Hello, I’m Marko Horvat. I’m a computer scientist with main research focus in areas of formal representation and automated reasoning, machine learning and development of information systems for health and wellbeing. Also, I’m interested in variety of topics such as the SETI.

I hold a PhD in Computer Science from University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, Croatia.

I’m an IEEE Senior Member and Co-Chair of Technology Management Chapter (TEMS) in IEEE Croatia Section.

I’m the founder and head of the Artificial Intelligence Laboratory at Zagreb University of Applied Sciences (TVZ AI Lab) and was an active participant in several research projects concerned with the management of emotion and stress using intelligent computer systems, data mining of EEG time series data, linking of semantic and affective knowledge, and development of affective multimedia databases with tools for multifaceted document retrieval.

Currently I’m a tenured Senior Lecturer in computer science at the Department of Computer Science and Information Technology, Zagreb University of Applied Sciences and an external Associate Professor at the University of Zadar, Zadar, Croatia.

This site showcases some of the research I’ve done, including my CV and software tools which can be freely downloaded for academic purposes and a blog on topics that intersect affective computing, machine learning, knowledge representation and information retrieval.

Research interests: machine learning, automated reasoning, knowledge representation, affective computing, ontologies, and the semantic web

Featured articles:

Formal knowledge representation, automated reasoning, affective computing:

  • Fuzul, E. & Horvat, M. (2019). Formal model of student competencies in higher education and required skills in the job market. In 30th Central European Conference on Information and Intelligent Systems (CECIIS 2019) (pp. 43-49).
  • Horvat, M., Dobrinić, M., Novosel, M., & Jerčić, P. (2018). Assessing emotional responses induced in virtual reality using a consumer EEG headset: A preliminary report. In 41st International Convention on Information and Communication Technology, Electronics and Microelectronics MIPRO 2018.
  • Horvat, M. (2017). A Brief Overview of Affective Multimedia Databases. In 28th Central European Conference on Information and Intelligent Systems (CECIIS 2017) (pp. 3-11).
  • Dunđer, I., Horvat, M., & Lugović, S. (2017). Exploratory study of words and emotions in tweets of UK startup founders. In Communication Management Forum 2017 (CMF2017).
  • Horvat, M., Kukolja, D., & Ivanec, D. (2015). Retrieval of multimedia stimuli with semantic and emotional cues: Suggestions from a controlled study. arXiv preprint arXiv:1505.07396.
  • Horvat, M., Kukolja, D., & Ivanec, D. (2015). Comparing affective responses to standardized pictures and videos: A study report. arXiv preprint arXiv:1505.07398.
  • Horvat, M., Bogunović, N., & Ćosić, K. (2014). STIMONT: a core ontology for multimedia stimuli description. Multimedia tools and applications, 73(3), 1103-1127.
  • Kukolja, D., Popović, S., Horvat, M., Kovač, B., & Ćosić, K. (2014). Comparative analysis of emotion estimation methods based on physiological measurements for real-time applications. International journal of human-computer studies, 72(10-11), 717-727.
  • Ćosić, K., Popović, S., Kukolja, D., Horvat, M., & Dropuljić, B. (2010). Physiology-driven adaptive virtual reality stimulation for prevention and treatment of stress related disorders. CyberPsychology, Behavior, and Social Networking, 13(1), 73-78.


  • Horvat, M. (2015). KIC 8462852: Remnants of a Failed Early Type II Civilization?. Journal of cosmology.
  • Horvat, M., Nakić, A., & Otočan, I. (2012). Impact of technological synchronicity on prospects for CETI. International Journal of Astrobiology, 11(1), 51-59.
  • Horvat, M. (2006). Calculating the probability of detecting radio signals from alien civilizations. International Journal of Astrobiology, 5(2), 143-149.

Selection of the latest student projects successfully accomplished at the TVZ AI Laboratory:

Affective computing and psychophysiology:

  • Development of a heart rate monitor with a webcam based on photoplethysmographic effect
  • Javascript application for visualization of affective and semantic-tagged images
  • Client-server system for tagging images with emotional annotations
  • Using Microsoft Cognitive Services for emotion recognition with facial expressions
  • Comparison of OpenCV and Microsoft Cognitive Services in face recognition
  • Application of EMOTIV Epoc+ wireless EEG system in a real-time neurofeedback training
  • Development of VR applications in Unreal environment for stimulation of emotions
  • Demonstration of an emotion elicitation experiment in fully immersive VR with EEG monitoring

Ubiquitous/Mobile computing:

  • Evaluating the usefulness of commercial Android Wear smartwatches in continuous heart rate monitoring
  • Development of Android mobile and web applications for paced breathing exercises
  • Development of Android mobile and web applications for emotion recognition using facial expressions with Visage SDK
  • Development of cognitive-bias modification mobile and web applications

Please feel free to contact me regarding research cooperation, project opportunities and other common professional topics.