Ding China	35	3.0k 1.0×	1.1k 0.7×	3.0k 2.6×	338 0.3×	50 0.1×	211	6.2k
Anna Scaglione United States	50	5.6k 1.9×	995 0.6×	6.6k 5.8×	602 0.6×	908 1.8×	375	10.7k

Countries citing papers authored by Michael Rabbat

Since Specialization

Citations

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

Fields of papers citing papers by Michael Rabbat

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Rabbat

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Assran, Mahmoud, Mathilde Caron, Ishan Misra, et al.. (2021). Semi-Supervised Learning of Visual Features by Non-Parametrically Predicting View Assignments with Support Samples. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 8423–8432. 54 indexed citations

Wang, Jianyu, et al.. (2020). SloMo: Improving Communication-Efficient Distributed SGD with Slow Momentum. International Conference on Learning Representations. 9 indexed citations

Dong, Xiaowen, Dorina Thanou, Michael Rabbat, & Pascal Frossard. (2019). Learning Graphs From Data: A Signal Representation Perspective. IEEE Signal Processing Magazine. 36(3). 44–63. 249 indexed citations breakdown →

Assran, Mahmoud, Joshua Romoff, Nicolas Ballas, Joëlle Pineau, & Michael Rabbat. (2019). Gossip-based Actor-Learner Architectures for Deep Reinforcement Learning. arXiv (Cornell University). 32. 13299–13309. 2 indexed citations

Dimakis, Alexandros G., Soummya Kar, José M. F. Moura, Michael Rabbat, & Anna Scaglione. (2018). Gossip Algorithms for Distributed Signal Processing. Figshare. 142 indexed citations

Gripon, Vincent, et al.. (2018). Characterization and Inference of Graph Diffusion Processes From Observations of Stationary Signals. HAL (Le Centre pour la Communication Scientifique Directe). 82 indexed citations

Rabbat, Michael. (2015). Multi-agent mirror descent for decentralized stochastic optimization. 517–520. 19 indexed citations

Tsianos, Konstantinos I. & Michael Rabbat. (2014). Efficient Distributed Online Prediction and Stochastic Optimization with Approximate Distributed Mini-Batches. arXiv (Cornell University). 3 indexed citations

Faghih-Imani, Ahmadreza, et al.. (2014). How Does Land-Use and Urban Form Impact Bicycle Flows--Evidence from the Bicycle-Sharing System (BIXI) in Montreal. Transportation Research Board 93rd Annual MeetingTransportation Research Board. 13 indexed citations

10.

Magnússon, Sindri, Pradeep Chathuranga Weeraddana, Michael Rabbat, & Carlo Fischione. (2014). On the convergence of an alternating direction penalty method for nonconvex problems. 2014 48th Asilomar Conference on Signals, Systems and Computers. 793–797. 7 indexed citations

11.

Tsianos, Konstantinos I. & Michael Rabbat. (2013). Simple iteration-optimal distributed optimization. European Signal Processing Conference. 1–5. 1 indexed citations

12.

Üstebay, Deniz, et al.. (2013). Distributed underwater acoustic source localization and tracking. 634–638. 5 indexed citations

13.

Chen, Xi, et al.. (2011). Sequential Monte Carlo for simultaneous passive device-free tracking and sensor localization using received signal strength measurements. Information Processing in Sensor Networks. 342–353. 84 indexed citations

14.

Qin, Wen, Michael Rabbat, & Bo Yang. (2011). A correlation model for shadow fading in multi-hop wireless networks. Annual Simulation Symposium. 100–104.

15.

Üstebay, Deniz, Mark Coates, & Michael Rabbat. (2011). Distributed auxiliary particle filters using selective gossip. 3296–3299. 50 indexed citations

16.

Üstebay, Deniz, Boris N. Oreshkin, Mark Coates, & Michael Rabbat. (2009). Multi-hop Greedy Gossip with Eavesdropping. International Conference on Information Fusion. 140–145. 1 indexed citations

17.

Üstebay, Deniz, Rui Castro, & Michael Rabbat. (2009). Selective Gossip. 11 indexed citations

18.

Zhu, Xiaojin, Andrew B. Goldberg, Michael Rabbat, & Robert Nowak. (2008). Learning Bigrams from Unigrams. Meeting of the Association for Computational Linguistics. 656–664. 5 indexed citations

19.

Rabbat, Michael, et al.. (2006). Understanding the Topology of a Telephone Network via Internally-Sensed Network Tomography. 3. 977–980. 1 indexed citations

20.

Rabbat, Michael. (2003). RICE UNIVERSITY Multiple Source Network Tomography.

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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