George Michailidis

12.6k total citations
257 papers, 7.7k citations indexed

About

George Michailidis is a scholar working on Molecular Biology, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, George Michailidis has authored 257 papers receiving a total of 7.7k indexed citations (citations by other indexed papers that have themselves been cited), including 59 papers in Molecular Biology, 45 papers in Computer Networks and Communications and 42 papers in Artificial Intelligence. Recurrent topics in George Michailidis's work include Statistical Methods and Inference (26 papers), Bioinformatics and Genomic Networks (24 papers) and Network Traffic and Congestion Control (23 papers). George Michailidis is often cited by papers focused on Statistical Methods and Inference (26 papers), Bioinformatics and Genomic Networks (24 papers) and Network Traffic and Congestion Control (23 papers). George Michailidis collaborates with scholars based in United States, Taiwan and United Kingdom. George Michailidis's co-authors include Ali Shojaie, Stilian Stoev, Elizaveta Levina, Michael Devetsikiotis, Subramaniam Pennathur, Jan de Leeuw, Mark V. Culp, Zi Yang, Ji Zhu and Alla Karnovsky and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Journal of Clinical Investigation.

In The Last Decade

George Michailidis

249 papers receiving 7.5k citations

Peers

George Michailidis

EEE

CNC

Weidong Liu China

Hong Yan Hong Kong

Ji Zhu United States

Xiaotong Shen United States

José A. Lozano Spain

Hoon Kim South Korea

Saharon Rosset Israel

Bor‐Sen Chen Taiwan

Madan M. Gupta India

Pedro Larrañaga Spain

Weidong Liu China

George Michailidis

3.0k ×1.1

725 ×0.8

306 ×0.4

EEE

1.4k ×2.1

155 ×0.2

CNC

Citations per year, relative to George Michailidis George Michailidis (= 1×) peers Weidong Liu

Countries citing papers authored by George Michailidis

Since Specialization

Citations

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

Fields of papers citing papers by George Michailidis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of George Michailidis

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

All Works

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20 of 20 papers shown

Michailidis, George, et al.. (2025). Multi-Objective Reverse Offloading in Edge Computing for AI Tasks. IEEE Open Journal of the Communications Society. 6. 2474–2485.

Safikhani, Abolfazl, et al.. (2024). A Functional Coefficients Network Autoregressive Model. Statistica Sinica.

Karnovsky, Alla, et al.. (2024). DNEA: an R package for fast and versatile data-driven network analysis of metabolomics data. BMC Bioinformatics. 25(1). 383–383.

Michailidis, George. (2023). Challenges for Anomaly Detection in Large-Scale Cyber-Physical Systems. SHILAP Revista de lepidopterología. 5(1). 2 indexed citations

Stevens, Nathaniel T., James Wilson, Ian McCulloh, et al.. (2021). The interdisciplinary nature of network monitoring: Advantages and disadvantages. Quality Engineering. 33(4). 731–735. 1 indexed citations

Stevens, Nathaniel T., James Wilson, Ian McCulloh, et al.. (2021). Broader impacts of network monitoring: Its role in government, industry, technology, and beyond. Quality Engineering. 33(4). 749–757. 2 indexed citations

Stevens, Nathaniel T., James Wilson, Ian McCulloh, et al.. (2021). Research in network monitoring: Connections with SPM and new directions. Quality Engineering. 33(4). 736–748. 6 indexed citations

Stevens, Nathaniel T., James Wilson, Ian McCulloh, et al.. (2021). Foundations of network monitoring: Definitions and applications. Quality Engineering. 33(4). 719–730. 3 indexed citations

Fort, Patrice E., Thekkelnaycke M. Rajendiran, Tanu Soni, et al.. (2021). Diminished retinal complex lipid synthesis and impaired fatty acid β-oxidation associated with human diabetic retinopathy. JCI Insight. 6(19). 25 indexed citations

10.

Leite, Walter L., et al.. (2021). The effects of a personalized recommendation system on students’ high-stakes achievement scores: A field experiment. Educational Data Mining. 4 indexed citations

11.

Banerjee, Moulinath, et al.. (2020). Change Point Estimation in a Dynamic Stochastic Block Model. Journal of Machine Learning Research. 21(107). 1–59. 13 indexed citations

12.

Afshinnia, Farsad, Thekkelnaycke M. Rajendiran, Tanu Soni, et al.. (2020). Plasma lipidomic profiling identifies a novel complex lipid signature associated with ischemic stroke in chronic kidney disease. Journal of Translational Science. 6(6). 13 indexed citations

13.

Choi, Seung‐Chul, Josephine Brown, Minghao Gong, et al.. (2020). Gut microbiota dysbiosis and altered tryptophan catabolism contribute to autoimmunity in lupus-susceptible mice. Science Translational Medicine. 12(551). 182 indexed citations

14.

Piyarathna, Danthasinghe Waduge Badrajee, James M. Arnold, Stacy M. Lloyd, et al.. (2019). ERR1- and PGC1α-associated mitochondrial alterations correlate with pan-cancer disparity in African Americans. Journal of Clinical Investigation. 129(6). 2351–2356. 24 indexed citations

15.

Ma, Jing, Ali Shojaie, & George Michailidis. (2019). A comparative study of topology-based pathway enrichment analysis methods. BMC Bioinformatics. 20(1). 546–546. 55 indexed citations

16.

Basu, Sumanta, William L. Duren, Charles R. Evans, et al.. (2017). Sparse network modeling and metscape-based visualization methods for the analysis of large-scale metabolomics data. Bioinformatics. 33(10). 1545–1553. 185 indexed citations

17.

Shojaie, Ali & George Michailidis. (2010). Penalized Principal Component Regression on Graphs for Analysis of Subnetworks. Neural Information Processing Systems. 23. 2155–2163. 8 indexed citations

18.

Culp, Mark V., Kjell Johnson, & George Michailidis. (2006). ada: AnRPackage for Stochastic Boosting. Journal of Statistical Software. 17(2). 70 indexed citations

19.

Michailidis, George, et al.. (2004). Estimating internal link loss rates using active network tomography.. Deep Blue (University of Michigan). 3 indexed citations

20.

Schwartz, Donald R., Sharon L. R. Kardia, Kerby Shedden, et al.. (2002). Gene expression in ovarian cancer reflects both morphology and biological behavior, distinguishing clear cell from other poor-prognosis ovarian carcinomas.. PubMed. 62(16). 4722–9. 348 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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