Artificial intelligence research group
The Research Group for Artificial Intelligence is dedicated to the study of intelligent behavior in biological and artificial systems during problem-solving and learning. We focus on the foundations of human learning and thinking, using computer simulations and behavioral experiments. Our goal is to uncover the logic behind cognitive processes, such as the construction of perceptual representations, concept learning, reasoning about similarity, and decision-making in problem-solving. We combine scientific methods, including testing adults, children, and machines, with the ultimate aim of better understanding human learning and applying these insights to the design of artificial intelligence systems based on human learning models.
The Research Group for the Development of Artificial Intelligence has the potential for collaboration in various fields thanks to the wide range of applications of our research. Here are a few areas where our expertise could be beneficial:
Artificial Intelligence Development: Our in-depth analysis of human learning can contribute to the development of AI systems that are better adapted to human thinking and problem-solving.
Education: Understanding cognitive learning processes can contribute to the development of innovative teaching methods and the creation of tailored educational technologies.
Software Development for Training: Our research can serve as a foundation for the development of training software that utilizes advanced learning and problem-solving techniques.
Game and Simulation Development: The analysis of perceptual representations and decision-making can be crucial for enhancing gaming experiences and developing simulations with increased intelligence.
Biomedicine: Understanding biological systems can contribute to advancements in medical research, especially in the study of human learning and memory.
Industrial Engineering: The application of our research can improve process automation, optimize management systems, and encourage innovation in the industrial sector.
Robotics: Understanding the logic behind reasoning and decision-making is crucial for the development of intelligent robots capable of learning and adaptation.
Psychology and Neuroscience: Collaboration with researchers in these disciplines would allow for better connections between computer models and real neurocognitive processes.
These applications demonstrate the broad potential of our research and open up possibilities for collaboration with various sectors, from the technological industry to education and medical sciences.”
Research team:
Team leader: Saša Mladenović
Collaborators : Goran Zaharija, Divna Krpan, Ivana Marin, Antonela Prnjak, Dino Nejašmić, Pero Bogunović, Boško Lišnić, Marko Jevtić, Helena Librenjak, Domina Sokol, Andrina Granić, Monika Mladenović
About team members:
Saša Mladenović
Ph.D. Saša Mladenović is a full professor at the Faculty of Science, University of Split (Croatia), where he teaches a number of doctoral, graduate, and undergraduate courses at the Department of Informatics. He received his Ph.D. in computer science from the Faculty of Electrical Engineering, Mechanical Engineering, and Naval Architecture in Split (FESB).
From 1999 to 2006, he served as the Technical Manager of the Toll Collection System Department at Ecsat, Croatia – the company responsible for software development at the Transportation department of CS group, a designer, integrator, and operator of mission-critical systems in France.
Saša is an active member of the international Science Communication workgroup, appointed as an expert by the University of Split. He organizes a variety of activities aimed at demystifying artificial intelligence for teachers, students, and the general public. He is also actively involved in the EDIT CodeSchool program, where he contributed to the development of AI curricula for K12 students as an extracurricular activity.
His research interests include problems in teaching programming, interoperability, and intelligent technologies like ontology and multi-agent systems, with a focus on engineering applications. Saša has been an IEEE member since 1996.
List of publications can be found on this page.
Andrina Granić
Andrina Granić holds a tenured position as a Professor in Computer Science at the Faculty of Science, University of Split, Croatia. She received her PhD from the University of Zagreb, Croatia. Her research interests include human-computer interaction, interaction design, technology-enhanced learning, and acceptance of technology. Her research has been published in Technology in Society, Universal Access in the Information Society, Computers & Education, Education and Information Technologies, British Journal of Educational Technology, and other journals. She holds positions on several editorial boards, actively engages in various national and international projects, serves as the Croatian representative in IFIP TC13 on Human-Computer Interaction, and is a member of the IEEE Computer Society.
Goran Zaharija
Ph.D. Goran Zaharija is assistant professor and the head of the Department of Informatics at the Faculty of Science, University of Split. He received his Ph.D. in computer science at the Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture in Split (FESB). He teaches several undergraduate and graduate courses in programming, computer architecture and artificial intelligence. His scientific interests include machine learning, artificial neural networks and multi-agent systems.
Divna Krpan
Ph.D. Divna Krpan is an assistant professor at the Department of Informatics at the Faculty of Science, University of Split. She holds a degree in Mathematics and Informatics and is dedicated to improving teaching and learning of computer programming, particularly for novice programmers at the introductory undergraduate level.
Her doctoral thesis, titled “Teaching Object-Oriented Programming using Didactic Reduction,” focuses on innovative teaching methodologies in computer programming. Divna teaches undergraduate courses in introductory programming, object-oriented programming, data structures and algorithms, visual programming, as well as Introduction to Data Science at the graduate level.
In addition to her academic work, Divna utilizes didactic reduction to explain complex algorithms and concepts used in artificial intelligence, teaching students from K5 upwards about AI. She is actively involved in the EDIT CodeSchool program, contributing to the development of AI curricula for K12 students as an extracurricular activity. She is also a member of ACM.
Divna is committed to promoting cautious and responsible use of technology. She participates in Science Fairs and Researchers’ Night events regularly, advocating for informed and ethical practices in technology adoption and usage.
Dino Nejašmić
Dino Nejašmić is a Lecturer at the Faculty of Science, University of Split, specializing in computer science. He conducts courses in Scientific Programming, Distributed Systems, and introductory software engineering and computer architecture. Previously, he held the position of University Assistant at the same institution, teaching subjects such as 3D object modelling and various programming topics. Before that, he worked as a Software Development Engineer at Ericsson Nikola Tesla, where he led a team in developing software for 4G and 5G telecommunication networks. In this role, he managed research studies, projects, and customer relations, demonstrating skills in programming, synchronization technologies, test automation, CI/CD, embedded systems, and network configuration. With extensive experience in software development, project management, and team leadership, a versatile professional in both academic and industrial domains.
Ivana Marin
Ivana Marin received her Bachelor’s degree in Mathematics from the Faculty of Science, University of Split, Croatia, in 2017, and a Master’s degree in Mathematics with specialisation in computing in 2019 from the same faculty. She is currently a PhD student at the Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, and has been working as an assistant at the Faculty of Science, University of Split, since 2019. Her research interests include deep learning, machine learning, and data science.
Antonela Prnjak
Antonela Prnjak is a Teaching Assistant at the Department of Informatics at the Faculty of Science, University of Split. She graduated in Informatics at the Faculty of Science. She currently teaches several undergraduate and graduate courses in computer programming. She is currently working on research related to artificial intelligence, more specifically to biologically inspired neuron models. Interests include databases, artificial neural networks, and machine learning.
Boško Lišnić
Boško Lišnić is a PhD student at the Department of Informatics, Faculty of Science, University of Split. He has a master’s degree in computer science education. He works in an elementary school as a computer science teacher. He also teaches undergraduate courses in introductory programming and computer science. His main interests include research on artificial intelligence literacy in K-12 education and the teaching of computer programming at the elementary school and undergraduate levels.