Dr. Marko Horvat
Faculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, Croatia
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Academic Career Length
21Years (2006-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications24 July 2015 in Behavior Research Methods
Journal Article
MRMonika Riegel
Monika RiegelŁŻŁukasz Żurawski
Łukasz Żurawski
MWMałgorzata Wierzba
Małgorzata WierzbaAMAbnoss Moslehi
Abnoss Moslehi
ŁKŁukasz Klocek
Łukasz Klocek
AMArtur Marchewka
Artur Marchewka +4
The Nencki Affective Picture System (NAPS; Marchewka, Żurawski, Jednoróg, & Grabowska, Behavior Research Methods, 2014) is a standardized set of 1,356 realistic, high-quality photographs divided into...
1 October 2014 in International Journal of Human-Computer Studies
Journal Article
DKDavor Kukolja
Davor Kukolja
SPSiniša Popović
Siniša Popović
Marko HorvatBKBernard Kovač
Bernard Kovač
KĆKrešimir Ćosić
Krešimir Ćosić
1 February 2010 in Cyberpsychology, Behavior, and Social Networking
Journal Article
KĆKrešimir Ćosić
Krešimir Ćosić
SPSiniša Popović
Siniša Popović
DKDavor Kukolja
Davor Kukolja
Marko HorvatBDBranimir Dropuljić
Branimir Dropuljić
The significant proportion of severe psychological problems related to intensive stress in recent large peacekeeping operations underscores the importance of effective methods for strengthening the prevention and treatment of stress-related disorders. Adaptive control of virtual reality (VR) stimulation presented in this work, based on estimation of the person's emotional state from physiological signals, may enhance existing stress inoculation training (SIT). Physiology-driven adaptive VR stimulation can tailor the progress of stressful stimuli delivery to the physiological characteristics of each individual, which is indicated for improvement in stress resistance. Following an overview of physiology-driven adaptive VR stimulation, its major functional subsystems are described in more detail. A specific algorithm of stimuli delivery applicable to SIT is outlined.
1 May 2016
Conference Paper
Affective computing opens a new area of research in computer science with the aim to improve the way how humans and machines interact. Recognition of human emotions by machines is becoming a significant focus in recent research in different disciplines related to information sciences and Human-Computer Interaction (HCI). In particular, emotion recognition in human speech is important, as it is the primary communication tool of humans. This paper gives a brief overview of the current state of the research in this area with the aim to underline different techniques that are being used for detecting emotional states in vocal expressions. Furthermore, approaches for extracting speech features from speech datasets and machine learning methods with special emphasis on classifiers are analysed. In addition to the mentioned techniques, this paper also gives an outline of the areas where emotion recognition could be utilised such as healthcare, psychology, cognitive sciences and marketing.
1 May 2018
Conference Paper
Marko HorvatMDMarko Dobrinic
Marko Dobrinic
MNMatej Novosel
Matej Novosel
PJPetar Jercic
Petar Jercic
20 May 2024
Conference Paper
AŠAntonia Šarčević
Antonia Šarčević
ITIvan Tomičić
Ivan Tomičić
AMAndrija Merlin
Andrija Merlin
Marko HorvatThis paper describes the development of an Open-Source Generative AI Chatbot, utilizing free Large Language Models (LLM) to enrich the student learning experience for a university course in “Introduction to Programming”. The article aims to provide a step-by-step guide for selecting, fine-tuning, and evaluating available models. As a first step in choosing the appropriate LLM, which provides the most accurate responses while not requiring excessive computing power, the article will cover a discussion of the advantages and disadvantages of local vs. cloud-available models. After selecting a few promising models, the next stage includes fine-tuning LLMs to answer domain-specific questions using a dataset containing essential rules, guidelines, and explanatory content regarding the subject. The crucial aspect of selecting a model was evaluating answers, and in this context, both human and automatic evaluation techniques will be presented. Finally, it is possible to enhance the model performance and accuracy by incorporating Retrieval-Augmented Generation (RAG) techniques and exploring the influence of various factors, such as different vector databases, model temperatures, maximum token lengths, prompt templates, embeddings, repetition penalties, and chunking sizes. Our results show that chatbots have significant potential to improve academic support and learning efficiency, as well as personalized education in general.
About Me
Dr. Marko
Horvat is an assistant professor at the Department of Applied Computing,
Faculty of Electrical Engineering and Computing (FER), the University of Zagreb. He
holds MEng (1999), MSc (2007), and PhD (2013) degrees from FER, specializing in
artificial intelligence and mobile computing. Before
joining FER in 2008, he accumulated 10 years of industry experience as a
software engineer, architect, project manager, and department manager. At FER,
he has contributed to numerous national and EU scientific projects as
a researcher, domain expert, and project leader. Between 2014 and 2020, he served
as vice-dean for science, international cooperation, and new study programs at
the Zagreb University of Applied Sciences. He actively
serves on editorial boards of international journals and conference committees
and regularly reviews academic programs, textbooks, and scientific projects. His
research interests include applied artificial intelligence, machine learning,
automated reasoning, knowledge representation, affective computing, the semantic
web, and generative AI applications in education and advanced spellchecking.
Currently, he leads research on humanitarian demining data observatories and
next-generation educational systems. He is a senior member of IEEE, chairs the IEEE Technology and Engineering
Management Chapter (Croatia Section), serves on the IEEE Croatia Section
Executive Board, and heads the Scientific Advisory Board of the Croatian Mine
Action Center (HCR-CTRO).