George Michailidis
About
In The Last Decade
George Michailidis
249 papers receiving 7.5k citations
Peers
Comparison fields: 5 of 200
- Molecular Biology 2.8k
- Artificial Intelligence 904
- Electrical and Electronic Engineering 821
- Statistics and Probability 650
- Computer Networks and Communications 641
Countries citing papers authored by George Michailidis
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
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
| # | Title | Journal | Authors | Indexed citations |
|---|---|---|---|---|
| 1 | Multi-Objective Reverse Offloading in Edge Computing for AI Tasks | IEEE Open Journal of the Communications Society | George Michailidis, Dimitris Karampatzakis et al. | 0 |
| 2 | A Functional Coefficients Network Autoregressive Model | Statistica Sinica | Abolfazl Safikhani, George Michailidis et al. | 0 |
| 3 | DNEA: an R package for fast and versatile data-driven network analysis of metabolomics data | BMC Bioinformatics | Alla Karnovsky, George Michailidis et al. | 0 |
| 4 | Challenges for Anomaly Detection in Large-Scale Cyber-Physical Systems | SHILAP Revista de lepidopterología | George Michailidis | 2 |
| 5 | The interdisciplinary nature of network monitoring: Advantages and disadvantages | Quality Engineering | Nathaniel T. Stevens, James Wilson et al. | 1 |
| 6 | Broader impacts of network monitoring: Its role in government, industry, technology, and beyond | Quality Engineering | Nathaniel T. Stevens, James Wilson et al. | 2 |
| 7 | Research in network monitoring: Connections with SPM and new directions | Quality Engineering | Nathaniel T. Stevens, James Wilson et al. | 6 |
| 8 | Foundations of network monitoring: Definitions and applications | Quality Engineering | Nathaniel T. Stevens, James Wilson et al. | 3 |
| 9 | Diminished retinal complex lipid synthesis and impaired fatty acid β-oxidation associated with human diabetic retinopathy | JCI Insight | Patrice E. Fort, Thekkelnaycke M. Rajendiran et al. | 25 |
| 10 | The effects of a personalized recommendation system on students’ high-stakes achievement scores: A field experiment | Educational Data Mining | Walter L. Leite, George Michailidis et al. | 4 |
| 11 | Change Point Estimation in a Dynamic Stochastic Block Model | Journal of Machine Learning Research | Moulinath Banerjee, George Michailidis et al. | 13 |
| 12 | Plasma lipidomic profiling identifies a novel complex lipid signature associated with ischemic stroke in chronic kidney disease | Journal of Translational Science | Farsad Afshinnia, Thekkelnaycke M. Rajendiran et al. | 13 |
| 13 | Gut microbiota dysbiosis and altered tryptophan catabolism contribute to autoimmunity in lupus-susceptible mice | Science Translational Medicine | Seung‐Chul Choi, Josephine Brown et al. | 182 |
| 14 | ERR1- and PGC1α-associated mitochondrial alterations correlate with pan-cancer disparity in African Americans | Journal of Clinical Investigation | Danthasinghe Waduge Badrajee Piyarathna, James M. Arnold et al. | 24 |
| 15 | A comparative study of topology-based pathway enrichment analysis methods | BMC Bioinformatics | Jing Ma, Ali Shojaie et al. | 55 |
| 16 | Sparse network modeling and metscape-based visualization methods for the analysis of large-scale metabolomics data | Bioinformatics | Sumanta Basu, William L. Duren et al. | 185 |
| 17 | Penalized Principal Component Regression on Graphs for Analysis of Subnetworks | Neural Information Processing Systems | Ali Shojaie, George Michailidis | 8 |
| 18 | ada: AnRPackage for Stochastic Boosting | Journal of Statistical Software | Mark V. Culp, Kjell Johnson et al. | 70 |
| 19 | Estimating internal link loss rates using active network tomography. | Deep Blue (University of Michigan) | George Michailidis, Vijayan N. Nair et al. | 3 |
| 20 | Gene expression in ovarian cancer reflects both morphology and biological behavior, distinguishing clear cell from other poor-prognosis ovarian carcinomas. | PubMed | Donald R. Schwartz, Sharon L. R. Kardia et al. | 348 |
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.