Michail Vlachos

5.4k total citations · 1 hit paper
81 papers, 3.3k citations indexed

About

Michail Vlachos is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Michail Vlachos has authored 81 papers receiving a total of 3.3k indexed citations (citations by other indexed papers that have themselves been cited), including 58 papers in Artificial Intelligence, 35 papers in Signal Processing and 30 papers in Computer Vision and Pattern Recognition. Recurrent topics in Michail Vlachos's work include Data Management and Algorithms (24 papers), Time Series Analysis and Forecasting (22 papers) and Algorithms and Data Compression (9 papers). Michail Vlachos is often cited by papers focused on Data Management and Algorithms (24 papers), Time Series Analysis and Forecasting (22 papers) and Algorithms and Data Compression (9 papers). Michail Vlachos collaborates with scholars based in United States, Switzerland and Italy. Michail Vlachos's 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 and has published in prestigious journals such as Information Sciences, IEEE Transactions on Knowledge and Data Engineering and Machine Learning.

In The Last Decade

Michail Vlachos

79 papers receiving 3.1k citations

Hit Papers

Discovering similar multidimensional trajectories 2003 2026 2010 2018 2003 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michail Vlachos United States 23 1.9k 1.3k 858 560 436 81 3.3k
Goce Trajcevski United States 29 2.2k 1.2× 1.9k 1.4× 579 0.7× 709 1.3× 539 1.2× 184 4.5k
Peter Scheuermann United States 24 1.8k 0.9× 1.4k 1.0× 493 0.6× 1.4k 2.5× 584 1.3× 127 3.6k
George Kollios United States 38 2.8k 1.5× 2.3k 1.7× 1.2k 1.4× 1.8k 3.2× 1.1k 2.5× 85 5.2k
Wen-Chih Peng Taiwan 24 790 0.4× 668 0.5× 264 0.3× 438 0.8× 436 1.0× 92 2.1k
Jae-Gil Lee South Korea 24 1.6k 0.8× 1.5k 1.1× 601 0.7× 469 0.8× 480 1.1× 90 3.4k
Zhifeng Bao Australia 26 1.0k 0.5× 839 0.6× 336 0.4× 665 1.2× 412 0.9× 153 2.3k
Kaushik Chakrabarti United States 27 2.6k 1.4× 1.8k 1.4× 1.1k 1.3× 965 1.7× 754 1.7× 52 4.1k
Yunjun Gao China 30 1.5k 0.8× 1.2k 0.9× 746 0.9× 886 1.6× 579 1.3× 261 3.3k
John F. Roddick Australia 24 1.1k 0.6× 1.3k 1.0× 434 0.5× 1.1k 1.9× 1.2k 2.7× 118 3.1k
Jianliang Xu Hong Kong 44 1.5k 0.8× 2.3k 1.7× 679 0.8× 3.0k 5.3× 1.3k 3.1× 353 6.0k

Countries citing papers authored by Michail Vlachos

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

20 of 20 papers shown
1.
Vlachou, Marilena, et al.. (2024). In vitro Modified Release Studies on Melatoninergic Fluorinated Phenylalkylamides:Circumventing their Lipophilicity for Oral Administration. Current Pharmaceutical Design. 30(18). 1433–1441. 1 indexed citations
2.
Schneider, Johannes, Christian Meske, & Michail Vlachos. (2023). Deceptive XAI: Typology, Creation and Detection. SN Computer Science. 5(1). 7 indexed citations
3.
Schneider, Johannes & Michail Vlachos. (2023). Reflective-net: learning from explanations. Data Mining and Knowledge Discovery. 38(5). 2975–2996. 4 indexed citations
4.
Vlachos, Michail, et al.. (2018). Addressing Interpretability and Cold-Start in Matrix Factorization for Recommender Systems. IEEE Transactions on Knowledge and Data Engineering. 31(7). 1253–1266. 23 indexed citations
5.
Schneider, Johannes & Michail Vlachos. (2017). Scalable density-based clustering with quality guarantees using random projections. Data Mining and Knowledge Discovery. 31(4). 972–1005. 16 indexed citations
6.
Vlachos, Michail, et al.. (2014). Improving Co-Cluster Quality with Application to Product Recommendations. 679–688. 12 indexed citations
7.
Vlachos, Michail, et al.. (2013). Right-Protected Data Publishing with Provable Distance-Based Mining. IEEE Transactions on Knowledge and Data Engineering. 26(8). 2014–2028. 6 indexed citations
8.
Fusco, Francesco, Michail Vlachos, & Xenofontas Dimitropoulos. (2012). RasterZip. 51–64. 9 indexed citations
9.
Zeinalipour-Yazti, Demetrios, Zografoula Vagena, Vana Kalogeraki, et al.. (2009). Finding the K highest-ranked answers in a distributed network. Computer Networks. 53(9). 1431–1449. 6 indexed citations
10.
Vlachos, Michail, Claudio Lucchese, Deepak Rajan, & Philip S. Yu. (2008). Ownership protection of shape datasets with geodesic distance preservation. ISTI Open Portal. 276–286. 3 indexed citations
11.
Lucchese, Claudio, Michail Vlachos, Deepak Rajan, & Philip S. Yu. (2008). Rights Protection of Trajectory Datasets. 1349–1351. 2 indexed citations
12.
Vlachos, Michail, Aris Anagnostopoulos, Olivier Verscheure, & Philip S. Yu. (2008). Online pairing of VoIP conversations. The VLDB Journal. 18(1). 77–98. 4 indexed citations
13.
Cao, Longbing, Chengqi Zhang, Qiang Yang, et al.. (2007). Domain-Driven, Actionable Knowledge Discovery. IEEE Intelligent Systems. 22(4). 78–88, c3. 49 indexed citations
14.
Keogh, Eamonn, Wei Li, Xiaopeng Xi, Sang‐Hee Lee, & Michail Vlachos. (2006). LB_Keogh supports exact indexing of shapes under rotation invariance with arbitrary representations and distance measures. Very Large Data Bases. 882–893. 135 indexed citations
15.
Verscheure, Olivier, Michail Vlachos, Aris Anagnostopoulos, et al.. (2006). Finding "Who Is Talking to Whom" in VoIP Networks via Progressive Stream Clustering. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 42. 667–677. 15 indexed citations
16.
Vlachos, Michail, Zografoula Vagena, Philip S. Yu, & Vassilis Athitsos. (2005). Rotation invariant indexing of shapes and line drawings. 131–138. 27 indexed citations
17.
Palpanas, Themis, et al.. (2004). Online amnesic approximation of streaming time series. 339–349. 95 indexed citations
18.
Vlachos, Michail, Christopher Meek, Zografoula Vagena, & Dimitrios Gunopulos. (2004). Identifying similarities, periodicities and bursts for online search queries. 131–142. 177 indexed citations
19.
Vlachos, Michail, Marios Hadjieleftheriou, Dimitrios Gunopulos, & Eamonn Keogh. (2003). Indexing multi-dimensional time-series with support for multiple distance measures. 22 indexed citations
20.
Vlachos, Michail, Carlotta Domeniconi, Dimitrios Gunopulos, George Kollios, & Nick Koudas. (2002). Non-linear dimensionality reduction techniques for classification and visualization. 645–651. 126 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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