Conference Program

Day 1, June 5th, 2023

08:00-09:00

Registration & Coffee 

09:00-09:15

Welcome by Klas Pettersen

09:15-10:15

Keynote: Anders M. Dale, Professor of Neurosciences, Radiology, Psychiatry, Cognitive Science, and Data Science, UCSD

10:15-10:30

Coffee Break 

10:30-11:30

Track 1 Responsible AI & Representation Learning

11:30-12:30

Lunch

12:30-13:40

Track 2 Medical AI & Chemistry

13:40-13:55

Coffee Break

13:55-14:55

Panel Discussion "NeuroAI"

Panelists: 

  • Solve Sæbø, Professor, The Norwegian University of Life Sciences - Moderator
  • Anders M. Dale, Professor of Neurosciences, Radiology, Psychiatry, Cognitive Science, and Data Science, UCSD
  • Marianne Fyhn, Professor, University of Oslo
  • Hanne Stensola,  Associate Professor, University of Agder
  • Klas Pettersen, CEO, NORA

14:55-15:45

Poster Session

15:45-16:45

Keynote: Jill Walker Rettberg,  Professor, Principal Investigator of the ERC project Machine Vision in Everyday Life, University of Bergen, Co-director Center for Digital Narratives

“AI and humans: A love/hate relationship spanning millennia”

16:45-17:00

Conference information dinner

17:00

End of Conference

18:00

Conference Dinner

Day 2, June 6th, 2023

08:00-09:00

The Ethics of AI Research 

08:30-09:00

Registration & Coffee 

09:00-10:00

Keynote: Arnoldo Frigessi, Professor of Statistics, Department of Biostatistics, University of Oslo

“Pair copula constructions in machine learning”

10:00-10:15

Coffee Break 

10:15-11:15

Track 3 Marine AI & Earth Observation

11:15-12:15

Lunch

12:15-13:05

Track 4 - Miscellaneous

13:05-13:30

Coffee Break

13:30-14:30

Panel discussion - Large Language Models: Reasoning & Bias

  • Jill Walker Rettberg, Professor UiB
  • Per Egil Kummervold, National Library
  • Silje Strandengen;
  • Morten Goodwin, Professor UiA - Moderator

14:30-15:00

Conference Closing 


Tracks

Track 1 Responsible AI & Representation Learning

Time

Title

Author

10:30-11:45

Making scientific data available for AI via semantic interoperability and data documentation frameworks

Francesca Lønstad Bleken, Thomas F. Hagelien, Martin Thomas Horsch and Jesper Friis

10:45-11:00

Semantically consistent self-supervised representation learning on point clouds

Ahmed Mohammed, Asbjørn Berge and Marianne Bakken

11:00-11:15

Discriminative Multimodal Learning via Conditional Priors in Generative Models

Rogelio A Mancisidor, Michael Kampffmeyer, Kjersti Aas and Robert Jenssen

11:15-11:30

European recommendations for explainable-AI-ready data in materials modelling and characterization

Martin Thomas Horsch, Francesca L. Bleken, Jesper Friis and Heinz A. Preisig

Track Chair: Ana Ozaki, Associate Professor, UiB 

Track 2 Medical AI & Chemistry

Time

Title

Author

12:30-12:45

Digital pathology in neuro-oncology: deep learning-based prediction of clinically actionable genomic alterations from histopathological images

Birgit Kriener

12:45-13:00

Deep Graph Learning Approaches to Chemistry

David Balcells

13:00-13:15

Automated Cardiac Elasticity Modeling with Evolutionary Energy Functions

Kristin Ludwicki, Sophia Ohnemus, Leto Riebel, Molly Maleckar and Gabriel Balaban

13:15-13:30

A two-stage mammography classification model using explainable-AI for ROI detection

Fredrik Andreas Dahl, Olav Brautaset, Marit Holden, Line Eikvil and Solveig Hofvind

13:30-13:40

Startup Presentation

Per Niklas Benzler Waaler, Machine Learning Engineer, Medsensio

Track Chair: Morten Goodwin, Professor, UiA

Track 3: Marine AI & Earth Observation

Time

Title

Author

10:15-10:30

ATELIER-EO:  An AutoML framework for Earth Observation

David Völgyes, Martijn Vermeer, Daniele Fantin, Jacob Alexander Hay and Tord Kriznik Sørensen

10:30-10:45

SeaBee - Norwegian Infrastructure for Drone-based Research, Mapping and Monitoring in the Coastal Zone

Arnt-Børre Salberg, Yi Liu, Are Charles Jensen, Jarle Hamar Reksten, Joseph Garrett, James Edward Sample, Hege Gundersen and Kasper Hancke

10:45-11:00

Mapping marine macroalgae using UAV hyperspectral imaging and machine learning

Martin Skjelvareid, Eli Rinde, Katalin Blix, Kasper Hancke and Galice G. Hoarau

11:00-11:15

MViST: A Multi-label Vision Spatiotemporal Transformer for Underwater Ship Inspection

Md Abulkalam Azad, Ahmed Mohammed, Maryna Waszak, Brian Elvesæter and Martin Ludvigsen

Track Chair: Katalin Blix, Research Fellow, UiT

Track 4: Miscellaneous

Time

Title

Author

12:15-12:30

An Efficient Machine Learning Approach for Building Segmentation Using Aerial Images and LiDAR Data

Erik Finnesand, Muhammad Sulaiman and Mina Farmanbar

12:30-12:45

GPT-4's Unconventional Route to Pi: A Novel Algorithm for Calculating Pi Using the Space-Filling Hilbert Curve and Monte Carlo-Inspired Sampling

Kristian Muri Knausgård

12:45-12:55

Startup Presentation - Bineric

"Data labelling using large language models and an army of data labellers"

Umair Mehmood Imam, CEO & Co-founder 

12:55-13:05

Strategic Partner Presentation

"Shipment Captioning - Predicting Production Lifecycle For Shipments At Posten"

Simon Simonsson, Data Scientist, Posten

Track Chair: Mina Farmanbar, Associate Professor, UiS 

Published Jan. 8, 2024 10:26 AM - Last modified Nov. 13, 2024 11:44 AM