Zagovor doktorske disertacije Gregoryja Caldwella Robsona
Gregory Caldwell Robson, študent doktorskega študijskega programa Matematične znanosti (izvedba v angleškem jeziku) na UP FAMNIT, bo zagovarjal doktorsko disertacijo z naslovom Automorphisms of bicoset digraphs and an alternative BCI problem (Avtomorfizmi digrafov bikoseta in alternativni BCI-problem), pod mentorstvom prof. dr. Edwarda Tauscherja Dobsona. Zagovor bo potekal v torek, 14. 7. 2026 ob 16. uri v predavalnici Famnit-MP1. Doktorska disertacija bo javnosti na vpogled v knjižnici UP. Vljudno vabljeni!
Erasmus+ BIP »Ai v mobilnosti prihodnosti«
Erasmus+ BIP »Ai v mobilnosti prihodnosti« ponuja priložnost za pridobivanje praktičnih znanj s področja umetne inteligence in analize podatkov. Na dogodku bodo prisotni prof. Tomasz Wesołowski (University of Silesia), prof. Toralf Trautmann (HTW Dresden) in prof. Branko Kavšek (UP FAMNIT). Študenti prihajajo z Univerze Vytautasa Magnusa, Univerze HTW Dresden, Univerze v Sileziji v Katovicah in UP FAMNIT. Program omogoča vpogled v uporabo umetne inteligence v avtonomnih vozilih in mobilnosti prihodnosti, pregled ustreznih metod strojnega učenja ter delo na realnih podatkih za razvoj praktičnih veščin. Dogodek bo potekal v Kopru.
Ponedeljkov seminar računalništva in informatike
Ponedeljkov seminar računalništva in informatike
V ponedeljek, 3. avgusta 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: 3. avgust 2026 ob 16.00 prek Zoom-a. 1. 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. ============================================================================================================= 2. predavanje: ============ ——————————————- PREDAVATELJ: Nemanja CVETIĆ ——————————————- Nemanja Cvetić is a Master’s student in Computer Science with a Bachelor’s degree in Information Technology. His research interests include machine learning, explainable artificial intelligence (XAI), data science, computer science and software engineering. His current research focuses on evaluating model interpretability techniques and their practical applications in machine learning. —————————————————————————————————————————————————————————————— NASLOV: Model interpretability in machine learning: A Comparison of LinearSHAP TreeSHAP, and LIME on the California Housing Dataset —————————————————————————————————————————————————————————————— POVZETEK: This seminar presents an empirical comparison of SHAP (LinearSHAP and TreeSHAP) and LIME as post-hoc explainability methods for machine learning models. Using Linear Regression and Random Forest models trained on the California Housing dataset, the study evaluates the quality, consistency, and interpretability of feature attributions. The results demonstrate that SHAP provides more stable and theoretically grounded explanations, while LIME shows greater variability, particularly for complex non-linear models. 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!
Structural Graph Theory Workshop on the Adriatic Coast
Datumi: 24.–28. avgust 2026Lokacija: InnoRenew CoE, Izola, Slovenija O delavnici Ta petdnevna delavnica je namenjena spodbujanju sodelovalnih razprav in raziskovanju različnih tem s področja strukturne teorije grafov. Dogodek je zasnovan kot manjša delavnica, ki omogoča poglobljena predavanja, razprave o odprtih problemih ter dovolj časa za raziskovalne razprave in izmenjavo idej med udeleženci. V duhu osredotočenih matematičnih delavnic je dogodek zasnovan tako, da v sproščenem, a hkrati spodbudnem okolju na jadranski obali spodbuja nastanek novih raziskovalnih sodelovanj. Organizatorji Pascal Gollin Matjaž Krnc Martin Milanič Vsi organizatorji so zaposleni na Univerzi na Primorskem.
SCORES: 12. študentski raziskovalni simpozij iz računalništva
Študentski raziskovalni simpozij iz računalništva je vsakoletna znanstvena konferenca, ki jo skupaj organizirajo Univerza v Ljubljani, Univerza v Mariboru in Univerza na Primorskem. Njen cilj je spodbuditi študente k predstavitvi in objavi njihovega raziskovalnega dela na področju računalništva ter spodbujati sodelovanje, izmenjavo znanja in ustvarjalnost. Simpozij bo potekal 8. oktobra 2026, v prostorih UP FAMNIT.

