Workshop: AI-based data-driven science
The workshop brought together researchers and IT support staff to let them exchange knowledge, requirements and planned support in applying AI methods in research and teaching.
The workshop had three objectives:
- Serving as a first step in establishing a forum / network of experts in applying AI methods.
- Informing about the current status of the UiO hub-node project “strategisk satsning innen maskinlæring, deep learning og data science for forskning og undervisning ved UiO.” and gathering input from users on prioritising the project’s work for the next 6-12 months.
- Gathering needs/tasks for an NFR-funded national project proposal to support applied machine learning in research and teaching.
We summarised the workshop and its findings in a short report. Please, see several of the presentations linked in the agenda below.
|09:00-09:15||Welcome, logistics, workshop goals [PDF]|
|09:15-10:00||Status of current initiatives to support AI & machine learning|
|10:15-11:45||Session with talks from researchers and lecturers (chair Thomas Röblitz)|
|10:15||Tone Tønjum: AMR use case|
|10:25||Victor Greiff: Learning the immune language of antibodes with machine learning|
|10:35||Valeria Vitelli: AI and machine learning in biostatistical research: example projects and IT requirements [PDF]|
|10:45||Owen Thomas: Computational inference methods for complex statistical models: example projects and IT requirements|
|10:55||Riccardo De Bin: Needs for our research in statistics/data science [PDF]|
|11:05||Ingrid Glad: The DataScience@UiO innovation cluster's data science advisory service, integration with USIT|
|11:15||Ingrid Glad: Needs for the SFI BigInsight|
|11:25||Geir Storvik: Needs in connection to the new master program in data science [PDF]|
|12:45-14:15||Session with talks from researchers and lecturers (chair Andrea Gasparini)|
|12:45||Bamba Dione: Developing a Neural Network Dependency Parser for Wolof [PDF]|
|12:55||Seong-Eun Cho: Identification of Speculations in Relation Extraction [PDF]|
|13:05||Stephan Oepen: Natural Language Processing [PDF]|
|13:15||Jim Tørresen: AI related work at robotics and intelligent systems group @ IFI [PDF]|
|13:25||Tor Endestad: Intracranial EEG data and how we try to make sense of them|
|13:35||James Catmore: Machine learning in particle physics [PDF]|
|13:45||Ana Costa Conrado: Machine learning in the GeoHive hub-node project [PDF]|
|13:55||Stein Kristiansen: Detecting OSA with Machine Learning and Low-Cost Sensors|
|14:30-15:00||Open discussion on next steps [PDF]|