Computational Science - ICCS 2025 Workshops

The 6-volume set constitutes the workshop proceedings of the 25th International Conference on Computational Science, ICCS 2025, which took place in Singapore, Singapore, during July 7 9, 2025.

The 137 full papers and 32 short papers presented in these proceedings were carefully reviewed and selected from 322 submissions. The papers are organized in the following topical sections:

Volume I:

Advances in high-performance computational earth sciences: numerical methods, frameworks & applications; artificial intelligence approaches for network analysis; artificial intelligence and high-performance computing for advanced simulations; and biomedical and bioinformatics challenges for computer science.

Volume II:

Computational health; computational modeling and artificial intelligence for social systems; and computational optimization, modelling and simulation.

Volume III:

Computational science and AI for addressing complex and dynamic societal challenges equitably; computer graphics, image processing and artificial intelligence; computing and data science for materials discovery and design; and large language models and intelligent decision-making within the digital economy.

Volume IV:

Machine learning and data assimilation for dynamical systems; and multi-criteria decision-making: methods, applications, and innovations.

Volume V:

(Credible) Multiscale modelling and simulation; numerical algorithms and computer arithmetic for computational science; quantum computing; retrieval-augmented generation; and simulations of flow and transport: modeling, algorithms and computation.

Volume VI:

Smart systems: bringing together computer vision, sensor networks and artificial intelligence; solving problems with uncertainty; and teaching computational science.

Computational Science and AI for Addressing Complex and Dynamic Societal Challenges Equitably. - Temporal-aware Social Bot Detection with Graph Contrastive Learning. - Bias or Justice? Analyzing LLM Sentencing Variability in Theft Indictments Across Gender, Ethnicity, and Education Factors. - Minimally Supervised Hierarchical Domain Intent Learning for CRS. - Computer Graphics, Image Processing and Artificial Intelligence. - A New Technique for Enhanced Monochrome Visualization of Non-Visual Data. - SupResDiffGAN a New Approach for the Super-Resolution Task. - Optimized Custom CNN for Real-Time Tomato Leaf Disease Detection. - ConvNeXt Fine-Tuning for Accurate Classification of 300 Cooking Ingredients. - Universal Deepfake Detection Across Various Image Generators Based on Data from Diffusion Models. - Hybrid Procedural Level Generation Using Wave Function Collapse and Genetic Algorithms. - Enhancing AI Face Realism: Cost-Efficient Quality Improvement in Distilled Diffusion Models with a Fully Synthetic Dataset. - Deep Learning Classification of Blackcurrant Genotypes by Ploidy Levels on Stomata Microscopic Images. - Advanced Graph-Based Object Segmentation in Large-Scale 3D Point Clouds. - BVH Trees of Many Dynamic Lights for Real-Time Ray Tracing. - Transferability of UNet-Based Downscaling Model for High-Resolution Temperature Data Across Diverse Regions. - Bayesianization of ML models in Forecasting Small Da-ta Sequences with Missing Values. - Enhancing Medical Image Analysis with Multi-Task Learning Using Visual Transformers. - Bat Algorithm for Automatic Chaos Control Method Driven by Multiplicative Pulses to the System Variables on the Logistic Map. - Computing and Data Science for Materials Discovery and Design. - Domain Specific Language for Materials Modeling. - Structural Response of Bijels Stabilized by Ellipsoidal Magnetic Particles. - Data-Driven Prediction of Glass Transition Temperature Using Molecular Structural Features. - Exploration and Learning Algorithms Used for Predicting Casting Properties. - Physics Informed Neural Networks for a Wigner-Fokker-Planck Model of Open Quantum Systems. - Large Language Models and Intelligent Decision-Making within the Digital Economy. - Dataset Distillation via Kantorovich-Rubinstein Dual of Wasserstein Distance. - Predicting Stock Prices with ChatGPT-annotated Reddit Sentiment: Hype or Reality? - AIOps for Reliability: Evaluating Large Language Models for Automated Root Cause Analysis in Chaos Engineering.