Computational Modeling of Complex System Dynamics
June 23rd, 2023 (GMT+1)
Surrey Space Center, University of Surrey
Roman received his Bachelor's and Master's Degree in Computational Science and Engineering from ETH Zuerich, Switzerland. Afterwards, he did his doctoral studies at the Institute for Neuroinformatics (INI) at ETH Zürich and University of Zürich, working on simulations of cortical development. He then joined Newcastle University in September 2013 as a postdoctoral research associate and afterwards started his MRC fellowship project in September 2016 as an independent principal investigator. In June 2018 he took up an EPSRC UKRI Innovation Fellowship at the School of Computing and a joint affiliation with the Institute of Genetic Medicine, both at Newcastle University. In August 2020 he then became a lecturer at the Department of Computer Science, University of Surrey.
Background:
Computational simulation has become a fundamental pillar of the scientific method. Among other factors, the advances in computational resources in both hardware as well as software, have accelerated the adoption of computational methods to formulate models, establish hypotheses and generate experimentally verifiable predictions. In particular, complex systems that comprise large numbers of interacting elements are well-suited for computational approaches due to their often counter-intuitive behavior and the existence of large amounts of data from different modalities. Among other techniques, agent-based simulation has gained significant attention in recent years. This workshop will focus on research based on different computational approaches to better understand complex systems across a broad range of domains, including for instance neuroscience, oncology and biology.
Goal/Rationale:
Given the broad range of computational approaches in complex systems, we will look into different use cases and establish commonalities as well as differences between them. In these use cases, significant weight will be given to showcase the validation with real-world data, and explore the demands that the research community faces.
Specific focus will be made to showcase existing software, ideally of the open-source type. Moreover, the current overlap in employed techniques will be discussed and existing gaps as well as challenges will be explored, particularly with regards to the development and maintenance of relevant research software. Ultimately, the aim is to identify opportunities to advance and accelerate computational research on complex systems.
Scope and Information for participants
The scope of this research topic is broad and encompasses work where computational methods are employed to model and ultimately better understand biological systems. These biological systems can have for instance medical, technological, environmental or ecological relevance. Hence, specific themes could be for instance computational models of neural systems (e.g., artificial neural networks, neurodevelopmental simulations), cancer simulations or work on bacterial communities and bacterial communication (e.g., biofilms).
We expect the participants to consider relevance for different research communities, and formulate the research in a language that can be communicated within interdisciplinary settings. If potential participants are unsure about the suitability of their research topic/approach, they are encouraged to contact the organizers via compbiomodelling2023@gmail.com. More information will be made available in the near future on https://sites.google.com/view/cbm2023.
Stag Hill, University Campus, Guildford GU2 7XH, United Kingdom
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