Computational Science - ICCS 2025 Workshops
Description
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.
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Content
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.
