Michal Kompan

Research areas: personalised recommendations, machine learning, artificial intelligence, information retrieval

Position: Chief Research & Innovations Officer

Email
Google Scholar
Research Gate
ORCiD
ResearcherID
LinkedIn

Michal focuses on recommender systems, machine learning, user modeling, and information retrieval. His research is focused on predictive modeling and customer behavior (e.g., churn prediction, next-item or multi-objective recommendation), as well as content-based adaptive models. He specifically addresses the recommender system in e-commerce, for instance the complementary products recommendations.

He participated in several research projects funded by the Slovak government or European union. As a principal investigator he led the “Modelling, prediction and evaluation of user behavior based on the web interaction for adaptation and personalization” (APVV), “European digital innovation hub Hopero” (Digital Europe) and “Trustworthy Multi-Objective and Multi-Stakeholder Recommenders” (Recovery and Resilience Plan) projects. Additionally, as a researcher he participated in: 5 projects funded by the Scientific and grant agency of Slovak Republic, 3 projects funded by the Slovak research and development agency and 4 projects funded by the European Union (Horizon 2020, Horizon Europe).

As a teacher, he has supervised more than 50 Bachelor’s and Master’s theses. To support the community, he has served as a reviewer or/and program committee member at several international conferences.

He is also a member of IEEE and senior member ACM and the Slovak informatics society. He has participated in many research projects in co-operation with industry such as Symbiosy by HB Reavis, Exponea, ZlavaDna, SME, Piano media and Orange SK.

Selected achievements

  • Co-authored the award-winning paper on social media auditing (Best Paper Award @ RecSys’21)
  • Member of the excellence team PeWe of Slovak University of Technology in Bratislava, lead prof. Mária Bieliková

Professional Service

Program or organizing committee member 

  • ACM Conference on Recommender Systems (RecSys)
  • International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR) 
  • The Web Conference (WWW)
  • European Conference on Advances in Databases and Information Systems (ADBIS)
  • ACM Conference on Hypertext and Social Media (Hypertext)
  • ACM International Conference on Web Search and Data Mining (WSDM)
  • ACM Conference on User Modeling, Adaptation and Personalization (UMAP)
  • International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP)
  • AAAI Conference on Artificial Intelligence (AAAI)
  • European Conference on Information Retrieval (ECIR)

Reviewer for several international journals 

  • Neural Computing and Applications 
  • Journal of Information Processing and Management
  • IEEE Transactions on Systems, Man and Cybernetics: Systems
  • International Journal of Continuing Engineering Education and Life-Long Learning
  • International Journal of Artificial Intelligence in Education
  • Journal of Organizational Computing and Electronic Commerce
  • IEEE Transactions on Learning Technologies
  • ACM Transactions on Recommender Systems

Member of

  • Association for Computing Machinery (senior member)
  • Slovak Society for Computer Science
  • Professional Evaluation Body of the Central Register of Publication Activity Records (2026)
  • Center for European Research in Trusted AI

Selected Student Supervising

PhD

  • Čief Matej – Recommender and adaptive web-based systems. External mentor: Branislav Kveton. Defended 2025.

Master

  • Slávka Ivaničová. Sequence based personalized recommendations. Defended 2022.
  • Ondrej Unger – User behavior pattern recognition. Defended 2020.
  • Markovičová Viktória – User style modeling with temporal dynamics. Defended 2020.
  • Pekarčík Daniel – Personalized recommendation considering sequence of interactions. Defended 2020.
  • Džurman Kamil – Preference-based user model for e-commerce. Defended 2020.
  • Balážová Michaela – Identification of Fake News on the Web. Defended 2019.
  • Blanárik Patrik – Meta-recommender: Adaptive selection of recommender approach. Defended 2019.
  • Kalafut Matúš – Graph-based recommender. Defended 2019.
  • Valčičák Miroslav – Product popularity prediction in e-commerce. Defended 2019.
  • Tibenský Peter – Products recommendation. Defended 2018.
  • Roštár Marek – Image enhanced personalised recommendation. Defended 2017.
  • Berger Patrik – Customer churn prediction in e-commerce. Defended 2017.
  • Hunka Mário – Scalable personalised recommendation. Defended 2017.
  • Lieskovský Adam – Scalable personalised recommendation. Defended 2015.
  • Svrček Martin – Visualization of generated recommendations. Defended 2015.
  • Kaššák Ondrej – Group recommendation for TV. Defended 2013.
  • Lačný Jozef – Personalised recommendation in e-learning. Defended 2012.

Bachelor

  • Unger Ondrej – Personalised recommendation on the Web. Defended 2019.
  • Tomaštík Nikolas – Personalised recommendation on the Web. Defended 2019.
  • Lam Tuan Dung – Customer behavior prediction in e-commerce. Defended 2018.
  • Balážová Michaela – Customer behavior prediction in e-commerce. Defended 2018.
  • Pitoňák Ondrej – Advanced search and visualization. Defended 2017.
  • Bachárová Zuzana – Customer behavior prediction. Defended 2017.
  • Kaššák Ondrej – Named entity recognition for Slovak. Defended 2012.