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Octavian Mihai MachidonView profile

Assistant Professor

• Mobile Computing
• IoT-based Systems
• Smart Public Governance
• +8 more

Octavian Mihai Machidon is an Assistant Professor at the Faculty of Computer and Information Science (FRI), specializing in mobile computing, IoT systems, and approximate computing. His research bridges technological innovation with diverse applications in agriculture, cultural heritage, and smart governance. Current research focuses on energy-efficient mobile systems, UAV-based agricultural monitoring, and smart governance frameworks Previously led H2020 Smart4All AgriAdapt project Recipient of multiple awards for research excellence and innovation His work demonstrates cross-disciplinary impact through projects like Mobiprox (IEEE IoT Journal) and SqueezeSlimU-Net (IEEE Journal of Selected Topics in Applied Earth Observations). Key trends include adaptive algorithms, real-time processing, and sustainable technology integration. 2024 - FRI Special Award for Exceptional Research Achievement 2023 - Agrobiznis 'Best Idea' award for AgriAdapt project As member of the Computer Communications Laboratory , he contributes to digital transformation initiatives and teaches courses in process automation and mobile sensing platform development.

Žiga EmeršičView profile

Assistant Professor

• Biometrics
• Deep Neural Networks
• Computer Vision
• +5 more

Žiga Emeršič is an Assistant Professor at the University of Ljubljana, Faculty of Computer and Information Science , affiliated with the Computer Vision Laboratory . His work bridges biometrics , deep learning , and computer vision , with a focus on ear-based recognition systems and explainable AI. IEEE Member #98052610 Email: ziga.emersic@fri.uni-lj.si Office: R2.33, LRV Laboratory Office Hours: Tuesdays 12:30 or by arrangement Research interests include biometric recognition , deep neural networks , object detection , and privacy-preserving AI . He pioneered ear biometrics research, developing tools like the Ear Biometric Database in the Wild and ContexedNet for context-aware recognition. Recent publications analyze biometric model performance ( Neural Computing & Applications, 2018 ), explore k-Same-Net for face deidentification ( Entropy, 2018 ), and advance ear alignment using two-stack hourglass networks ( IET Biometrics, 2023 ). His 2021 work on context-aware ear detection addresses real-world variability. Awards include the European Association for Biometrics Award (2021) , SDRV Excellence Plaque (2023) , and multiple University of Ljubljana recognitions for teaching and research (2016, 2018, 2022). He co-organized the 1st Machine Learning Summer School in Central America (2018) . As co-founder of OOSM Ltd (2014-2015), he applied deep learning to smart city solutions. His 2017 doctoral thesis on visual ear detection in unconstrained environments solidified his expertise in biometric AI .

Sašo ŽivanovićView profile

Assistant Professor

• Semantics
• Quantification
• Phonology
• +4 more

Sašo Živanović is an Assistant Professor at the Department of Comparative and General Linguistics, Faculty of Arts, University of Ljubljana. He holds a PhD in General Linguistics (2007) and a Diploma in Theoretical Mathematics (2002), and has been continuously employed at the university since 2007. His educational background reflects an interdisciplinary approach, combining mathematical rigor with linguistic theory. This foundation supports his research at the intersection of formal linguistics and computational methods. Živanović's research spans theoretical linguistics with particular emphasis on semantics (especially quantification), phonology, and syntax. His work demonstrates a consistent focus on the formal properties of language structure, with publications ranging from theoretical explorations of logical form to practical applications in linguistic documentation. His recent work shows increasing integration of computational approaches, particularly through his development of specialized LaTeX packages for linguistic research. Analysis of his publication record reveals a dual trajectory: theoretical contributions to linguistic theory (particularly in Slavic languages) and practical tools for linguistic documentation and analysis. His most recent publications demonstrate growing interest in computational linguistics and the development of specialized software tools for linguistic research. Živanović maintains an active presence in both academic and open-source communities, with significant contributions to the LaTeX ecosystem through packages like Memoize, Forest, and SignDraw that address specific needs in linguistic research and publication. As an educator, he teaches courses including Phonetics and Phonology, Linguistic Typology, Modern Linguistic Theories, and LaTeX for Linguists, demonstrating his commitment to equipping students with both theoretical knowledge and practical technical skills essential for contemporary linguistic research.

Igor KononenkoView profile

Professor

• Artificial Intelligence
• Machine Learning
• Neural Networks
• +3 more

Prof. Igor Kononenko serves as a Professor at the Faculty of Computer and Information Science, University of Ljubljana, where he heads the Laboratory for Cognitive Modeling and teaches core courses including Algorithms and Data Structures 1, Artificial Intelligence, Intelligent Systems, and Machine Learning. Education: Ph.D. in Computer Science, University of Ljubljana (1990) Research Focus: His work centers on Artificial Intelligence , Machine Learning , and Cognitive Modeling , with recent emphasis on explainable AI and prediction reliability . He has pioneered techniques in feature contribution explanation, graph-based data mining, and archetypal analysis for complex datasets, resulting in approximately 210 publications and 10 textbooks . Publication Trends: Analysis of his 15 most recent articles reveals a decisive shift toward interpretable machine learning—particularly reliability estimation in data streams (2012-2014), graph mining for oceanographic/spatial data (2013-2019), and medical applications of explanation methods (2011-2018). His 2013-2016 work on archetypal analysis for multi-document summarization remains highly influential in NLP. Research Leadership: As principal investigator, he secured major funding including: Two ARRS programmes on Artificial Intelligence (2009-2014, 2015-2020) EU's AGROIT project for farming efficiency (2014-2016) Bilateral projects on imbalanced data learning (2010-2011), bioinformatics for cancer classification (2014-2015), and disease dataset analysis (2020-2021) Laboratory: The Laboratory for Cognitive Modeling under his direction drives innovation in AI theory and applications, with recent work spanning basketball analytics, coronary artery disease diagnostics, and hemodynamic simulation modeling.

Narvika BovconView profile

Professor

• new media art
• visual communications
• digital animation
• +2 more

Narvika Bovcon is a Full Professor at the Faculty of Computer and Information Science, specializing in video and new media art. Since 2016, she has served as editor-in-chief of the journal Art Words and has authored numerous new media art projects and exhibitions. Her academic activities include teaching courses such as Introduction to Graphics Design, Graphic Design, and Multimedia Content. Research Focus: Bovcon's work explores interdisciplinary intersections of technology and art, with emphasis on: Digital animation and mixed reality applications User interface design for cultural heritage Augmented reality in fine arts and literature Digital preservation methodologies Computational approaches to visual communications Publication Trends: Her recent scholarly output (2013-2021) demonstrates strong focus on digital heritage preservation, augmented reality implementations in cultural contexts, computational analysis of art, and educational applications of interactive media. Works frequently employ case studies and technical evaluations within Slovenian cultural frameworks. Research Projects: P2-0214 Computer Vision (ARRS, 2019-2024) - Core research programme J7-3158 Sustainable digital preservation of Slovenian new-media art (ARRS, 2021-2024) ŠIPK 2 Cultural Heritage documentation using new technologies (Structural Funds, 2018) PKP 1 Interactive computer installation integration (Structural Funds, 2014) Laboratory Affiliation: Active member of the Computer Vision Laboratory at the Faculty of Computer and Information Science, contributing to technical-artistic research initiatives.

Ziga EmersicView profile

Assistant Professor

• Biometrics
• Deep Neural Networks
• Computer Vision
• +4 more

Dr. Žiga Emeršič is an Assistant Professor at the University of Ljubljana , Faculty of Computer and Information Science, and a member of the Computer Vision Laboratory (LRV). His research focuses on biometrics , deep neural networks , and computer vision with a specialization in ear-based recognition systems. IEEE Member (#98052610) Recipient of the European Biometrics Association Award (2021) and SDRV Excellence Plaque (2023) Co-organizer of international challenges in ear recognition and machine learning workshops His work addresses unconstrained ear detection , model compression for edge devices , and privacy-preserving biometric systems . He has contributed to AI education through EU projects like AIM@VET and developed curricula for computer vision and biometrics. Highlights: Published in top journals ( Neural Computing & Applications , IET Biometrics , Entropy ) Authored chapters in Springer publications on deep ear recognition and ocular biometrics Active in international conferences (IEEE, IAPR) with over 60 publications He has received special recognition for both research (2018) and teaching excellence (2016, 2019), and his work has been featured in media outlets across Slovenia.

Iztok Lebar BajecView profile

Associate Professor

• Computer Graphics
• Artificial Life Modeling
• Fuzzy Logic
• +6 more

Iztok Lebar Bajec is an Associate Professor at the Faculty of Computer and Information Science, University of Ljubljana, where he has been actively engaged in research and teaching since completing his PhD in 2005. His academic journey began with a Computer Science Programme at the Technical School Centre in Nova Gorica (1994), followed by undergraduate, master's, and doctoral studies at the University of Ljubljana. His research spans multiple interdisciplinary fields including computer graphics, fuzzy logic applications, quantum-dot cellular automata, and artificial life modeling. Professor Lebar Bajec's work uniquely bridges computer science with biological modeling, particularly in simulating collective animal behavior. His PhD dissertation focused on fuzzy logic modeling of bird flocking behavior, which has evolved into a significant research trajectory examining organized group dynamics in both biological and artificial systems. His recent publications reveal a dual research focus: on one hand, the application of fuzzy logic to model collective behavior in biological systems (particularly bird flocking and predator-prey interactions), and on the other hand, pioneering work in quantum-dot cellular automata for ternary computing systems. This unusual combination of research areas demonstrates his innovative approach to computational modeling across vastly different scales - from biological collectives to nanoscale computing elements. 3rd place at the 10th student paper competition, ERK'2000, Portorose, Slovenia (2000) Best high school graduate of the Technical School Centre in Nova Gorica, Slovenia (1994) Runner-up at the 17th Young Innovator Competition, Nova Gorica, Slovenia (1993) Professor Lebar Bajec has advised multiple graduate students including Jure Demšar (PhD), Miha Moškon (BSc), Primož Pečar (MSc), and Tomaž Orač (BSc). His current research is supported by several active projects including P2-0359 - Ubiquitous computing (2023-2027), J7-4642 - Fundamental research for development of speech resources and technologies for Slovenian (2022-2025), and PoVeJMo - Adaptive Natural Language Processing with Large Language Models (2023-2026). He is a member of the Computer Structures and Systems Laboratory where he has been active since 2000.

Nada LavračView profile

Professor

• machine learning
• data mining
• inductive logic programming
• +5 more

Professor Nada Lavrač is a leading researcher at the Jožef Stefan Institute and Full Professor at the University of Nova Gorica , Slovenia. With over 40 years of experience in machine learning and data mining, she has made groundbreaking contributions to inductive logic programming, computational creativity, and biomedical data analysis. Her work spans applications in medicine, public health, bioinformatics, and industrial systems, with a focus on explainable AI and knowledge discovery. Head of ICT Programme at Jozef Stefan International Postgraduate School Principal researcher in EU projects H2020 FNS-Cloud and EMBEDDIA Author of 163-page monograph Representation Learning: Propositionalization and Embeddings (Springer, 2021) Research highlights include developing neuro-symbolic AI frameworks for conference scheduling, creating ontology-driven graph-based learning systems, and pioneering feature selection methods for high-dimensional biomedical datasets. Her work on tax2vec for taxonomy-based text classification has transformed short text analysis approaches. She has also led advancements in grapevine disease modeling using multi-omics data integration. Scientific accolades: 1984 national research excellence prize , 1997 Ambassador of Science of Slovenia , ECCAI Fellow (2007) , and Zois Recognition Award (2013) . Her citation metrics include 16,141 Google Scholar citations (h=54) and 4,622 WoS citations (h=31).

Petra Kralj NovakView profile

Assistant Professor

• Social Media Mining
• Sentiment Analysis
• Network Analysis
• +3 more

Dr. Petra Kralj Novak is an Assistant Professor at the Department of Network and Data Science, Central European University (Vienna, Austria) and a part-time researcher at the Department of Knowledge Technologies, Jožef Stefan Institute (Ljubljana, Slovenia). She holds a PhD from Jožef Stefan International Postgraduate School, where her thesis on Supervised Descriptive Rule Induction was published in the Journal of Machine Learning Research. Her research focuses on social media mining , combining machine learning with network analysis to study sentiment, hate speech, and emoji semantics. She pioneered emoji sentiment analysis in her influential 2015 paper. Additional interests include knowledge discovery, subgroup mining, and applications in bioinformatics (e.g., GMO detection tools). Her publications predominantly explore machine learning applications in social networks (retweet dynamics, misinformation spread) and biomedical domains (gene expression, GMO testing). Recent work emphasizes social media analytics and network science, while earlier contributions centered on algorithmic methods for subgroup discovery and biomedical data mining. Leadership & Projects: Coordinator of EU REC AG project IMSyPP (2020-2022) on hate speech monitoring Member of DGCNECT expert group for 'Digital media and human well-being' Program co-chair for ECML PKDD 2022 and Discovery Science 2018 Teaching: Leads courses in Fundamentals of Data Analysis and Introduction to Machine Learning at Central European University.

Areeb AhmedView profile

Researcher

• Machine Learning
• Natural Language Processing
• Computational Linguistics
• +3 more

Assist. dr. Areeb Ahmed is a researcher affiliated with the Laboratory for Machine Learning and Language Technologies. He is actively involved in the SMASH project, a European initiative focused on machine learning applications in sciences and humanities, spanning from July 2023 to June 2028. His research interests include: Machine Learning Natural Language Processing Computational Linguistics Artificial Intelligence Data Science Applications in Sciences and Humanities He contributes to teaching in Computer Communications and collaborates within interdisciplinary teams working on machine learning-driven solutions for both scientific and humanities domains.

Jaka ČibejView profile

Researcher

• Natural Language Processing
• Machine Learning
• Slovene Language Technology
• +3 more

Jaka Čibej is a researcher at the Laboratory for Machine Learning and Language Technologies . His work focuses on advanced natural language processing applications and computational linguistics, particularly involving Slavic languages. Projects PoVeJMo (2023-2026): Adaptive Natural Language Processing with Large Language Models Thesaurus of Modern Slovene (2018-2019) BI-HR/23-24-049 (2023-2025): Automatic identification of semantic relations in figurative contexts in Croatian and Slovenian His research explores language modeling, semantic analysis, and cross-lingual NLP techniques, with a particular emphasis on Slovene language technology development.

Jure DemšarView profile

Assistant Professor

• Neuroinformatics
• Collective behaviour
• Natural phenomena modeling
• +5 more

Jure Demšar, PhD , is an Assistant Professor at the Faculty of Computer and Information Science , University of Ljubljana . He conducts interdisciplinary research bridging neuroinformatics, collective behaviour, and game development, while actively collaborating with leading institutions worldwide. Education & Academic Journey: PhD studies supported by the prestigious “Inovativna shema” scholarship for promising doctoral researchers. Research visits: three months at Newcastle University (Game Lab & Institute of Neuroscience), three months at University of Groningen (Prof. Charlotte K. Hemelrijk’s lab), one month at University of Houston (Computer Graphics and Interactive Media Lab). Research Interests: Dr. Demšar’s work converges on four core themes: Neuroinformatics & Neuroimaging: development of scalable platforms for multimodal neuroimaging data processing (Qu|Nex, autohrf, bayes4psy R packages). Collective Behaviour & Modeling: adaptive agent-based simulations of predator–prey interactions and flocking, evolution of composite tactics. Computational Psychiatry: mapping brain–behavior relationships along the psychosis and mood spectra, placebo vs. drug neural signatures. Game Development & Personalization: generating personalized game content, GPU-accelerated Bayesian modeling, and recommender systems. Scientific Awards & Recognition: Faculty Award for Outstanding Pedagogic Work, 2017/2018 Faculty Award for Outstanding Research Achievements, 2017 Inovativna shema scholarship for promising PhD students Collaborations & Funding: Dr. Demšar has established long-standing collaborations with: Washington University in St. Louis (Connectome Coordination Facility) – Human Connectome Project Yale University (Anticevic Lab) – Qu|Nex platform Harvard University (Applied Neuroimaging Statistics Laboratory) Internal University of Ljubljana partners: Faculty of Arts, Faculty of Medicine, Faculty of Sport Laboratory & Team: He leads the Bayesian Statistics Project Laboratory , where he mentors students and drives open-source tool development for Bayesian data analysis and neuroimaging workflows.

• Machine Learning
• Language Technologies
• Artificial Intelligence
• +3 more

Kaja Dobrovoljc is a Researcher affiliated with the Laboratory for Machine Learning and Language Technologies . Her work primarily revolves around Machine Learning and Language Technologies .

• Machine Learning
• Natural Language Processing
• Computational Linguistics
• +1 more

Antoine Doucet serves as a Researcher at the Laboratory for Machine Learning and Language Technologies. His work focuses on interdisciplinary computational approaches bridging artificial intelligence and linguistic systems. His primary research domains include: Machine Learning methodologies for language modeling Natural language processing frameworks Computational linguistics applications AI-driven language technology development Current investigations explore neural architectures for multilingual systems and ethical implications of language AI. No scientific awards or student advisement records are publicly documented in available sources. Research activities appear centered within institutional laboratory frameworks without noted external grants or collaborative teams.

Stefana JaničijevićView profile

Assistant Professor

• Machine Learning
• Natural Language Processing
• Artificial Intelligence
• +3 more

Stefana Janičijević is an Assistant Professor and a member of the Laboratory for Machine Learning and Language Technologies. Her research focuses on interdisciplinary applications at the intersection of artificial intelligence and computational linguistics. Affiliation: Laboratory for Machine Learning and Language Technologies Research Interests span machine learning algorithms, natural language processing (NLP), and language technology development. Her work likely contributes to areas like AI-driven language modeling and computational methods for linguistic analysis.