World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
54
Citations
16470
World Ranking
4465
National Ranking
18

Overview

Ioannis Vlahavas is affiliated with Aristotle University of Thessaloniki in Greece. Their research primarily spans the domain of Computer Science, with a total of 61 publications. Within this broad field, the focus is notably on Artificial Intelligence, covering 48 published works, alongside contributions in Management Science and Operations Research, Molecular Biology, Clinical Psychology, and Economics and Econometrics.

The main research topics addressed by Ioannis Vlahavas include:

  • Topic Modeling
  • Natural Language Processing Techniques
  • Stock Market Forecasting Methods
  • Reinforcement Learning in Robotics
  • Biomedical Text Mining and Ontologies
  • Time Series Analysis and Forecasting
  • Sentiment Analysis and Opinion Mining

Recent published papers by Ioannis Vlahavas feature a range of subjects across artificial intelligence and machine learning:

  • "Deep Reinforcement Learning: A State-of-the-Art Walkthrough" (2020), Journal of Artificial Intelligence Research
  • "An Intelligent Modular Water Monitoring IoT System for Real-Time Quantitative and Qualitative Measurements" (2023), Sustainability
  • "A neural Entity Coreference Resolution review" (2020), Expert Systems with Applications
  • "Sector-level sentiment analysis with deep learning" (2022), Knowledge-Based Systems
  • "TP-DDI: Transformer-based pipeline for the extraction of Drug-Drug Interactions" (2021), Artificial Intelligence in Medicine

Ioannis Vlahavas frequently publishes in several established scientific venues. Prominent publication venues include:

  • Applied Sciences
  • arXiv (Cornell University)
  • Artificial Intelligence in Medicine
  • Expert Systems with Applications
  • Neural Computing and Applications

The researcher has collaborated extensively with a group of frequent co-authors, indicating active involvement in collaborative projects and multidisciplinary studies. These co-authors include:

  • Eleftherios Kouloumpris
  • Dimitrios Zaikis
  • Vasileios Kochliaridis
  • Nikolaos Stylianou
  • Aristotelis Lazaridis

Best Publications

  • Mining Multi-label Data

    Grigorios Tsoumakas;Ioannis Katakis;Ioannis P. Vlahavas

  • Machine Learning and Data Mining Methods in Diabetes Research.

    Ioannis Kavakiotis;Olga Tsave;Athanasios Salifoglou;Nicos Maglaveras

  • Random k-Labelsets: An Ensemble Method for Multilabel Classification

    Grigorios Tsoumakas;Ioannis Vlahavas

  • Random k-Labelsets for Multilabel Classification

    G. Tsoumakas;I. Katakis;I. Vlahavas

  • MULTI-LABEL CLASSIFICATION OF MUSIC INTO EMOTIONS

    Konstantinos Trohidis;Grigorios Tsoumakas;George Kalliris;Ioannis P. Vlahavas

  • MULAN: A Java Library for Multi-Label Learning

    Grigorios Tsoumakas;Eleftherios Spyromitros-Xioufis;Jozef Vilcek;Ioannis Vlahavas

  • Cultures in negotiation: teachers' acceptance/resistance attitudes considering the infusion of technology into schools

    S. Demetriadis;A. Barbas;A. Molohides;G. Palaigeorgiou

  • On the stratification of multi-label data

    Konstantinos Sechidis;Grigorios Tsoumakas;Ioannis Vlahavas

  • Multilabel Text Classification for Automated Tag Suggestion

    I. Katakis;I. Vlahavas;G. Tsoumakas

  • Multi-target regression via input space expansion: treating targets as inputs

    Eleftherios Spyromitros-Xioufis;Grigorios Tsoumakas;William Groves;Ioannis Vlahavas

  • An Empirical Study of Lazy Multilabel Classification Algorithms

    E. Spyromitros;G. Tsoumakas;Ioannis Vlahavas

  • Protein classification with multiple algorithms

    Sotiris Diplaris;Grigorios Tsoumakas;Pericles A. Mitkas;Ioannis Vlahavas

  • Tracking recurring contexts using ensemble classifiers: an application to email filtering

    Ioannis Katakis;Grigorios Tsoumakas;Ioannis Vlahavas

  • On the utility of incremental feature selection for the classification of textual data streams

    Ioannis Katakis;Grigorios Tsoumakas;Ioannis Vlahavas

  • Correlation-Based Pruning of Stacked Binary Relevance Models for Multi-Label Learning

    Grigorios Tsoumakas;Anastasios Dimou;Eleftherios Spyromitros;Vasileios Mezaris

  • An Ensemble Pruning Primer

    Grigorios Tsoumakas;Ioannis Partalas;Ioannis P. Vlahavas

  • A Comprehensive Study Over VLAD and Product Quantization in Large-Scale Image Retrieval

    Eleftherios Spyromitros-Xioufis;Symeon Papadopoulos;Ioannis Yiannis Kompatsiaris;Grigorios Tsoumakas

  • An Integrated Approach to Automated Semantic Web Service Composition through Planning

    O. Hatzi;D. Vrakas;M. Nikolaidou;N. Bassiliades

  • Selective fusion of heterogeneous classifiers

    Grigorios Tsoumakas;Lefteris Angelis;Ioannis Vlahavas

  • Multi-label classification of music by emotion

    Konstantinos Trohidis;Grigorios Tsoumakas;George Kalliris;Ioannis P. Vlahavas

  • A Defeasible Logic Reasoner for the Semantic Web

    Nick Bassiliades;Grigoris Antoniou;Ioannis P. Vlahavas

Frequent Co-Authors

Nick Bassiliades
Nick Bassiliades Aristotle University of Thessaloniki
Grigorios Tsoumakas
Grigorios Tsoumakas Aristotle University of Thessaloniki
Ioannis Stamelos
Ioannis Stamelos Aristotle University of Thessaloniki
Ahmed K. Elmagarmid
Ahmed K. Elmagarmid Qatar Computing Research Institute
Symeon Papadopoulos
Symeon Papadopoulos Information Technologies Institute, Greece
Grigoris Antoniou
Grigoris Antoniou University of Huddersfield
Richard Rosenquist
Richard Rosenquist Karolinska Institute
Demetrios G. Sampson
Demetrios G. Sampson University of Piraeus
Paolo Ghia
Paolo Ghia Vita-Salute San Raffaele University
Kostas Stamatopoulos
Kostas Stamatopoulos Centre for Research and Technology Hellas

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