Monday Computer Science Seminar Archives - UP Famnit

Dušan Todorović

vanja.kovse — Mon, 27 Jul 2026 07:37:07 +0000

On Monday, July 27, 2026, at 4:00 PM, a lecture will be held as part of the Monday RIN seminar, organized by the UP FAMNIT and UP IAM. TIME / VENUE: July 27, 2026, at 4:00 PM, via Zoom. SPEAKER: Dušan TODOROVIĆ Dušan Todorović graduated from the Academy of Technical and Educational Applied Studies (ATVSS) in Niš, specializing in Modern Computer Technologies. He is currently a master’s student in the Computer Science program at UP FAMNIT. His seminar paper was prepared as part of the Research Seminar course under the supervision of Dr. Branko Kavšek. ———————————————————————————————————NASLOV: Tehnike za razložljivost v strojnem učenju: LIME, SHAP in Grad-CAM——————————————————————————————————— POVZETEK: V seminarski nalogi obravnavam problem interpretabilnosti kompleksnih modelov strojnega učenja ter analiziram tri pomembne metode za razložljivost — LIME, SHAP in Grad-CAM. V teoretičnem delu predstavim osnovne pojme interpretabilnosti (lokalna in globalna interpretacija, model-agnostične in model-specifične metode) ter matematično ozadje posamezne metode. V praktičnem delu izvedem dva eksperimenta: prvega na podatkovnem naboru Titanic z modelom Random Forest (LIME in SHAP za tabelarične podatke), drugega pa na podatkovnem naboru Fashion-MNIST s konvolucijsko nevronsko mrežo (SHAP in Grad-CAM za slike). Rezultati pokažejo, da LIME ponuja intuitivne lokalne razlage, SHAP omogoča stabilnejšo in teoretično bolje utemeljeno interpretacijo (tako lokalno kot globalno), Grad-CAM pa vizualni vpogled v regije slike, ki najbolj vplivajo na odločitev CNN modela. Ugotovim, da ne obstaja ena univerzalna metoda za razlago vseh modelov, saj je izbira odvisna od tipa podatkov in modela. Seminar bo potekal v slovenskem jeziku. Seminar bo potekal online prek aplikacije Zoom s pričetkom ob 16:00 uri na sledeči povezavi: https://upr-si.zoom.us/j/297328207?pwd=S3Zpdk1VR3pjckNtWkQwKzlvcDR5UT09 Meeting ID: 297 328 207Passcode: 123456789 Vabljeni!

The post Dušan Todorović appeared first on UP Famnit.

Lina MEŠIČ in Luka MATIČ

mario.krajoski — Sun, 28 Jun 2026 22:00:00 +0000

V ponedeljek, 29. junija 2026, bodo ob 16:00 uri izvedeni dve predavanji v okviru PONEDELJKOVEGA SEMINARJA RAČUNALNIŠTVA IN INFORMATIKE Oddelkov za Informacijske znanosti in tehnologije UP FAMNIT in UP IAM. ČAS/PROSTOR: 29. junij 2026 ob 16.00 prek Zoom-a. 1. predavanje: ============ —————————————– PREDAVATELJICA: Lina MEŠIČ —————————————– Lina Mešič je magistrska študentka Računalništva in informatike na UP FAMNIT in trener športnega plezanja. ———————————————————————————————– NASLOV: Interaktivni sistemi kot orodje za trening športnega plezanja ———————————————————————————————– POVZETEK: Športno plezanje je v zadnjem desetletju doživelo izjemen razvoj, s tem pa so v ospredje stopile določene pomanjkljivosti v treniranju in povečale zahteve po kakovostnem treningu. V seminarju bo predstavljen pregled devetih interaktivnih sistemov s področja HCI, ki se uporabljajo za trening športnega plezanja. Od plezalnih sten s projiciranimi igrami, kjer plezalci lovijo navidezne cilje in pozabijo na strah pred višino, prek virtualne resničnosti za varno soočanje s padci, do nosljivih naprav, ki prek vibracij ali zvoka vodijo plezalca med samim vzponom. Na podlagi izbranih študij poskušamo odgovoriti na vprašanja, kje so meje teh sistemov, komu najbolj koristijo in kako jih v prihodnosti oblikovati, da bodo trenerju v pomoč in ne v napoto. Ugotovitve kažejo, da tehnologija seveda ne more nadomestiti trenerja, lahko pa prevzame ponavljajoče se naloge in administracijo ter mu tako olajša delo. Seminar bo potekal v slovenskem jeziku. =============================================================================== 2. predavanje: ============ ————————————- PREDAVATELJ: Luka MATIČ ————————————- Luka Matič je študent magistrskega študija Računalništva in informatike na UP FAMNIT, ki se osredotoča na biomedicinsko obdelavo signalov in razvoj programske opreme. Njegova raziskovalna področja vključujejo analizo EEG signalov, strojno učenje in obdelavo podatkov v realnem času. Trenutno se ukvarja s primerjavo spektralnih in kepstralnih značilk pri klasifikaciji EEG signalov. ——————————————————————————————– NASLOV: Uporaba kepstralne analize za klasifikacijo EEG posnetkov ——————————————————————————————– POVZETEK: Seminar obravnava primerjavo spektralnih in kepstralnih metod za analizo in klasifikacijo EEG signalov. Predstavljena je ekstrakcija značilk iz EEG podatkov v frekvenčni in kepstralni domeni ter njihova uporaba v okviru metod strojnega učenja. Osrednji poudarek je na primerjalni analizi učinkovitosti obeh pristopov, ki temelji na doseženi točnosti in pravilnosti klasifikacije EEG signalov. Rezultati prispevajo k boljšemu razumevanju vpliva izbire metode na uspešnost klasifikacije EEG signalov. Seminar bo potekal v slovenskem jeziku. =============================================================================== Seminarja bosta potekala online prek aplikacije Zoom s pričetkom ob 16:00 uri na sledeči povezavi: https://upr-si.zoom.us/j/297328207?pwd=S3Zpdk1VR3pjckNtWkQwKzlvcDR5UT09 Meeting ID: 297 328 207 Passcode: 123456789 Vabljeni!

The post Lina MEŠIČ in Luka MATIČ appeared first on UP Famnit.

Jovan VUKOVIĆ in Uroš SERGAŠ

mario.krajoski — Sun, 21 Jun 2026 22:00:00 +0000

V ponedeljek, 22. junija 2026, bodo ob 16:00 uri izvedeni dve predavanji v okviru PONEDELJKOVEGA SEMINARJA RAČUNALNIŠTVA IN INFORMATIKE Oddelkov za Informacijske znanosti in tehnologije UP FAMNIT in UP IAM. ČAS/PROSTOR: 22. junij 2026 ob 16.00 prek Zoom-a. 1. predavanje: ============ —————————————– PREDAVATELJ: Jovan VUKOVIĆ —————————————– Jovan Vuković is a Master's student in Data Science at the University of Primorska (UP FAMNIT). He previously completed a Bachelor's degree in Computing and Information Technology at the University of Montenegro. His professional background is primarily focused on software engineering, microservice architectures, distributed systems, and large-scale backend development. His current research interests include knowledge graphs, machine learning, data integration, and scalable graph processing. ————————————————————————————————————————————– NASLOV: Embedding-Based Entity Alignment between Large-Scale Knowledge Graphs: A Case Study of YAGO and OpenAlex ————————————————————————————————————————————– POVZETEK: Knowledge graphs have become an important approach for representing and integrating structured information in domains such as web search, digital libraries, recommendation systems, and scientific knowledge management. By representing entities and their relationships as graphs, they enable the discovery of connections that are difficult to capture using traditional relational data models. As the number and size of available knowledge graphs continue to grow, combining information from multiple sources has become an increasingly important challenge. One of the key problems in this context is entity alignment, the task of identifying entities in different knowledge graphs that refer to the same real-world object. Solving this problem is essential for building integrated knowledge bases, but it becomes particularly challenging when working with large-scale graphs containing hundreds of millions of entities and relationships. This presentation introduces the entity alignment problem through a case study involving the YAGO and OpenAlex knowledge graphs. It focuses on the first stages of a scalable alignment pipeline, including large-scale RDF preprocessing, extraction of structural and textual information, graph transformation and integer encoding, and the generation of knowledge graph embeddings using PyTorch-BigGraph. Several embedding models, including TransE, DistMult, and ComplEx, are evaluated through link prediction experiments on large-scale datasets. The obtained results are used to assess how well the learned embeddings capture the underlying graph structure and to identify the most suitable embedding model for the subsequent entity alignment task. Seminar bo potekal v angleškem jeziku. =============================================================================== 2. predavanje: ============ ————————————– PREDAVATELJ: Uroš SERGAŠ ————————————– Uroš Sergaš is a teaching assistant of Computer Science at UP FAMNIT and a member of the Centre for Responsible AI UP. As a researcher specializing in recommender systems and computational social science, his work focuses on applying machine learning methods to address societal challenges. Recently, his work also addresses the issue of AI alignment. He is currently pursuing his PhD in recommender systems. ————————————————————————————————————————————– NASLOV: Can News Ranking Reduce Political Polarization? Evidence from an Online Experiment with LLM-Generated News ————————————————————————————————————————————– POVZETEK: Algorithmic news ranking and large language models (LLMs) increasingly mediate how citizens receive political information. While personalization is often criticized for reinforcing echo chambers, ranking has also been proposed as a lever for depolarization by shaping exposure to cross-cutting viewpoints. We tested this claim in an online experiment (N=100, Prolific) using five LLM-generated news articles on gun legislation spanning pro–gun freedom to pro–gun control. All participants read the same articles; the only manipulation was article order, instantiated as a random baseline and six stance-aware depolarization-oriented strategies (counter-narrative sandwich, balanced alternation, and directional gradients). Pre–post questionnaires measured ideological selfplacement (feeling thermometer) and affective evaluations of gun-control and gun-freedom advocates. Across six research questions, we tested to see whether such recommender strategies had any reduction in ideological or affective polarization. Seminar bo potekal v angleškem jeziku. =============================================================================== Seminarja bosta potekala online prek aplikacije Zoom s pričetkom ob 16:00 uri na sledeči povezavi: https://upr-si.zoom.us/j/297328207?pwd=S3Zpdk1VR3pjckNtWkQwKzlvcDR5UT09 Meeting ID: 297 328 207 Passcode: 123456789 Vabljeni!

The post Jovan VUKOVIĆ in Uroš SERGAŠ appeared first on UP Famnit.

Ekaterina BOCHVAROSKA: RAVEN: A Retention-Aware Verifiable Extension-Block Network for Off-Chain Message Storage and Retrieval in Andrej Milisavljević: SAVI ionization and conformer generation

mario.krajoski — Sun, 14 Jun 2026 22:00:00 +0000

V ponedeljek, 15. junija 2026, bodo ob 16:00 uri izvedeni dve predavanji v okviru PONEDELJKOVEGA SEMINARJA RAČUNALNIŠTVA IN INFORMATIKE Oddelkov za Informacijske znanosti in tehnologije UP FAMNIT in UP IAM. ČAS/PROSTOR: 15. junij 2026 ob 16.00 prek Zoom-a. 1. predavanje: ============ ———————————————————- PREDAVATELJICA: Ekaterina BOCHVAROSKA ———————————————————- Ekaterina Bochvaroska received her B.Sc. degree in Computer Science from UP FAMNIT in 2025, where she is currently pursuing the M.Sc. degree in Computer Science. She is currently working as a developer at the Port of Koper, where she is involved in software development, data analysis, and digital solutions for logistics and port operations. Her research interests include decentralized systems, distributed computing, blockchain technologies, algorithms and data structures. ————————————————————————————————————————————- NASLOV: RAVEN: A Retention-Aware Verifiable Extension-Block Network for Off-Chain Message Storage and Retrieval ————————————————————————————————————————————- POVZETEK: RAVEN is a prototype protocol and reference implementation that stores encrypted-message data in off-chain extension blocks and commits each block to an ordered parent chain through a small anchor record. Nodes keep different amounts of history – archive nodes retain everything, regular nodes only a recent suffix window and a client retrieves height ranges from whichever nodes can serve them. Every returned block is verified against its canonical, final anchor before acceptance, so corrupt, missing, or orphaned data is detected rather than trusted. The project covers the protocol core, the node runtime, the retention-aware retrieval pipeline, and an experiment that runs the same workload across several strategies on a local Docker Compose demo. Seminar bo potekal v angleškem jeziku. ============================================================================== 2. predavanje: ============ ————————————————– PREDAVATELJ: Andrej MILISAVLJEVIĆ ————————————————– Andrej Milisavljević is a student of Data Science at UP FAMNIT, currently researching cheminformatics at UPR with professors Marko Jukić and Jure Pražnikar as mentors. Their research includes methods for protein modeling, binding site detection, ligand docking, and the parallelization and distribution of cheminformatics computational analyses. ———————————————————————- NASLOV: SAVI ionization and conformer generation ———————————————————————- POVZETEK: In molecular docking simulations used for the discovery of new medicines, the initial conformation and ionization states of the molecules being studied are crucial for ensuring biochemically relevant results and allowing drug-like molecules to be recognized. In this work, we describe a distributed and parallelized pipeline for efficiently computing ionization states and molecular conformations of 1 billion molecules from the Synthetically Accessible Virtual Inventory (SAVI), and the resulting docking-ready dataset of drug-like molecules for use in drug discovery and other related studies. Seminar bo potekal v angleškem jeziku. ============================================================================== Seminarja bosta potekala online prek aplikacije Zoom s pričetkom ob 16:00 uri na sledeči povezavi: https://upr-si.zoom.us/j/297328207?pwd=S3Zpdk1VR3pjckNtWkQwKzlvcDR5UT09 Meeting ID: 297 328 207 Passcode: 123456789 Vabljeni!

The post Ekaterina BOCHVAROSKA: RAVEN: A Retention-Aware Verifiable Extension-Block Network for Off-Chain Message Storage and Retrieval in Andrej Milisavljević: SAVI ionization and conformer generation appeared first on UP Famnit.

Aljaž Gec:Vpliv različnih načinov uporabe mobilnih telefonov na dobrobit srednješolcev

mario.krajoski — Sun, 14 Jun 2026 22:00:00 +0000

———————————- PREDAVATELJ: Aljaž GEC ———————————- Aljaž Gec je študent magistrskega programa Računalništvo in informatika na UP FAMNIT. Na Fakulteti za računalništvo in informatiko v Ljubljani je diplomiral na temo zasnove informacijskega sistema za osnovne šole. ———————————————————————————————————————– NASLOV: Vpliv različnih načinov uporabe mobilnih telefonov na dobrobit srednješolcev ———————————————————————————————————————– POVZETEK: Mobilni telefoni predstavljajo osrednji del vsakdana sodobnih mladostnikov, njihova vseprisotnost pa pomembno vpliva na način komunikacije, učenja, preživljanja prostega časa in oblikovanja socialnih stikov. Namen raziskave je bil analizirati navade uporabe mobilnih telefonov med srednješolci ter oceniti njihov vpliv na koncentracijo, učenje, kakovost spanja in digitalno higieno. Raziskava, izvedena med 83 dijaki računalniških srednješolskih programov, je pokazala, da dijaki telefone najpogosteje uporabljajo za družbena omrežja in zabavne vsebine, medtem ko je uporaba za šolske in izobraževalne namene precej nižja. Seminar bo potekal v slovenskem jeziku. Zoom povezava ostaja enaka. Seminar bo sledil prvim dvem seminarjem.

The post Aljaž Gec:Vpliv različnih načinov uporabe mobilnih telefonov na dobrobit srednješolcev appeared first on UP Famnit.

Vedenje velikih jezikovnih modelov v napovednih trgih z različnimi udeleženci & A High-Rate Data Acquisition Protocol with Relative Topology Reconstruction & Machine learning models for predicting personal loan acquisition

mario.krajoski — Sun, 07 Jun 2026 22:00:00 +0000

V ponedeljek, 8. junija 2026, bodo ob 16:00 uri izvedena tri predavanja v okviru PONEDELJKOVEGA SEMINARJA RAČUNALNIŠTVA IN INFORMATIKE Oddelkov za Informacijske znanosti in tehnologije UP FAMNIT in UP IAM. ČAS/PROSTOR: 8. junij 2026 ob 16.00 prek Zoom-a. 1. predavanje: ============ ——————————————- PREDAVATELJ: Marjan MEGLEN ——————————————- Marjan Meglen je magistrski študent Računalništva in informatike na UP FAMNIT. ———————————————————————————————————————– NASLOV: Vedenje velikih jezikovnih modelov v napovednih trgih z različnimi udeleženci ———————————————————————————————————————– POVZETEK: V seminarju bo predstavljena analiza vedenja velikega jezikovnega modela pri napovedovanju izidov na napovednih trgih. Osrednje vprašanje seminarja je, ali se napovedi modela spreminjajo glede na informacije, ki jih model prejme v pozivu. Eksperiment vključuje tri neodvisne spremenljivke: vrsto drugih udeležencev trga, prikaz trenutnih tržnih verjetnosti in prikaz relevantnih novic. Model je za posamezen trg in datum podal napovedano verjetnost, da se bo trg razrešil v izid YES. Rezultati kažejo, da ima prikaz tržnih verjetnosti najmočnejši in najbolj konsistenten vpliv na napovedi modela, novice imajo prav tako izrazit, vendar tržno specifičen učinek, medtem ko je vpliv vrste drugih udeležencev šibkejši in manj konsistenten. S tem seminar pokaže, da so napovedi velikih jezikovnih modelov v napovednih trgih najbolj občutljive na neposredne informacije o trgu in dogodku. Seminar bo potekal v slovenskem jeziku. ============================================================================================================= 2. predavanje: ============ ————————————– PREDAVATELJ: Blaž JERMAN ————————————– Blaž Jerman is a student of the master's program Computer Science at UP FAMNIT. ———————————————————————————————————————- NASLOV: A High-Rate Data Acquisition Protocol with Relative Topology Reconstruction ———————————————————————————————————————- POVZETEK: In this seminar, a protocol for rapid data collection in wired sensor networks will be presented. The focus will be on the use of simple UART communication and on the way sensor nodes collect and forward data toward a central node. The seminar will also introduce an automatic reconstruction of the network’s relative topology, which reduces the need for manually defining connections between sensors. Finally, measurement results obtained using linear and tree-based network structures will be presented as case studies for evaluating the protocol’s performance. Seminar bo potekal v angleškem jeziku. ============================================================================================================= 3. predavanje: ============ ————————————————— PREDAVATELJICA: Pika POVH MAVRIČ ————————————————— Pika Povh Mavrič is currently completing her master’s studies in Computer Science at UP FAMNIT. She works as a data analyst in the Customer Relationship Management department at a bank, where she applies and deepens her expertise in data analytics. Her work involves automating processes, improving data quality, creating various reports and analyses, and applying data-driven decision-making to everyday processes within the department. The topic of her paper aligns well with her work in the banking sector. —————————————————————————————————— NASLOV: Machine learning models for predicting personal loan acquisition —————————————————————————————————— POVZETEK: In modern retail banking, the traditional approach of mass marketing consumer loans is becoming highly inefficient and often leads to customer fatigue. To address this issue, this research project focuses on developing a machine learning model designed to accurately predict a customer's intent to acquire a personal loan. By analyzing historical data, including demographics, product ownership, and past marketing engagement, the project uncovers hidden behavioral patterns. This predictive approach allows financial institutions to shift towards a more customer-centric strategy, optimizing marketing resources and offering loans only to those who truly need them. Seminar bo potekal v angleškem jeziku. ============================================================================================================= Seminarji bodo potekali online prek aplikacije Zoom s pričetkom ob 16:00 uri na sledeči povezavi: https://upr-si.zoom.us/j/297328207?pwd=S3Zpdk1VR3pjckNtWkQwKzlvcDR5UT09 Meeting ID: 297 328 207 Passcode: 123456789 Vabljeni!

The post Vedenje velikih jezikovnih modelov v napovednih trgih z različnimi udeleženci & A High-Rate Data Acquisition Protocol with Relative Topology Reconstruction & Machine learning models for predicting personal loan acquisition appeared first on UP Famnit.

Kosar SEYYEDHOSSEINZADEH in Asmir KADUŠIĆ

mario.krajoski — Sun, 31 May 2026 22:00:00 +0000

V ponedeljek, 1. junij 2026, bodo ob 16:00 uri izvedeni dve predavanji v okviru PONEDELJKOVEGA SEMINARJA RAČUNALNIŠTVA IN INFORMATIKE Oddelkov za Informacijske znanosti in tehnologije UP FAMNIT in UP IAM. ČAS/PROSTOR: 1. junij 2026 ob 16.00 v FAMNIT-VP3. 1. predavanje: ============ —————————————————————- PREDAVATELJICA: Kosar SEYYEDHOSSEINZADEH —————————————————————- Kosar Seyedhosseinzadeh is a second-year PhD student and teaching assistant at UP FAMNIT, where she works with the HICUP Lab. She is working on music recommender systems and user modeling. She received her bachelor’s and master’s degrees in computer engineering from Iran, where her master’s research also focused on recommender systems. —————————————————————————————————————————————————– NASLOV: What do Listeners Attend to When Listening to Music? Toward Explainable Music Recommendations ————————————————————————————————————————————- POVZETEK: Music recommender systems are good at suggesting songs, but explaining why a song is relevant to a listener is more difficult. This Seminar explores how listeners differ in what they attend to when listening to music, especially lyrics and musical elements such as rhythm, melody, and harmony. The main idea is that understanding these listener orientations can support user modeling for future explainable music recommender systems. Seminar bo potekal v angleškem jeziku. ============================================================================== 2. predavanje: ============ —————————————— PREDAVATELJ: Asmir KADUŠIĆ —————————————— Asmir Kadušić is a master’s student at UP FAMNIT with a bachelor’s degree in applied mathematics. Currently, he works in the industry at Quant3S as a data scientist/software developer on different kinds of problems. His work includes big data related to commodity trading, forecasting models, database maintenance, and designing solutions for various problems using Microsoft technologies. ——————————————————————————————————————— NASLOV: Scallable Parallel Influence Maximization with a Multi-State Diffusion Model ——————————————————————————————————————— POVZETEK: I will present my work related to my master’s thesis. More specifically, I will present the extension I developed which introduces multistate nodes in the network and addresses the IM problem within the existing theoretical limits. The solution is designed for a distributed system of machines using the MPI model, with the goal of solving and running it on large real-world graphs. I also apply the solution to political influence analysis in networks using the soc-pokec relationship dataset. Seminar bo potekal v angleškem jeziku. ============================================================================== Seminarja bosta potekala v predavalnici FAMNIT-VP3 s pričetkom ob 16:00 uri. Vabljeni!

The post Kosar SEYYEDHOSSEINZADEH in Asmir KADUŠIĆ appeared first on UP Famnit.

Francesco RICCI: Simulation-based evaluation of trustworthy recommender systems

mario.krajoski — Sun, 24 May 2026 22:00:00 +0000

V ponedeljek, 25. maja 2026, bo ob 16:00 uri izvedeno predavanje v okviru PONEDELJKOVEGA SEMINARJA RAČUNALNIŠTVA IN INFORMATIKE Oddelkov za Informacijske znanosti in tehnologije UP FAMNIT in UP IAM. ČAS/PROSTOR: 25. maj 2026 ob 16.00 v FAMNIT-VP3. —————————————— PREDAVATELJ: Francesco RICCI —————————————— Francesco Ricci is senior professor in Computer Science of Free University of Bozen-Bolzano (UNIBZ), Italy. He is member of the UNIBZ Competence Center on Sustainability and member of the Steering Committee of the Digital Humanism Initiative, TUW, Vienna. His current research interests focus on the usage of Artificial Intelligence techniques, such as Recommender Systems and intelligent agents, in supporting human collaboration with AI, and ultimately improving users' decision making processes and wellbeing. He is interested in building systems that can help groups and individuals to make more rational and fair decisions in complex and context dependent scenarios, such as, news and tourism. He is the author of more than 250, highly cited, refereed publications. He coedited the Recommender Systems Handbook, a reference publication, and served as president of the steering committee of the ACM conference on RSs. https://scholar.google.com/citations?user=vK7a7K8AAAAJ&hl ——————————————————————————————————– NASLOV: Simulation-based evaluation of trustworthy recommender systems ——————————————————————————————————– POVZETEK: Recommender systems (RSs) are personalized artificial intelligence (AI) tools routinely used by online platforms to promote algorithmically selected news, posts, music, travel, and videos. In this talk I will focus on the goal of making these systems more trustworthy, ensuring they better serve the various stakeholders interested in their functionality, especially the end users and the providers of the recommended items. A novel type of user/system interaction simulation framework, proposed as an approach to assess RSs performance, will therefore be presented. Compared to the standard train/test ML evaluation approach, this framework enables a better estimation of the longitudinal and multidimensional effects (positive and negative) that an RS can have. The core idea is to more faithfully simulate users' reactions to the recommendations produced by the tested RS by relying on a calibrated algorithmic model of how users make their choices, i.e., select items among the recommended ones. This approach departs from the standard ML testing mechanism that leverages testing data sampled from historical user/system interaction logs, which, unfortunately, were acquired when users interacted with unknown and different RSs. The application and usefulness of this evaluation approach will be exemplified in a particular case study: sustainable tourism management, specifically, how to mitigate overtourism, respect local communities, and still satisfy tourist preferences. Seminar bo potekal v angleškem jeziku v predavalnici FAMNIT-VP3 s pričetkom ob 16:00 uri. Vabljeni!

The post Francesco RICCI: Simulation-based evaluation of trustworthy recommender systems appeared first on UP Famnit.

Daniel LE ROUX: Should Schools Ban Smartphones to Enhance Academic Performance? Evidence from Five South African High Schools

mario.krajoski — Mon, 18 May 2026 22:00:00 +0000

V četrtek, 21. maja 2026, bo ob 15:00 uri izvedeno predavanje v okviru PONEDELJKOVEGA SEMINARJA RAČUNALNIŠTVA IN INFORMATIKE Oddelkov za Informacijske znanosti in tehnologije UP FAMNIT in UP IAM. ČAS/PROSTOR: 21. maj 2026 ob 15.00 v FAMNIT-VP3. —————————————– PREDAVATELJ: Daniel LE ROUX —————————————– Prof. Daniel le Roux heads up the Cognition and Technology Research Group at Stellenbosch University in South Africa. He studies various dimensions of the interaction between humans and technology with emphasis on the cognitive and behavioural processes by which humans, both individually and collectively, adopt and adapt to technologies, and how this impacts their performance and well-being. His research is interdisciplinary in nature and has been published in outlets across various domains including Information Systems, Psychology, Business Management and Education. ———————————————————————————————————————— NASLOV: Should Schools Ban Smartphones to Enhance Academic Performance? Evidence from Five South African High Schools ———————————————————————————————————————— POVZETEK: In recent years, concerns about the impact of smartphone use on high school students’ academic performance have intensified, prompting some schools to consider restrictive policies, including complete bans. This seminar presents findings from a multi-year research project conducted in collaboration with five South African high schools, involving data from 2,195 students, 2,264 parents, and 203 teachers. While principals, teachers, and parents widely perceive smartphone use during school hours as detrimental to academic performance, empirical evidence remains mixed. Drawing on two studies—an experimental design and a large-scale survey of students and teachers—this seminar examines the relationship between smartphone policies, usage patterns, and academic outcomes. The findings offer nuanced insights into the effectiveness and implications of smartphone restrictions in school settings. Seminar bo potekal v angleškem jeziku v predavalnici FAMNIT-VP3 s pričetkom ob 15:00 uri. Vabljeni!

The post Daniel LE ROUX: Should Schools Ban Smartphones to Enhance Academic Performance? Evidence from Five South African High Schools appeared first on UP Famnit.

Peter Knees: Digital Humanism – Actively and Inclusively Shaping the Digital Transformation

mario.krajoski — Sun, 17 May 2026 22:00:00 +0000

V ponedeljek, 18. maja 2026, bo ob 16:00 uri izvedeno predavanje v okviru PONEDELJKOVEGA SEMINARJA RAČUNALNIŠTVA IN INFORMATIKE Oddelkov za Informacijske znanosti in tehnologije UP FAMNIT in UP IAM. ČAS/PROSTOR: 18. maj 2026 ob 16.00 v FAMNIT-VP3. ————————————- PREDAVATELJ: Peter KNEES ————————————- Peter Knees is Full Professor for Information Processing and Retrieval at the Faculty of Informatics, TU Wien. For nearly two decades, Peter has been a leading researcher in Music Information Retrieval, with contributions to multimedia and text information retrieval, recommender systems, and digital arts. As UNESCO Chair for Digital Humanism, he focuses on responsible AI, digital literacy, and bridging technological innovation with human-centered values. ———————————————————————————————————————— NASLOV: Digital Humanism – Actively and Inclusively Shaping the Digital Transformation ———————————————————————————————————————— POVZETEK: Digitization and Artificial Intelligence are transforming key areas of society, science, and the public sphere. This presentation examines these transformation processes from the perspective of digital humanism and discusses the design of technological innovation in accordance with democratic values, transparency, and social responsibility. The focus is on questions of algorithmic decision-making processes, power and dependency structures within digital infrastructures, and new demands on skills and education. The talk will highlight the activities of the Digital Humanism Initiative and the UNESCO Chair on Digital Humanism at TU Wien. Particular emphasis is placed on the importance of interdisciplinary research between computer science, the humanities, and social sciences in critically reflecting on and actively shaping digital transformation. Seminar bo potekal v angleškem jeziku v predavalnici FAMNIT-VP3 s pričetkom ob 16:00 uri. Vabljeni!

The post Peter Knees: Digital Humanism – Actively and Inclusively Shaping the Digital Transformation appeared first on UP Famnit.

Arsen Matej GOLUBOVIKJ: Rethinking Subjective Features in Recommender Systems: Personal Views Over Aggregated Values & Nadun Liyanage: Passenger Experience in Autonomous Vehicles

mario.krajoski — Sun, 10 May 2026 22:00:00 +0000

V ponedeljek, 11. maja 2026, bodo ob 16:00 uri izvedeni dve predavanji v okviru PONEDELJKOVEGA SEMINARJA RAČUNALNIŠTVA IN INFORMATIKE Oddelkov za Informacijske znanosti in tehnologije UP FAMNIT in UP IAM. ČAS/PROSTOR: 11. maj 2026 ob 16.00 v FAMNIT-VP3. 1. predavanje: ============ ——————————————————- PREDAVATELJ: Arsen Matej GOLUBOVIKJ ——————————————————- Arsen Matej Golubovikj is currently a teaching assistant and a PhD student in the HICUP Lab at UP FAMNIT, under the supervision of prof. Marko Tkalčič. His academic interests encompass recommender systems, and user modeling, primarily in subjective domains, such as music recommendation and movie recommendation. His doctoral work explores user-centric recommender systems that account for subjective item perspectives. ————————————————————————————————————————————————– NASLOV: Rethinking Subjective Features in Recommender Systems: Personal Views Over Aggregated Values ————————————————————————————————————————————————– POVZETEK: Subjective features of content items, such as emotional resonance and aesthetic quality, have become increasingly important in recommender systems (RecSys), as the field moves beyond objective content and behavioral signals. Traditionally, such features were treated as fixed item-level properties, aggregated across users. However, emerging evidence suggests that subjective features are inherently user-dependent, shaped by individual interpretations and personal perspectives. This paper presents the first direct comparison between fixed (aggregated) and user-specific (subjective) item representations for modeling subjective features in RecSys. Using three datasets spanning movies, videos, and images, with subjective features, such as eudaimonia, hedonia, emotion, and aesthetics, we evaluate the impact of the representation strategy (i.e. fixed vs. user-specific) on recommendation performance across multiple algorithms. Our findings show that user-specific representations consistently outperform aggregate ones, often with statistically significant improvements. These results underscore the importance of modeling subjectivity at the user level, offering concrete guidance for more personalized and effective recommendation systems. Seminar bo potekal v angleškem jeziku. ============================================================================================================= 2. predavanje: ============ ——————————————– PREDAVATELJ: Nadun LIYANAGE ——————————————– Nadun Liyanage is a doctoral researcher at University of Primorska – HICUP Lab. His work explores how immersive technologies can improve interactions in vehicles and transportation contexts, such as driver assistance, infotainment, and user experience in future mobility systems. —————————————————————————- NASLOV: Passenger Experience in Autonomous Vehicles —————————————————————————- POVZETEK: Autonomous vehicles (AVs) shift mobility from a driver-centered task to a passenger-centered experience, making comfort, trust, and overall passenger experience critical determinants of acceptance. This review synthesizes empirical research on passenger experience in AV contexts, with particular attention to immersive interventions (e.g., AR/VR) and the realism of experimental methodologies used to study AV travel. We analyze 32 peer-reviewed studies and organize them into a structured design space spanning (i) experimental platform and in-vehicle setup (simulator vs. real-world driving, driving mode, cabin representation, motion cueing, and display technologies), (ii) study focus and in-scenario roles (passenger/driver/pedestrian, scenarios, and controlled sensory focus), and (iii) measurement strategy and domains (comfort factors, subjective and objective measures, and focus conditions). Alluvial diagrams and complementary quantitative visualizations reveal strong coupling between methodological choices: simulator studies frequently depend on displays and often lack high-fidelity motion cueing, whereas real-world studies naturally provide full motion cues but more often avoid additional displays. Across the literature, visual interventions dominate, while multisensory approaches (auditory, haptic, olfactory) and standardized, multimodal measurement triangulation are less common. Based on these trends, we outline research opportunities for future AV passenger-experience studies, including higher-fidelity experimental setups that combine motion cueing with immersive displays, better separation of “perceived autonomy” confounds such as driver presence/visibility, and more systematic evaluation frameworks that integrate subjective experience with physiological, behavioral, and vehicle/system measures. Seminar bo potekal v angleškem jeziku. ============================================================================================================= Seminarja bosta potekala v predavalnici FAMNIT-VP3 s pričetkom ob 16:00 uri. Vabljeni!

The post Arsen Matej GOLUBOVIKJ: Rethinking Subjective Features in Recommender Systems: Personal Views Over Aggregated Values & Nadun Liyanage: Passenger Experience in Autonomous Vehicles appeared first on UP Famnit.

Michelle FERNANDO: Immersive Technologies for Motor Skill Learning Guidance

mario.krajoski — Sun, 03 May 2026 22:00:00 +0000

V ponedeljek, 4. maja 2026, bodo ob 16:00 uri izvedeni dve predavanji v okviru PONEDELJKOVEGA SEMINARJA RAČUNALNIŠTVA IN INFORMATIKE Oddelkov za Informacijske znanosti in tehnologije UP FAMNIT in UP IAM. ČAS/PROSTOR: 4. maj 2026 ob 16.00 v FAMNIT-VP3. 1. predavanje: ============ —————————————————- PREDAVATELJICA: Michelle FERNANDO —————————————————- Michelle Fernando is a PhD student and teaching assistant at UP FAMNIT, where she works at the HICUP Lab. She received the B.Sc. (Hons) degree in computer science from the University of Colombo, Sri Lanka. Her research focuses on human-computer interaction, extended reality, and human motion analysis in the context of sports training and skill acquisition. ——————————————————————————————– NASLOV: Immersive Technologies for Motor Skill Learning Guidance ——————————————————————————————– POVZETEK: Motor skill learning is the process of acquiring, refining, and automating physical movements through structured practice. Traditionally, this process relies on a feedback loop between a learner and a coach, in which the instructor provides "feedforward", demonstrations or instructions on how to move, followed by corrective feedback after the attempt. However, this traditional model is often constrained by the limited availability of expert human coaches and the difficulty of delivering consistent, objective, and real-time guidance during practice sessions. Furthermore, physical practice often lacks the precise feedback required for learners to accurately monitor their own movement mechanics and adjust accordingly. Immersive technologies, such as Virtual Reality (VR) and Augmented Reality (AR), offer new opportunities to address these limitations by embedding visual, auditory, and haptic guidance directly into the training environment. This study examines the design of immersive systems for motor skill training through the lens of established motor learning theories. We analyze the current literature to synthesize a structured design space that categorizes immersive systems based on their technological configurations and instructional design paradigms. Our findings highlight current research trends, identify a significant gap in technological support for expert-level performance, and outline key directions for future research in designing effective, theory-driven immersive training systems. Seminar bo potekal v angleškem jeziku. ============================================================================================================= 2. predavanje: ============ —————————————————– PREDAVATELJ: Nilukshan KRISHNARAM —————————————————– Nilukshan Krishnaram is a PhD student and teaching assistant at UP FAMNIT, where he is affiliated with the HICUP Lab. He holds a B.Sc. (Hons) in Information Systems from the University of Colombo, Sri Lanka. His research interests focus on human–computer interaction, extended reality, user experience design, and visual and perceptual attention guidance. —————————————————————————————————————————————— NASLOV: Where You Look Is Not Random: Attention Guidance Across AR, VR, and Traditional Displays —————————————————————————————————————————————— POVZETEK: Guiding user attention is a fundamental challenge in environments where important information can appear anywhere across the visual field, particularly in traditional displays, augmented reality, and virtual reality. A growing body of research has explored techniques that direct attention toward relevant objects or regions, ranging from perceptible techniques such as arrows, labels, animations and highlights, to more subtle techniques such as flicker, brightness modulation, color vibration, and blur. This work surveys attention guidance techniques across the reality–virtuality continuum and examines how they draw on theories of visual attention, Gestalt principles, and visual variables including position, color, and size. A central distinction is made between perceptible techniques, which are consciously noticeable, and imperceptible techniques, which attempt to influence gaze while preserving visual continuity and immersion. The survey further highlights an important challenge in the literature: although many techniques improve search performance and attentional focus, fewer studies rigorously evaluate whether these cues remain non-distracting or preserve immersion. The findings show that attention guidance is not only a matter of making users look at the right place, but of doing so in a way that remains effective, subtle, and perceptually acceptable across different visual environments. Seminar bo potekal v angleškem jeziku. ============================================================================================================= Seminarja bosta potekala v predavalnici FAMNIT-VP3 s pričetkom ob 16:00 uri. Vabljeni!

The post Michelle FERNANDO: Immersive Technologies for Motor Skill Learning Guidance appeared first on UP Famnit.