World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
30
Citations
7410
World Ranking
13856
National Ranking
220

Overview

Michail Vlachos is affiliated with the University of Lausanne in Switzerland and has contributed extensively to the field of computer science, with a primary focus on artificial intelligence. Their research portfolio includes more than 40 publications, spanning a variety of subfields such as artificial intelligence, computer vision and pattern recognition, information systems, biophysics, and electrical and electronic engineering.

The main topics in Michail Vlachos's work include:

  • Explainable Artificial Intelligence (XAI)
  • Adversarial Robustness in Machine Learning
  • Topic Modeling
  • Anomaly Detection Techniques and Applications
  • Machine Learning and Data Classification
  • Recommender Systems and Techniques
  • Cell Image Analysis Techniques

The scientist's recent papers demonstrate engagement with explainability and recommendation systems, including studies published in noted venues. Selected recent publications include:

  • "Explaining classifiers by constructing familiar concepts," 2022, Machine Learning
  • "Using Neural and Graph Neural Recommender Systems to Overcome Choice Overload: Evidence From a Music Education Platform," 2023, ACM Transactions on Information Systems
  • "Reflective-net: learning from explanations," 2023, Data Mining and Knowledge Discovery
  • "Deceptive XAI: Typology, Creation and Detection," 2023, SN Computer Science
  • "Deceptive AI Explanations: Creation and Detection," 2022, Proceedings of the 14th International Conference on Agents and Artificial Intelligence

Michail Vlachos collaborates frequently with several co-authors. Notable collaborators include Johannes Schneider, with whom they have co-authored multiple works, Ahmad Ajalloeian, Avi Arampatzis, Evangelos Kanoulas, and Theodora Tsikrika.

Their publications appear often in venues such as:

  • arXiv (Cornell University)
  • Proceedings of the 31st ACM International Conference on Information & Knowledge Management
  • ACM Transactions on Information Systems
  • Machine Learning
  • Data Mining and Knowledge Discovery

In addition to journal and conference papers, Michail Vlachos has contributed to academic book publications. One of their books, "Experimental IR Meets Multilinguality, Multimodality, and Interaction," was published by Springer Science+Business Media in 2023.

Best Publications

  • Discovering similar multidimensional trajectories

    M. Vlachos;G. Kollios;D. Gunopulos

  • Indexing multi-dimensional time-series with support for multiple distance measures

    Michail Vlachos;Marios Hadjieleftheriou;Dimitrios Gunopulos;Eamonn Keogh

  • Identifying similarities, periodicities and bursts for online search queries

    Michail Vlachos;Christopher Meek;Zografoula Vagena;Dimitrios Gunopulos

  • On Periodicity Detection and Structural Periodic Similarity

    Michail Vlachos;Philip S. Yu;Vittorio Castelli

  • LB_Keogh supports exact indexing of shapes under rotation invariance with arbitrary representations and distance measures

    Eamonn Keogh;Li Wei;Xiaopeng Xi;Sang-Hee Lee

  • Iterative incremental clustering of time series

    Jessica Lin;Michail Vlachos;Eamonn Keogh;Dimitrios Gunopulos

  • Iterative incremental clustering of time series

    Jessica Lin;Michail Vlachos;Eamonn J. Keogh;Dimitrios Gunopulos

  • Non-linear dimensionality reduction techniques for classification and visualization

    Michail Vlachos;Carlotta Domeniconi;Dimitrios Gunopulos;George Kollios

  • Mining Time Series Data

    Chotirat Ann Ratanamahatana;Jessica Lin;Dimitrios Gunopulos;Eamonn J. Keogh

  • A Wavelet-Based Anytime Algorithm for K-Means Clustering of Time Series

    Michail Vlachos;Jessica Lin;Eamonn Keogh;Dimitrios Gunopulos

  • Indexing Multidimensional Time-Series

    Michail Vlachos;Marios Hadjieleftheriou;Dimitrios Gunopulos;Eamonn Keogh

  • Online amnesic approximation of streaming time series

    T. Palpanas;M. Vlachos;E. Keogh;D. Gunopulos

  • Supporting exact indexing of arbitrarily rotated shapes and periodic time series under Euclidean and warping distance measures

    Eamonn Keogh;Li Wei;Xiaopeng Xi;Michail Vlachos

  • Rotation invariant distance measures for trajectories

    Michail Vlachos;D. Gunopulos;Gautam Das

  • NET-FLi: on-the-fly compression, archiving and indexing of streaming network traffic

    Francesco Fusco;Marc Ph. Stoecklin;Michail Vlachos

  • Robust similarity measures for mobile object trajectories

    M. Vlachos;D. Gunopulos;G. Kollios

  • Global distance-based segmentation of trajectories

    Aris Anagnostopoulos;Michail Vlachos;Marios Hadjieleftheriou;Eamonn Keogh

  • Computing Correlation Anomaly Scores Using Stochastic Nearest Neighbors

    T. Ide;S. Papadimitriou;M. Vlachos

  • Domain-Driven, Actionable Knowledge Discovery

    Longbing Cao;Chengqi Zhang

  • The threshold join algorithm for top-k queries in distributed sensor networks

    D. Zeinalipour-Yazti;Z. Vagena;D. Gunopulos;V. Kalogeraki

  • Mining Time Series Data

    Eamonn J. Keogh

Frequent Co-Authors

Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Dimitrios Gunopulos
Dimitrios Gunopulos National and Kapodistrian University of Athens
Eamonn Keogh
Eamonn Keogh University of California, Riverside
Claudio Lucchese
Claudio Lucchese Ca Foscari University of Venice
Vittorio Castelli
Vittorio Castelli IBM (United States)
Nick Koudas
Nick Koudas University of Toronto
Divesh Srivastava
Divesh Srivastava AT&T (United States)
George Kollios
George Kollios Boston University
Vana Kalogeraki
Vana Kalogeraki Athens University of Economics and Business
Marios Hadjieleftheriou
Marios Hadjieleftheriou AT&T (United States)

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