Call for Papers

Background

The vast improvements in computational resources, both from a hardware as well as software perspective, have led to significant advances in research on complex, intelligent systems. Indeed, computational methods have become a fundamental pillar of research, rendering the scientific method more efficient and facilitating collaboration across disciplines. Experimental and theoretical researchers can effectively work with computational experts since computational models have increasingly gained in detail, accuracy and realism. Along those lines, systems such as the brain, the immune system or specific organs can be captured based on experimental data from different spatial and temporal scales. Moreover, state-of-the-art AI models can be employed using large-scale data-sets, which is further facilitated by the increasing availability of public databases and practicality for collaboration across labs.

This symposium will allow researchers who work in computationally-assisted research involving intelligent systems to show their work, exchange ideas and ideally foster further collaboration.

Goal/Rationale

The goal of this symposium topic is to present, discuss and exchange ideas on computational approaches that go beyond classification and/or regression performance. Given the crucial point of explainability and interpretability in complex systems modeling, we would like to study approaches that address current flaws in black-box AI techniques. We would like to achieve a general meeting where an open discussion of current challenges and existing gaps is encouraged.

A focus of the meeting will be on the presentation of existing platforms and software that facilitate explainable model generation, comparison and testing. Ideally, these should be available as open-source, and support reproducibility, extendibility and collaboration. Ultimately, we would like to see this meeting as a stepping stone for wider, international collaboration and grant proposals.

Scope and Information for Participants

The scope of this symposium includes any computational or mathematical approaches and methods that are applicable to questions involving intelligent systems. Such questions can focus on fundamental problems or causal processes that are relevant to a given topic. For instance, in the case of neuroscience, this could be on the architectural design or generative modelling. The application can be with regards to applications or fundamental science, to better understand the underlying functional factors, or derive explainable predictions.

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 r.bauer@surrey.ac.uk. More information will be made available in the near future via the following link: https://www.combynelab.com/home/news/comosis2026