ponedeljek, 25. avgust 2025 Marija Rakić: Prediction and Validation of the Temperature Factors of Protein Structures

V ponedeljek, 25. avgusta 2025, 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. avgust 2025 ob 16.00 prek Zoom-a (https://upr-si.zoom.us/j/297328207?pwd=S3Zpdk1VR3pjckNtWkQwKzlvcDR5UT09).

--------------------------------------------
PREDAVATELJICA: Marija RAKIĆ
--------------------------------------------

Marija Rakić is a 2nd-year Data Science master’s student at UP FAMNIT, writing her master thesis under the supervision of Assoc. Prof. Jure Pražnikar, PhD. She is also working at UP FAMNIT, as part of the pilot project GDI UP.

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NASLOV: Prediction and Validation of the Temperature Factors of Protein Structures
------------------------------------------------------------------------------------------------------------------

POVZETEK:

Experimental B-factors, while routinely deposited in crystallographic models, are often inconsistent, resolution-dependent, or entirely missing in predicted structures. To overcome these limitations, we employed a model for the goal of predicting and validating protein B-factors. The model is based on graphlet degree vectors (GDVs), which capture the local topological environment of each atom within a protein structure. The model was used on a dataset of nearly 69,000 protein structures from the Protein Data Bank (PDB), where GDVs were used as features in a multiple linear regression framework. We showed that this approach enables the prediction of B-factors without relying on resolution-specific parameters or refinement metadata. Evaluation of model performance shows strong agreement between predicted and experimental values, with a mean Spearman correlation of 0.72 across the dataset and consistent performance across resolution groups. As a key outcome, a web-based tool named ProtWeb was developed. It allows users to upload protein structures in PDB format and receive two modified files: predicted.pdb, containing normalized B-factor predictions, and rescaled.pdb, where predicted values are scaled to match the experimental distribution.

Seminar bo potekal v angleškem jeziku.

Seminar bo izveden online prek Zoom-a na sledeči povezavi:

https://upr-si.zoom.us/j/297328207?pwd=S3Zpdk1VR3pjckNtWkQwKzlvcDR5UT09

Meeting ID: 297 328 207
Passcode: 123456789

Vabljeni!

---

ponedeljek, 18. avgust 2025 Daniil Baldouski: An open-shop scheduling problem with operations batching

V ponedeljek, 18. avgusta 2025, 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. avgust 2025 ob 16.00 prek Zoom-a (https://upr-si.zoom.us/j/297328207?pwd=S3Zpdk1VR3pjckNtWkQwKzlvcDR5UT09).

--------------------------------------------
PREDAVATELJ: Daniil BALDOUSKI
--------------------------------------------

Daniil Baldouski is a third-year PhD student of Computer Science at UP FAMNIT.

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NASLOV: An open-shop scheduling problem with operations batching
-----------------------------------------------------------------------------------------------

POVZETEK:

This work generalizes the open-shop and batch scheduling problems by considering merging of operations. We propose an efficient two-phase heuristic, which combines a graph-based optimal merging algorithm with a mixed-integer linear programming (MILP) model for the open-shop scheduling part of the problem. We introduce a benchmark instance set to validate our methodology.

Seminar bo potekal v angleškem jeziku.

Seminar bo izveden online prek Zoom-a na sledeči povezavi:

https://upr-si.zoom.us/j/297328207?pwd=S3Zpdk1VR3pjckNtWkQwKzlvcDR5UT09

Meeting ID: 297 328 207
Passcode: 123456789

Vabljeni!

---

četrtek, 7. avgust 2025 Nedim ŠIŠIĆ: Deep learning in whole brain MRI segmentation: A Review

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sreda, 30. julij 2025 Matic POŽAR: Network-Aware Uplift Modeling through Influence Maximization Techniques in Dina MITROVIĆ: Analysis of full-length 16S rRNA gene and ITS regions amplicons sequenced with Oxford Nanopore Technologies

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četrtek, 24. julij 2025 Nikola KOVAČEVIĆ: Discrete-Event Simulation Model for Wood Waste Reverse Supply Chain in Jovan PAVLOVIĆ Integrating agent-based modeling and network science for responsive epidemic management in urban transport

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ponedeljek, 21. julij 2025 Jakob BEBER: Naključnost v pokrivanju košev in Aljaž GEC: Generativna umetna inteligenca

V ponedeljek, 21. julija 2025, bosta 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: 21. julij 2025 ob 16.00 prek Zoom-a (https://upr-si.zoom.us/j/297328207?pwd=S3Zpdk1VR3pjckNtWkQwKzlvcDR5UT09).

1. predavanje:
============

--------------------------------------
PREDAVATELJ: Jakob BEBER
--------------------------------------

Jakob Beber je študent magistrskega programa računalništvo in informatika. Na UP FAMNIT je dodiplomski študij zaključil z diplomsko nalogo o algoritmih, ki rešujejo problem pokrivanja košev. Raziskovanje tega problema nadaljuje na magistrskem študiju, zato bo na seminarju predstavil nove ugotovite.

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NASLOV: Naključnost v pokrivanju košev
--------------------------------------------------------

POVZETEK:

Na seminarju bo predstavljena vsebina članka, v katerem predstavimo sprotno različico problema pokrivanja košev in možne strategije za njegovo reševanje. Kasneje se osredotočimo na strategijo naslednji ustrezen (DNF), pri kateri ugotavljamo, da je analiza najslabšega primera preveč pesimistična za praktično uporabo. Da bi to raziskali, smo razvili spletno platformo za izvajanje in preizkušanje strategij ter različnih generatorjev zaporedij. V naših empiričnih rezultatih prikažemo razliko med teoretično najslabšim in "povprečnim" primerom uspešnosti za strategijo DNF.

Seminar bo potekal v slovenskem jeziku.

=============================================================================================================

2. predavanje:
============

----------------------------------
PREDAVATELJ: Aljaž GEC
----------------------------------

Aljaž Gec je magistrski študent računalništva in informatike na UP FAMNIT in zaposlen na srednji računalniški šoli kot učitelj strokovnih predmetov iz področja računalništva. Zanimajo ga področja umetne inteligence, programiranja in poučevanja le-tega. Njegov raziskovalni seminar je tesno povezan z njegovim delovnim področjem, saj obravnava razlago umetne inteligence pri generiranju različnih vsebin, med drugim tudi pisanju programov v različnih programskih jezikih.

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NASLOV: Generativna umetna inteligenca
---------------------------------------------------------

POVZETEK:

Generativna umetna inteligenca (UI) je vrsta UI, ki zna ustvarjati nove vsebine, kot so besedila, slike, koda, glasba in video. Deluje na podlagi učenja iz ogromnih količin podatkov in uporablja statistične vzorce za ustvarjanje novih rezultatov. Med glavnimi tehnologijami so transformerski modeli (npr. ChatGPT) in difuzijski modeli (npr. DALL·E, Stable Diffusion). V praksi lahko generativna UI npr. iz besedilnega opisa ustvari sliko ali napiše programsko kodo po navodilih. Uporablja se na različnih področjih, kot so umetnost, izobraževanje, programiranje in podpora strankam. V prihodnosti se pričakuje razvoj večmodalnih modelov, boljše etične smernice ter lokalno delovanje UI brez povezave v internet.

Seminar bo potekal v slovenskem jeziku.

=============================================================================================================

Seminarja bosta izvedena online prek Zoom-a na sledeči povezavi:

https://upr-si.zoom.us/j/297328207?pwd=S3Zpdk1VR3pjckNtWkQwKzlvcDR5UT09

Meeting ID: 297 328 207
Passcode: 123456789

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četrtek, 10. julij 2025 Andrej ERJAVEC: Pristopi k iskanju informacij - od klasičnih do jezikovnih modelov in Marjan MEGLEN: Primerjava pristopov učenja pri matrični faktorizaciji v priporočilnih sistemih

V ponedeljek, 14. julija 2025, bosta 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: 14. julij 2025 ob 16.00 prek Zoom-a (https://upr-si.zoom.us/j/297328207?pwd=S3Zpdk1VR3pjckNtWkQwKzlvcDR5UT09).

1. predavanje:
============

------------------------------------------
PREDAVATELJ: Andrej ERJAVEC
------------------------------------------

Andrej Erjavec je študent 2. letnika magistrskega študijskega programa Računalništvo in informatika na UP FAMNIT.

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NASLOV: Pristopi k iskanju informacij - od klasičnih do jezikovnih modelov
-----------------------------------------------------------------------------------------------------

POVZETEK:

Z naraščajočo količino digitalno shranjenih podatkov postaja učinkovito iskanje informacij eden osrednjih izzivov sodobne informacijske tehnologije. Področje iskanja informacij (Information Retrieval) se je oblikovalo kot odgovor na potrebo po sistematičnem dostopu do relevantnih vsebin v vse obsežnejših podatkovnih zbirkah. Poseben izziv predstavljajo nestrukturirani podatki, kot so besedila, slike in video posnetki, katerih delež v celotni količini podatkov že presega 80 odstotkov. V okviru tega seminarja bo predstavljen razvoj pristopov k iskanju informacij skupaj s konkretnimi implementacijami ter njihovimi področji uporabe.

Seminar bo potekal v slovenskem jeziku.

================================================================================

2. predavanje:
============

-------------------------------------------
PREDAVATELJ: Marjan MEGLEN
-------------------------------------------

Marjan Meglen je magistrski študent Računalništva in informatike na UP FAMNIT. Zanimajo ga področja strojnega učenja, priporočilnih sistemov in razlage modelov.

---------------------------------------------------------------------------------------------------------------------
NASLOV: Primerjava pristopov učenja pri matrični faktorizaciji v priporočilnih sistemih
---------------------------------------------------------------------------------------------------------------------

POVZETEK:

Na seminarju bomo predstavili matrično faktorizacijo kot enega najpogosteje uporabljenih pristopov sodelovalnega filtriranja v priporočilnih sistemih. Osredotočili smo se na primerjavo dveh pristopov učenja latentnih faktorjev: sočasnega in postopnega. Uporabili smo podatkovno zbirko Movielens, kjer smo metode primerjali glede na napovedno uspešnost in razložljivost modela. Za napovedno uspešnost smo uporabili metrikо RMSE, za razložljivost pa vizualizacije in statistične teste, kot sta Anova in parni t testi. Rezultati so pokazali, da je sočasno učenje omogočilo hitrejšo konvergenco in nižjo napovedno napako, medtem ko je postopno učenje zagotovilo boljšo razložljivost, predvsem pri filmih iz pogostejših žanrov. S tem smo pokazali, da izbira pristopa učenja pomembno vpliva na razmerje med napovedno natančnostjo in razložljivostjo modela.

Seminar bo potekal v slovenskem jeziku.

================================================================================

Seminarja bosta izvedena online prek Zoom-a na sledeči povezavi:

https://upr-si.zoom.us/j/297328207?pwd=S3Zpdk1VR3pjckNtWkQwKzlvcDR5UT09

Meeting ID: 297 328 207
Passcode: 123456789

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ponedeljek, 7. julij 2025 Anđela ĐUKIĆ:Application of Clustering-Based Recommendation Systems in Nursing Diagnosis in Pika POVH MAVRIČ: Understanding Customer Behavior Through Data Analytics in the Banking Sector

V ponedeljek, 7. julija 2025, bosta 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: 7. julij 2025 ob 16.00 prek Zoom-a (https://upr-si.zoom.us/j/297328207?pwd=S3Zpdk1VR3pjckNtWkQwKzlvcDR5UT09).

1. predavanje:
============

--------------------------------------------
PREDAVATELJICA: Anđela ĐUKIĆ
--------------------------------------------

Anđela Đjukić is a second year Data Science Masters student at UP FAMNIT under the supervision of mentor Bošjan Žvanut and co-mentor Branko Kavšek. She is also a part of the GDI UP Project at FAMNIT.

-------------------------------------------------------------------------------------------------------------------------
NASLOV: Application of Clustering-Based Recommendation Systems in Nursing Diagnosis
-------------------------------------------------------------------------------------------------------------------------

POVZETEK:

This work explores how recommendation systems, specifically the CLUICE algorithm, can help with more efficient and accurate nursing diagnoses for older adults in a shorter amount of time.
The process of making a nursing diagnosis involves many steps and a lot of time and effort, specifically when connecting symptoms to possible diagnoses, and there aren’t many tools that help with this in an automated way. 
With this in mind, as well as the basic recommendation system knowledge, patients are modeled as users and their symptoms as items, using ideas from recommendation systems commonly seen and used in domains like marketing. The aim is to investigate if a system like this can suggest nursing diagnoses via identifying patterns in symptom data, even when the information is incomplete or limited.
The further goal comes through applying an approach not traditionally used in healthcare, with the potential to enhance clinical decision-making and reduce the cognitive burden on practitioners.

Seminar bo potekal v angleškem jeziku.

================================================================================

2. 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.

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NASLOV: Understanding Customer Behavior Through Data Analytics in the Banking Sector
--------------------------------------------------------------------------------------------------------------------------

POVZETEK:

This article examines how data analytics and machine learning are reshaping customer behavior analysis in the banking sector. It focuses on key applications such as credit scoring, fraud detection, churn prediction, and product recommendation, using models like Random Forest, LightGBM, and neural networks. The study highlights improved decision-making and customer engagement, while also addressing challenges around data quality, transparency, and ethics. It underscores the importance of organizational readiness and responsible AI practices to balance predictive accuracy with fairness and interpretability.

Seminar bo potekal v angleškem jeziku.

================================================================================

Seminarja bosta izvedena online prek Zoom-a na sledeči povezavi:

https://upr-si.zoom.us/j/297328207?pwd=S3Zpdk1VR3pjckNtWkQwKzlvcDR5UT09

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ponedeljek, 30. junij 2025 Una VULETIĆ: Computational Analysis and Visualization of Viewing Behavior: Interactive vs. Non-Interactive Documentary / Zala ŽUŽEK: Prediction of Eudaimonic and Hedonic Movie characteristics using User reviews

V ponedeljek, 30. junija 2025, bosta 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: 30. junij 2025 ob 16.00 v FAMNIT-VP2.

1. predavanje:
============

------------------------------------------
PREDAVATELJICA: Una VULETIĆ
------------------------------------------

Una Vuletić is 2nd year Data Science master's student at UP FAMNIT, writing her master thesis under supervision of Associate Professors Matjaž Kljun and Klen Čopič Pucihar. She is also working at HICUP Lab at UP FAMNIT, as part of the pilot project GDI UP.

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NASLOV: Computational Analysis and Visualization of Viewing Behavior: Interactive vs. Non-Interactive Documentary
---------------------------------------------------------------------------------------------------------------------------------------------------------------

POVZETEK:

In this seminar, we explore how interactivity in digital documentaries influences viewer experience, both visually and emotionally. While traditional documentaries rely on passive, linear storytelling, which can limit emotional engagement and attention, interactive documentaries allow viewers to shape their own experience while navigating through content. To investigate effect of interactivity, we analyzed eye-tracking and facial expression data from two participant groups who watched interactive and non-interactive versions of the iIsland documentary, which focuses on the lives of the last residents of Biševo, a small Croatian island.

Seminar bo potekal v angleškem jeziku.

=============================================================================================================

2. predavanje:
============

---------------------------------------
PREDAVATELJICA: Zala ŽUŽEK
---------------------------------------

Zala Žužek is currently completing her master’s studies in Data Science at UP FAMNIT. Her interests include data analytics, machine learning, and recommender systems, which she explores in depth through her master’s thesis on the prediction of psychological content in user-generated movie reviews. She currently works as a data analyst in the Data Intelligence and Delivery Assurance department, where she applies and deepens her expertise in data analytics, process automation, and data-driven assurance. Her work involves automating audit processes, improving data quality, and supporting digital transformation by integrating advanced analytics into assurance workflows. She is passionate about using data to enhance efficiency, uncover meaningful insights, and enable smarter decision-making in complex business environments.

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NASLOV: Prediction of Eudaimonic and Hedonic Movie characteristics using User reviews
-------------------------------------------------------------------------------------------------------------------------

POVZETEK:

This thesis explores the use of machine learning to predict eudaimonic and hedonic movie characteristics based on user reviews. Using natural language processing (NLP) techniques, we extracted relevant features from full-text reviews scraped from an online movie database and trained several regression and classification models. The results indicate that user reviews contain sufficient emotional and semantic information that can predict user preferences more effectively than baseline models. These findings suggest that integrating text-based insights with traditional features can provide a deeper understanding of user behavior and improve the performance of recommendation systems.

Seminar bo potekal v angleškem jeziku.

 

Vabljeni.

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ponedeljek, 23. junij 2025 Valentina PUCER: Razložljiva umetna inteligenca pri napovedovanju verjetnosti neplačila v bančništvu

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nedelja, 15. junij 2025 Bogdan ŠINIK: Application of Benfords Law on Enviormental Data

V ponedeljek, 16. junija 2025, 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: 16. junij 2025 ob 16.00 v FAMNIT-VP2.

---------------------------------------
PREDAVATELJ: Bogdan ŠINIK
---------------------------------------

Bogdan Šinik is doing his Masters in Data Science at UP FAMNIT under the supervision of Associate Professor Jernej Vičič and Assistant Professor Aleksandar Tošić. He is also working at DLT^2 lab at UP FAMNIT, as part of the pilot project GDI UP.

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NASLOV: Application of Benfords Law on Enviormental Data
----------------------------------------------------------------------------------

POVZETEK: 

This presentation provides an overview of the application of Benford's Law as a novel approach to assess data quality and integrity within Life-Cycle Assessment (LCA). LCA is a critical methodology for evaluating environmental impacts, yet its reliability is highly dependent on the quality of the underlying data, which can often be subject to inconsistencies or potential biases. This study explores the utility of Benford's Law by applying conformity tests to numerical data found in several Life Cycle Inventory (LCI) databases. The work demonstrates how this statistical tool can reveal patterns indicative of potential data anomalies. The research highlights Benford's Law as a simple, computationally efficient, and robust method for enhancing data quality assessment in LCA. Its application offers a valuable means to identify potential issues and improve the overall reliability of environmental impact evaluations.

Seminar bo potekal v živo, s pričetkom ob 16:00 uri v učilnici FAMNIT-VP2.

Vabljeni. 

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ponedeljek, 9. junij 2025 2 predavanji: Špela ČUČKO & Anastasiia DZIUBA: Sofisticiranost ocenjevanja glasbe in vpliv razlage na priporočila & Graphlet-based Network Analysis

V ponedeljek, 9. junija 2025, bosta 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: 9. junij 2025 ob 16.00 v FAMNIT-VP2.

1. predavanje:

------------------------------------------
PREDAVATELJICA: Špela ČUČKO
------------------------------------------

Špela Čučko zaključuje študijski program Podatkovna znanost in trenutno deluje kot podatkovna znanstvenica, kjer se osredotoča na področje zavarovalništva. Njeno delo vključuje razvoj naprednih analitičnih rešitev, ki temeljijo na podatkovnem modeliranju, strojnem učenju ter uporabi statističnih metod za podporo poslovnim odločitvam v zavarovalni industriji.

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NASLOV: Sofisticiranost ocenjevanja glasbe in vpliv razlage na priporočila
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POVZETEK:

Glasba je univerzalni jezik, ki zajema vse kulture in generacije, hkrati pa predstavlja eno najpomembnejših področij za uporabo priporočilnih sistemov. Večina obstoječih sistemov pri glasbi se pretežno zanašajo na podatke o zgodovini poslušanja, priljubljenosti, žanrskih oznakah ali vedenjske vzorce uporabnikov. Razvili smo priporočilni sistem, ki temelji na analizi glasbene kvalitete s poudarkom na ritmu, melodiji, harmoniji in lastnostih besedila. Raziskali smo, kako glasbena izobrazba vpliva na percepcijo teh lastnosti in ali prisotnost razlage pri priporočilih vpliva na uporabnikov okus in zaupanje v model. Ugotovitve potrjujejo subjektivnost dojemanja glasbe, ter nakazujejo potencialen vpliv vsebinskih razlag pri priporočanju skladb z izrazitimi.

Seminar bo potekal v slovenskem jeziku.

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2. predavanje:

-------------------------------------------------
PREDAVATELJICA: Anastasiia DZIUBA
-------------------------------------------------

Anastasiia Dziuba is a second-year Data Science master’s student at UP FAMNIT.

-----------------------------------------------------------
NASLOV: Graphlet-based Network Analysis
-----------------------------------------------------------

POVZETEK:

This research addresses the challenge of capturing local structure in complex networks by applying graphlet-based analysis. While traditional global metrics provide limited insight into detailed connectivity patterns, graphlets (small, connected subgraphs) can offer a more nuanced understanding of how nodes interact within their local neighbourhoods. Although graphlets have been successfully applied in biological and social networks, their potential remains unexplored in other dynamic fields. In this study, we propose an approach to apply graphlet-based analysis to stock market data. The focus is to investigate whether the use of graphlet-based methods can extend traditional approaches by capturing complex topological features. In particular, we will investigate whether graph local and global parameters can improve the detection and interpretation of market shifts and improve portfolio diversification.

Seminar bo potekal v angleškem jeziku.

Vabljeni.

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petek, 23. maj 2025 Shlomo BERKOVSKY: Personality Sensing: Detection of Personality Traits Using Physiological Responses to Image and Video Stimuli

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ponedeljek, 19. maj 2025 Vanja MILESKI: Deep learning for time series data using Inception and ResNet paradigms

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ponedeljek, 24. marec 2025 Fairuz Ishrat BHUIYAN: Comparative Analysis of VR and Traditional Simulators in Anti-Aircraft Training

V ponedeljek, 24. marca 2025, 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: 24. marec 2025 ob 16.00 v FAMNIT-VP2.

------------------------------------------------------
PREDAVATELJICA: Fairuz Ishrat BHUIYAN
------------------------------------------------------

Fairuz Ishrat Bhuiyan is a master’s degree student, born and raised in Helsinki, Finland. She studies Computer Engineering at the University of Turku, and she is specializing in Health Technology. As her minor subject, she studied Marine Technology / Naval Architecture in the Department of Mechanical Engineering at Aalto University, School of Engineering. Her Bachelors thesis topic was Weather and Air Quality in Helsinki and it was part of a national project called Cityzer. In 2021, she completed her one-year military service at the Guard Jaeger Regiment in Santahamina, Helsinki and was promoted to the rank of corporal.

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NASLOV: Comparative Analysis of VR and Traditional Simulators in Anti-Aircraft Training
-----------------------------------------------------------------------------------------------------------------------

POVZETEK:

The study aims to measure attitude processes when using simulators and subjective experiences after use by comparing a VR-based immersive simulator and a classic non-immersive simulator. The target groups are the conscripts in the Parola Armored Brigade of the Finnish Defense Forces, who will receive training in using an anti-aircraft machine gun with the help of virtual reality. Both simulators highlighted commendable traits, such as prompt responsiveness to user actions and awareness of control devices. The VR simulator's propensity to induce more pronounced simulator sickness symptoms occurred similarly in both simulators, suggesting common physiological responses across different simulator types. Interestingly, participants in the VR simulator found it easier to control events and manipulate objects, leading to better engagement than in real-life scenarios. These findings illuminate the advantages and limitations of VR training with augmented cues, offering valuable insights for refinement and future research endeavors.

Seminar bo potekal v živo, s pričetkom ob 16:00 uri v učilnici FAMNIT-VP2.

Vabljeni.

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petek, 7. marec 2025 Jan JOVAN: ChatGPT in ostali jezikovni modeli

V ponedeljek, 10. marca 2025, 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: 10. marec 2025 ob 16.00 v FAMNIT-VP2.

-----------------------------------
PREDAVATELJ: Jan JOVAN
-----------------------------------

Jan Jovan je študent 2. letnika magistrskega programa računalništva in informatike ter razvojni inženir v podjetju Smart Com d.o.o.. Specializira se za integracijo velikih jezikovnih modelov (LLM), kar mu omogoča, da prispeva k razvoju naprednih rešitev v podjetju. Njegovo delo vključuje raziskovanje in implementacijo LLM tehnologij ter iskanje novih načinov za izboljšanje njihove uporabnosti v različnih aplikacijah.

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NASLOV: ChatGPT in ostali jezikovni modeli
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POVZETEK:

Veliki jezikovni modeli (LLM) so revolucionarizirali obdelavo naravnega jezika z izkoriščanjem obsežnih podatkovnih nizov in arhitektur  globokega učenja za generiranjem besedila, odgovarjanjem na vprašanja in izvajanjem kompleksnega sklepanja. Ta seminar raziskuje osnovne mehanizme LLM, vključno z njihovo arhitekturo in metodami usposabljanja, pri čemer izpostavlja naraščajoče število primerov njihove uporabe na različnih področjih. Konkretno se obravnavajo aplikacije LLM v medicini za pomoč pri diagnozi in generiranju medicinske literature, v robotiki za izboljšanje interakcije med človekom in robotom ter v kodiranju za avtomatizacijo razvoja programske opreme. Poudarjeni so tudi izzivi, povezani z ocenjevanjem modelov, vključno z obsegom znanja in razširljivostjo, ter potencialne prihodnje smeri za izboljšanje zmogljivosti LLM.

Seminar bo potekal v živo, s pričetkom ob 16:00 uri v učilnici FAMNIT-VP2.

Vabljeni.

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četrtek, 13. februar 2025 Gianmarco CHERCHI: Interactive and Robust Mesh Booleans

V ponedeljek, 17. februarja 2025, 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: 17. februar 2025 ob 16.00 v FAMNIT-VP2.

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PREDAVATELJ: Gianmarco CHERCHI
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Gianmarco Cherchi is a Computer Science Researcher (Tenure Track Assistant Professor) at the Department of Mathematics and Computer Science of the University of Cagliari (Italy), where he obtained his PhD. His research interests are in Computer Graphics and Geometry Processing, focusing on the generation and optimization of surface and volumetric meshes, and Digital Fabrication. He is also the Professor of the "Data Visualization" (Applied Computer Science and Data Analytics BSc) and "Web Programming" (Computer Science BSc) courses at the University of Cagliari. In 2024, he received the "Young Investigator Award 2024," granted by the Shape Modeling International Organization.

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NASLOV: Interactive and Robust Mesh Booleans
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POVZETEK:

Boolean operations are among the most used paradigms to create and edit digital shapes. Despite being conceptually simple, the computation of mesh Booleans is notoriously challenging. The main issues come from numerical approximations that make the detection and processing of intersection points inconsistent and unreliable, exposing implementations based on floating-point arithmetic to many kinds of failure. Numerical methods based on rational numbers or exact geometric predicates have the needed robustness guarantees that are achieved at the cost of increased computation times that, as of today, have always restricted the use of robust mesh Booleans to offline applications. In this seminar, I will briefly summarize the results obtained in three recent articles on the topic, which have enabled us to develop an algorithm for Boolean operations with robustness guarantees, capable of operating at interactive frame rates on meshes with up to 200K triangles.

Seminar bo potekal v živo, s pričetkom ob 16:00 uri v učilnici FAMNIT-VP2.

Vabljeni.

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četrtek, 16. januar 2025 Ivan DAMNJANOVIĆ: Finding the number of inequivalent arithmetic expressions on n variables

V ponedeljek, 20. januarja 2025, bo ob 17.00 uri izvedeno
predavanje v okviru PONEDELJKOVEGA SEMINARJA RAČUNALNIŠTVA IN INFORMATIKE
Oddelkov za Informacijske znanosti in tehnologije UP FAMNIT in UP IAM.

ČAS/PROSTOR: 20. januar 2025 ob 17.00 v FAMNIT-VP2.

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PREDAVATELJ: Ivan DAMNJANOVIĆ
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Ivan Damnjanović is pursuing a PhD degree in Mathematical Sciences at the Faculty of Mathematics, Natural Sciences and Information Technologies at the University of Primorska. He previously obtained a PhD degree in Electrical Engineering and Computing at the Faculty of Electronic Engineering at the University of Niš, where he currently works as a teaching assistant at the department of mathematics.

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NASLOV: Finding the number of inequivalent arithmetic expressions on n variables
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POVZETEK:

Given n distinct formal variables, in how many ways can we use them to construct different arithmetic expressions? An expression tree is a rooted tree whose internal nodes correspond to some operations to be performed, while its leaves are formal variables. Here, we deal with the expression trees such that the only allowed operations are the four standard arithmetic operations (addition, subtraction, multiplication and division) together with, optionally, additive inversion. We consider two expressions to be equivalent if their expression trees yield the same formal expression. To begin, we provide certain theoretical results concerning the equivalence of arithmetic expressions. Afterwards, we disclose a Θ(n^2) algorithm that computes the number of inequivalent arithmetic expressions on n distinct variables. The algorithm covers both the case when the unary operation of additive inversion is allowed and when it is not.
(This is a joint work with Ivan Stošić and Žarko Ranđelović.)

Seminar bo potekal v živo, s pričetkom ob 17:00 uri v učilnici FAMNIT-VP2.
Pozor, to je eno uro kasneje kot ponavadi !!!

Vabljeni. 

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petek, 10. januar 2025 Jovan PAVLOVIĆ: A Data-Driven Approach for the Analysis of Ridership Fluctuations in Transit Systems

V ponedeljek, 13. januarja 2025, 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: 13. januar 2025 ob 16.00 v FAMNIT-VP2.

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PREDAVATELJ: Jovan PAVLOVIĆ
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Jovan Pavlović is a second-year Data Science master's student at UP FAMNIT, where he also earned his bachelor's degree in Mathematics.

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NASLOV: A Data-Driven Approach for the Analysis of Ridership Fluctuations in Transit Systems
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POVZETEK:

This seminar explores a data-driven approach to analyzing ridership fluctuations in public transportation systems, especially during pandemics. It focuses on identifying critical components within urban transit systems, by employing agent-based simulations and graph analytics techniques. Key findings reveal specific transit stops and routes that are highly sensitive to changes in demand, often serving as bottlenecks or high-risk areas for the spread of infectious diseases.

Seminar bo potekal v živo, s pričetkom ob 16:00 uri v učilnici FAMNIT-VP2.

Vabljeni. 

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