2026-08-13 –, Room 1
Computational Science and Engineering (CSE) integrates engineering, applied mathematics, and computer science to enable model-based design, knowledge generation, and decision support. While CSE has become a key enabler of sustainable products and operations, sustainability is still often treated as an afterthought in computational method development. This talk reflects on sustainability as a core design principle for CSE—one that aligns naturally with scientific relevance, long-term usability, and enduring research value. Drawing on representative examples, we present a holistic perspective spanning resource consumption, digital infrastructure, and organizational practices. We examine how these aspects interact in modern computational research and conclude with directions for impact through sustainable CSE.
I am an enthusiastic Computational Science and Engineering researcher interested in developing computational methods to study and predict complex engineering systems and environmental processes, such as geohazards. My specific interests include data-integrated simulation models for shallow flow, contact, and phase-change processes, as well as surrogate models for real-time prediction, applied uncertainty management, and Bayesian model selection. I am an open science and FAIR data advocate, passionate about modern research software engineering, holistic computational workflow management, and ensuring 'analysis-readiness' of data to foster sustainability in CSE and to maximize our knowledge return from computational investments. I am similarly passionate about promoting a diverse working culture, convinced that bringing together a multitude of perspectives not only enriches innovation but also paves the way for broadly accepted scientific solutions.