Michail Vlachos

Michail Vlachos is a researcher affiliated with the University of Lausanne, Switzerland, with a focus on data mining, machine learning, and interpretable AI. His work spans algorithm design, time-series analysis, and data privacy, often intersecting with applications in recommender systems and neural network transparency.

• Research Interests: Data mining, machine learning, XAI (Explainable AI), time-series analysis, clustering algorithms, privacy-preserving data publishing, and recommender systems.

Publication Trends: Recent work emphasizes interpretable deep learning architectures (2024), detection of deceptive AI explanations (2023), and neural recommender systems for educational platforms (2024). Earlier contributions include compressive data mining (2015), clustering preservation techniques (2017), and trajectory analysis (2009).

• Collaborations: Regularly works with Johannes Schneider, Ahmad Ajalloeian, and teams from institutions like IBM Research, ETH Zurich, and University of Lausanne.