Tidligere arrangementer - Side 13

Department seminar. Torfinn Harding is a Professor of Economics at the University of Stavanger Business School. He will be presenting the paper "Quantifying supply-side climate policies" (written with Lassi Ahlvik, J?rgen Juel Andersen, and Jonas Hveding Hamang).

The Departmental Seminar Series features research fellow Andrew Graan, Helsinki Collegium for Advanced Studies, University of Helsinki. 

Til h?stens siste litter?re instituttseminar, vil professor Hans Kristian Strandstuen Rustad legge frem argumentasjon for at lyrikk prim?rt og fundamentalt er en hendelse.

Leiv R?nneberg is a DSTrain Postdoctoral Fellow at the Department of Mathematics and affiliated with The Norwegian Centre for Knowledge-driven Machine Learning (INTEGREAT) at the University of Oslo. Prior to this he was a Research Associate at the MRC Biostatistics Unit at the University of Cambridge, and completed his PhD in Biostatistics at the University of Oslo in 2022. His interests are broadly within the realms of probabilistic machine learning, and connections to Bayesian nonparametrics.
 

Department seminar. Hans Henrik Sievertsen is a Professor at the Danish Center for Social Science Research (VIVE), and an Associate Professor at the Univeristy of Bristol School of Economics. He will present the paper "Saving neonatal lives at scale: lessons for targeting."

Earthquake, landslide, and glacier instabilities are multi-scale processes that cannot be predicted. When a rock is subjected to large stress, it can develop fractures that grow and connect to form a network. This network of fractures spans the entire rock right before it fails catastrophically. Despite extensive research on rock damage, researchers are still far from being able to predict when a rock will fail. Here, I will show how to use a multi-view convolutional neural network model to identify characteristics of a failing rock. By training a neural network model on images of rock samples exposed to different levels of stress, one can predict how close a rock is to failure. The neural network model outperforms traditional estimates based on fracture density. More importantly, the model provides fundamental insight that may offer precursory information on impending material failure. For instance, according to the model, the angle of the fracture plane relative to the principal loading direction becomes a key factor contributing to failure.

Eilif Sommer ?yre, Rosseland Centre for Solar Physics (RoCS), UiO.

Elo?se Mignon (University of Melbourne) will present her research on family relationships in The Wild Duck.

Based on preprints https://arxiv.org/abs/2006.07213 and https://arxiv.org/abs/2406.05382.

The African Anthropology seminar series features Kerry Ryan Chance, associate professor at the Department of Social Anthropology, University of Bergen.

QOMBINE Seminar by Chloe Kim (University of Illinois Urbana-Champaign)

Department seminar. Helene Mass is an Assistant Professor at the University of Vienna. She will be presenting the paper "Optimal Testing in Disclosure Games."

By Prof. Fran?ois Renard, University of Oslo

Join us for a presentation by Chris Murray on Global Threats to Health, featuring a short introduction by Tore Godal. The event is organized by P1H and will be held at the Norwegian Institute of Public Health.

QOMBINE seminar by Roy Araiza (University of Illinois at Urbana-Champaign)

Archaeological Friday seminar with Taylor Peacock. Taylor is a PhD student in archaeology at the University of Cambridge and will be presenting:Thinking Through Bones: The Viking Age Cemetery of Kopparsvik. 

Paola Gamboa will discuss her experience as a researcher and lecturer in the undergraduate and master¡¯s programs of didactics of French as a foreign or second language at Sorbonne Nouvelle University. This presentation will focus on the complexity of implementing plurilingual teaching practices, necessary for the process of welcoming immigrant minors, in a country like France whose national linguistic policy is monolingual.

Join us for a CIMS lecture with postdoctoral fellow ?zlem G¨¹rakar Skribeland.

Jonas Gahr Sturtzel Lunde, Institute of Theoretical Astrophysics, UiO.

Thomas Nagler is a Professor of Computational Statistics \& Data Science at the Department of Statistics, LMU Munich, and a principal investigator at the Munich Center for Machine Learning (MCML).

Previously, he held positions as an assistant professor at TU Delft and Leiden University, following a PhD in Mathematical Statistics from TU Munich.

His research lies at the intersection of mathematical and computational statistics. His group develops statistical methods, establishes theoretical guarantees, and designs scalable algorithms, which are packaged into user-friendly software. He also regularly collaborates with domain experts to tackle challenges in diverse application areas.