Events

Below is a list of events (schools, conferences, minisymposia/dedicated session at larger events, etc.), that I have participated in organizing over the years.

11	Geilo Winter School 2025: Inverse Problems (main organizer) January 19-24, Geilo, Norway About: The 25th Geilo Winter School focused on Inverse problems, with topics ranging from solving inverse problems with Julia’s SciML, water waves, geosteering, and machine learning. Lecturers: Adrian Kirkeby (Simula), Chris Rackauckas (JuliaHub, PumasAI, MIT), Sergey Alyaev (NORCE), Giovanni Alberti (University of Genoa)
10	Dedicated session: Direct Heat Geothermal Energy: Importance of Forward Modelling and Data Assimilation D. Voskov, Ø. Klemetsdal 85th EAGE Annual Conference & Exhibition, June 2024, Oslo, Norway About: Heating and cooling demands almost 50% of the EU’s total gross energy consumption. A large portion of this energy can be delivered by direct heat from geothermal resources. In this session, we discuss how numerical modeling and data assimilation can help in improving the energy production from direct heat systems.
9	Minisymposium: Predictive Digital Twins T. Kvamsdal, K. Mathisen, Ø. Klemetsdal 9th European Congress on Computational Methods in Applied Sciences and Engineering, 3-7 June 2024, Lisbon, Portugal About: This MS will have a special emphasis on enabling technologies for Digital Twins, where we adopt the following definition of a Digital Twin: A digital twin is defined as a virtual representation of a physical asset, or a process enabled through data and simulators for real-time prediction, optimization, monitoring, control, and decision-making. To enable predictive twins, one may utilize Hybrid Analysis and Modelling (HAM) that combines classical Physic-Based Methods (PBM) accelerated by means of Reduced Order Modelling (ROM) together with Data-Driven Methods (DDM) based on sensor measurement analysed by use of Machine Learning (ML). Pure Data-Driven Methods based on sensor measurement analysed by any means of AI is also welcome. In general, this MS welcome contributions on enabling technologies that can facilitate Predictive Digital Twins. Advanced applications of Predictive Digital Twins are also welcome.
8	Geilo Winter School 2024: Graphs and Applications (co-organizer) January 21-26, Geilo, Norway About: The 24th Geilo Winter School took a dive into the world of graphs and their applications, covering topics from how to best model graphs in Python to spectral theory to graph neural networks.
7	MRST Symposium 2023 (co-chair) Online, September 26-27, 2023 About: The second MRST symposium was held on 26th and 27th September 2023. The symposium had over 190 registered participants and consisted of several talks and poster presentations with contributions from the core development team at SINTEF as well as the wider MRST community.
6	Minisymposium: Practical Simulation of Geothermal Energy Systems Ø. Klemetsdal, O. Andersen SIAM Conference on Mathematical & Computational Issues in the Geosciences (GS23). June 19-22, 2023, Bergen, Norway About: Geothermal energy can become imperative in order to meet the world’s future energy demand. Deep geothermal energy extraction has the potential to provide large amounts of stable and reliable energy with a very low carbon footprint, and the subsurface provides a highly scalable means of buffering imbalance between heating/cooling supply and demand. However, high cost, technological limitations and large uncertainties have so far limited large-scale, global adoption. Key to tackling these challenges is robust, efficient, and accurate simulation technology. Simulation of geothermal energy is a truly multiscale problem: heat is rapidly advected through fractures and high-permeability regions and slowly conducted into the solid rock; high-enthalpy systems exhibit sharp interfaces delineating regions of distinctly different fluid properties; and the subsurface can have extreme and abrupt variations in geological parameters, possibly further amplified by mechanical effects. Moreover, geothermal plants require production facilities that may include boreholes, heat exchangers, heat pumps, and end users, all of which contribute model parameters that need tuning in order to fit observations and operational conditions. This minisymposium focuses on challenges related to practical modeling and simulation of geothermal energy systems. We invite contributions related to all aspects, including modeling, gridding, discretization, linear and nonlinear solution strategies, and optimization.
5	Geilo Winter School 2023: Computational Statistics (co-organizer) January 22-27, Geilo, Norway About: The 23rd Geilo Winter School covered the topic of computational statistics, which is of great importance in a number of modern applications. The lectures ranged from introductions to Monte Carlo methods, MCMC and friends, Bayesian inference and Integrated Nested Laplace Approximation to using Julia for computational statistics and even covered some reinforcement learning.
4	Geilo Winter School 2022: Continuous Optimization (co-organizer) January 24-28, Geilo, Norway About: Continuous optimization is the study of maximizing functions of continuous variables. Such problems are generally intractable without additional conditions and constraints, but for many specific cases, theoretical research has led to the development of very useful algorithms for practical applications. Today, such algorithms constitute the workhorse in a diverse range of applications spanning from robotics over machine learning to economics. Recent successes in the field include progress in compressed sensing and advances in large-scale optimization. In the school of 2022 we looked into a number of exciting topics ranging from continuous optimization basics to topics like shape optimization, PDE-constrained optimization, and the relationship between machine learning and optimization.
3	MRST Symposium 2021 (co-chair) Online, September 14-15, 2021 About: The first MRST Symposium took place online from 14th / 15th September 2021. The event had 169 registered participants and brought together a range of MRST users with many, varying interests with the aim of sharing experiences and inspiring each other in new scientific directions. The symposium consisted of 9 plenary talks from prominent users, panel discussions with the opportunity to meet the developers here at SINTEF, and a poster session featuring 17 different contribution. The event was free to attend.
2	Geilo Winter School 2021: Explainable Algorithms (co-organizer) January 25-29, Geilo, Norway About: The past decade has seen impressive developments in powerful machine learning algorithms. These methods have been most successful when applied to problems where other tools are not readily available, and today frequently guide many decision-making processes. Much recent research focuses on applying these methods in areas where machine learning and statistical methods are not commonly part of the toolbox in order to tackle parts of the problem that are hard to solve by traditional approaches. In these cases, a proper understanding of what the algorithms are in fact telling us is very important. An example is in numerical simulation, where machine learning can be used for parameter estimation, acceleration of linear and nonlinear solvers, or even as proxy models where the governing equations merely serve as physical constraints. On the other hand, numerical tools can also be used to enhance our understanding of applied machine learning algorithms. In the 2021 winter school, we took a deep dive into explainable algorithms, and aimed to understand how an algorithm can be efficient, robust and comprehensible at the same time.
1	Geilo Winter School 2020: Modern Techniques and Algorithms in High-Performance Computing (co-organizer) January 19-24, Geilo, Norway About: Modern multicore and parallel CPU and GPU architectures have made it possible to handle problems that were far out of reach not so long ago. Moreover, there is an increasing interest in quantum computers, which have the potential of opening entirely new avenues of algorithmic research. Exploiting the numerical potential of modern computing platforms requires knowledge and training in high-performance computing (HPC). This winter school looked at important topics related to HPC, including GPU computing, Quantum computing, Automatic differentiation, and Distributed parallelism.