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Michalis Vlachos


Professeur ordinaire
Département des systèmes d'information

Internef, bureau 135
Tél 021.692.33.00

Adresse postale
Université de Lausanne
Quartier UNIL-Chamberonne
Bâtiment Internef
1015 Lausanne


master Big-Scale Analytics
Formation concernée
Maîtrise universitaire ès Sciences en systèmes d'information
bachelor Business Intelligence and Analytics
Formations concernées
Baccalauréat universitaire ès Sciences en management
Baccalauréat universitaire ès Sciences en économie politique
Baccalauréat universitaire en sciences économiques
master Data Mining and Machine Learning
Formation concernée
Maîtrise universitaire ès Sciences en systèmes d'information


Ahmad Ajalloeian

  Mathilde Boccara

Lucas Franco Betzler

  Jonas Heim

Kamil Seghrouchni

  Frédéric Spycher



26 dernières publications

: Revue avec comité de lecture


Schneider Johannes, Joshua Handali, Michalis Vlachos ; Christian Meske (submitted). Deceptive AI Explanations: Creation and Detection. CoRR abs/2001.07641.


Freris Nikolaos M., Yang Chuhan ; Vlachos Michalis (2020). FIDE: Fast and Interpretable 2D Embedding with correlation, distance, and rank considerations. 2020 6th International Conference on Big Data Computing and Communications (BIGCOM).

Schneider Johannes , Vlachos Michalis (2020). Personalization of Deep Learning. International Data Science Conference. Revue avec comité de lecture


Fusco Francesco, Vlachos Michalis, Vasileiadis Vasileios, Wardatzky Kathrin ; Schneider Johannes (2019, Jan). RecoNet: An Interpretable Neural Architecture for Recommender Systems. Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence. Revue avec comité de lecture

Schneider Johannes , Vlachos Michalis (2019). Mass Personalization of Deep Learning.

Vlachos Michalis, Duenner Celestine, Heckel Reinhard, Vassiliadis Vassilios G., Parnell Thomas P. ; Atasu Kubilay (2019). Addressing Interpretability and Cold-Start in Matrix Factorization for Recommender Systems. IEEE Transactions on Knowledge and Data Engineering. Revue avec comité de lecture


Atasu K., Parnell T., Dunner C., Sifalakis M., Pozidis H., Vasileiadis V. et al. (2018). Linear-complexity relaxed word Mover’s distance with GPU acceleration. Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017, 2018-January, 889-896.

Vlachos Michail (2018). Indexing and Similarity Search. Encyclopedia of Database Systems.

Zouzias Anastasios , Vlachos Michalis (2018). Very-Low Random Projection Maps.


Atasu K., Parnell T., Dunner C., Vlachos M. ; Pozidis H. (2017). High-Performance Recommender System Training Using Co-Clustering on CPU/GPU Clusters. Proceedings of the International Conference on Parallel Processing, 372-381.

Heckel Reinhard , Vlachos Michalis (2017). Private and Right-Protected Big Data Publication: An Analysis. Proceedings of the 2017 SIAM International Conference on Data Mining (pp. 660-668). Society for Industrial and Applied Mathematics.


Vlachos M., Vassiliadis V.G., Heckel R. ; Labbi A. (2016). Toward interpretable predictive models in B2B recommender systems. IBM Journal of Research and Development, 60.


Vlachos Michalis, Freris Nikolaos M. ; Kyrillidis Anastasios (2015). Compressive mining: fast and optimal data mining in the compressed domain. The VLDB Journal, 24, 1-24.

Vlachos Michalis, Schneider Johannes ; Vassiliadis Vassilios G. (2015). On Data Publishing with Clustering Preservation. ACM Trans. Knowl. Discov. Data, 9, 1-30.


Schneider J. , Vlachos M. (2014). On randomly projected hierarchical clustering with guarantees. SIAM International Conference on Data Mining 2014, SDM 2014, 1, 407-415.

Schneider Johannes, Bogojeska Jasmina ; Vlachos Michail (2014, Jan). Solving Linear SVMs with Multiple 1D Projections. Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management - CIKM 14. Association for Computing Machinery (ACM).

Zoumpoulis Spyros I., Vlachos Michail, Freris Nikolaos M. ; Lucchese Claudio (2014). Right-Protected Data Publishing with Provable Distance-Based Mining. IEEE Trans. Knowl. Data Eng., 26, 2014-2028.


Schneider Johannes , Vlachos Michail (2013, Jan). Fast parameterless density-based clustering via random projections. Proceedings of the 22nd ACM international conference on Conference on information & knowledge management - CIKM 13. ACM Press.


Freris N.M., Vlachos M. ; Turaga D.S. (2012). Cluster-aware compression with provable k-means preservation. Proceedings of the 12th SIAM International Conference on Data Mining, SDM 2012, 82-93.

Vlachos Michail, Wieczorek Aleksander ; Schneider Johannes (2012, Jan). Right-protected data publishing with hierarchical clustering preservation. Proceedings of the 21st ACM international conference on Information and knowledge management - CIKM 12. Association for Computing Machinery (ACM).


Lucchese Claudio, Vlachos Michail, Rajan Deepak ; Yu Philip S. (2010). Rights protection of trajectory datasets with nearest-neighbor preservation. The VLDB Journal, 19, 531-556.

Svonava Daniel , Vlachos Michail (2010, Déc). Visualizing Graphs Using Minimum Spanning Dendrograms. 2010 IEEE International Conference on Data Mining. Institute of Electrical & Electronics Engineers (IEEE).

Vlachos Michail, Kozat Suleyman S. ; Yu Philip S. (2010). Optimal distance bounds for fast search on compressed time-series query logs. ACM Trans. Web, 4, 1-28.


Ratanamahatana Chotirat Ann, Lin Jessica, Gunopulos Dimitrios, Keogh Eamonn, Vlachos Michail ; Das Gautam (2009). Mining Time Series Data. Data Mining and Knowledge Discovery Handbook (pp. 1049-1077). Springer Science $\mathplus$ Business Media.


Vlachos Michalis, Anagnostopoulos Aris, Verscheure Olivier ; Yu Philip S. (2008). Online pairing of VoIP conversations. The VLDB Journal, 18, 77-98.


Vlachos Michail, Wu Kun-Lung, Chen Shyh-Kwei ; Yu Philip S. (2007). Correlating burst events on streaming stock market data. Data Mining and Knowledge Discovery, 16, 109-133.


Expériences professionnelles

Research Staff Member: Team Lead on Enterprise Recommender Systems
IBM Research - Zurich

Research Staff Member
IBM Research - New York, USA
Research on time-series analytics, data mining and machine learning

Visiting Researcher
Microsoft Research, Machine Learning and Applied Statistics

Prix et distinctions scientifiques

ERC Starting Grant
"Exact Mining from InExact Data"
Année : 2011

Récipiendaire : Michalis Vlachos

Best Paper Runner Up: SIAM Data Mining International Conference
For work on scalable density-based clustering.
Année : 2014

Outstanding Technical Achievement Award: "Efficient Indexing and Searching on Big Data", IBM
Année : 2015

Best Paper Award, IEEE International Conference in Data Engineering
"Best of ICDE 2017" paper, IEEE International Conference in Data Engineering. For research work on interpretable recommender systems.
Année : 2017

Distinguished Alumnus Award, Informatics Dept., Aristotle University Thessaloniki
Année : 2017

Research Division Award: "Watson Company Analyzer (WCA)", IBM
Année : 2017

Member: IBM Academy of Technology
Année : 2018

IBM Corporate Award
"Data-Driven IBM Sales Transformation"
Année : 2018


  • data science, machine learning, recommender systems, information retrieval


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