Michail Vlachos
- Signal Processing top 0.2%
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 1%
- Computer Networks and Communications top 2%
- Information Systems top 2%
- Co-authors
- Dimitrios GunopulosGeorge KolliosEamonn KeoghMarios HadjieleftheriouPhilip S. YuVittorio CastelliZografoula VagenaChristopher Meek
- Topics
- Data Management and Algorithms (24 papers)Time Series Analysis and Forecasting (22 papers)Algorithms and Data Compression (9 papers)
- Partner nations
- United StatesSwitzerlandItaly
In The Last Decade
Michail Vlachos
79 papers receiving 3.1k citations
Hit Papers
Peers
Comparison fields: 5 of 129
- Signal Processing 1.9k
- Artificial Intelligence 1.3k
- Computer Vision and Pattern Recognition 858
- Computer Networks and Communications 560
- Information Systems 436
Countries citing papers authored by Michail Vlachos
This map shows the geographic impact of Michail Vlachos'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 Michail Vlachos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michail Vlachos more than expected).
Fields of papers citing papers by Michail Vlachos
This network shows the impact of papers produced by Michail Vlachos. 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 Michail Vlachos. The network helps show where Michail Vlachos may publish in the future.
Co-authorship network of co-authors of Michail Vlachos
This figure shows the co-authorship network connecting the top 25 collaborators of Michail Vlachos. A scholar is included among the top collaborators of Michail Vlachos 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 Michail Vlachos. Michail Vlachos is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 7 | |
| 3 | 4 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 23 | |
| 7 | 29 | |
| 8 | 26 | |
| 9 | 9 | |
| 10 | 6 | |
| 11 | 3 | |
| 12 | 20 | |
| 13 | 2 | |
| 14 | 135 | |
| 15 | 167 | |
| 16 | 27 | |
| 17 | 95 | |
| 18 | 22 | |
| 19 | Discovering similar multidimensional trajectoriesbreakdown → | 998 |
| 20 | 126 |
About Michail Vlachos
Michail Vlachos is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 81 papers that have together received 3.3k indexed citations. Recurring topics across this work include Data Management and Algorithms (24 papers), Time Series Analysis and Forecasting (22 papers) and Algorithms and Data Compression (9 papers). The work is most often cited by research in Signal Processing (1.9k citations), Transportation (311 citations) and Computer Vision and Pattern Recognition (858 citations). Michail Vlachos has collaborated with scholars based in United States, Switzerland and Italy. Frequent co-authors include Dimitrios Gunopulos, George Kollios, Eamonn Keogh, Marios Hadjieleftheriou, Philip S. Yu, Vittorio Castelli, Zografoula Vagena, Christopher Meek, Francesco Fusco and Sang‐Hee Lee. Their work appears in journals such as Information Sciences, IEEE Transactions on Knowledge and Data Engineering and Machine Learning.
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.