Call for Symposia Proposals for NTCI 2025
The International Conference on New Trends in Computational Intelligence (NTCI) has been held for 6 sessions since 2016, with over 5,000 participants in total. It serves as a pivotal international conference in the field of computational intelligence, garnering significant attention from researchers. A total of 53 top experts, including academicians, IEEE Fellows, and journal editors in the field of computational intelligence from around the globe, have delivered 78 invited reports. Since 2023, the conference has achieved stable EI indexing, with more than 200 academic papers included to date. It provides a platform for researchers, practitioners, and scholars in computational intelligence to focus on discussing new fields, designs, and applications, having become an influential international platform in the field.
The 7th International Conference on New Trends in Computational Intelligence (NTCI 2025) will take place in Jinan, China from October 17 to 19, 2025. To ensure the conference's high-quality execution, encourage active participation from researchers and engineering professionals, and comprehensively showcase new advancements and research achievements in computational intelligence and related fields at home and abroad, the conference now invites proposals for NTCI 2025 symposia from the entire industry. Relevant units and experts are cordially invited to support and undertake the symposia!
I. Overview of NTCI 2025 Symposia
(1) Symposia Theme Directions
Symposia themes can be planned around directions such as models and algorithms (e.g., machine learning, multi-objective optimization, image processing, quantum machine learning, etc.), and theories and applications (e.g., space information, smart healthcare, IoT engineering, material genome engineering, network information security, intelligent oil & gas field development, intelligent marine engineering, intelligent operations research & optimization, etc.).
(2) Symposia Forms
NTCI 2025 symposia support diverse formats, including but not limited to special report sessions, round-table dialogues, group discussions, and interactive seminars. All symposia will be held offline.
(3) Symposia Schedule
NTCI 2025 will be held from October 17 to 19, 2025, with symposia conducted concurrently with the main conference.
(4) Symposia Venue
Offline venues for all symposia will be the same as the main conference venue in Jinan.
II. Undertaking Requirements
(1) Applicant units/individuals must have relevant work experience, strong resource mobilization and conference organization capabilities, and actively cooperate with the conference's overall arrangements.
(2) Each symposia may set its own theme and appoint 1-3 symposium chairs, who should possess influence and prestige in the relevant field.
(3) Each symposia must solicit at least 5 contributions (long abstracts or papers, with at least 4 being papers), and chairs may invite one Keynote report.
III. Organizing Committee Support
The Organizing Committee will provide venue services, financial support, on-site facilities, and other resources, and recommend outstanding papers to SCI journals.
IV. Additional Notes
(1) For unmentioned matters, please consult the Organizing Committee.
(2) The Organizing Committee reserves the right to interpret these symposia application guidelines.
(3) For specific matters of symposia application, please consult the organizing committee in advance (Ms. Wang: +86-13061345702; Ms. Yang: +86-15053818666).
Symposia for NTCI 2025
I. NTCI 2025 Symposium on Advances in Neural Networks and Machine Learning
Symposium Overview:This session brings together cutting-edge research and innovative applications in the field of neural networks and machine learning. Experts will present their latest findings on deep learning architectures, optimization techniques, and real-world implementations across various domains, including computer vision, natural language processing, signal processing and reinforcement learning. Attendees will gain insights into emerging trends, challenges, and future directions in this rapidly evolving field.
Topics of Interest Include (but not limited to):
1.Novel neural network architectures (e.g., transformers, GANs, spiking neural networks)
2.Scalable and efficient training algorithms
3.Explainability and interpretability in deep learning
4.Federated learning and privacy-preserving ML
5.Applications in healthcare, robotics, finance, and more
II.NTCI 2025 Symposium on Granular Computing
Symposium Overview: Granular Computing (GrC) is a computational paradigm based on information granularity, aimed at simplifying the problem-solving process through abstraction and hierarchical processing of complex systems. Granular Computing focuses not only on the representation and processing of information but also emphasizes knowledge discovery and reasoning capabilities in uncertain and fuzzy environments. Its core theories include fuzzy sets, rough sets, quotient space, cloud models, and tri-branch decision theory, which provide a solid foundation for handling complex data and building intelligent systems. This conference aims to gather the latest research findings in the field of Granular Computing, promoting its application and development in knowledge discovery, intelligent decision-making, and big data analysis. We warmly invite researchers from academia and industry to submit high-quality papers and join us in exploring the cutting-edge theories, methods, and applications of Granular Computing.
Topics of Interest Include (but not limited to):
1.Theoretical foundations and methodologies of Granular Computing
2.Applications and integration of fuzzy sets and rough sets in Granular Computing
3.Quotient space theory and its application in multi-scale data analysis
4.Cloud models in pattern recognition and data mining
5.Tri-branch decision theory in intelligent decision-making systems
6.Integration of Granular Computing with machine learning and deep learning
7.Granular Computing in big data analysis and knowledge discovery
8.Granular Computing and the challenges of interpretable artificial intelligence and trusted systems
9.Applications of Granular Computing in complex system modeling and optimization
10.Integration of Granular Computing with brain-computer interfaces and smart environments
Ⅲ.NTCI 2025 Symposium on Advances in Intelligent Oil and Gas Exploration and Development
Symposium Overview: Against the background of global energy transition and increasingly complex exploration and development scenarios, artificial intelligence technologies are accelerating the intelligent transformation of the oil and gas industry. This sub-symposium, themed “Deep Integration of Artificial Intelligence with Oil and Gas Exploration and Development,” will focus on cutting-edge applications of deep learning, multimodal data fusion, large-scale models, and digital twin technologies in geophysical exploration, reservoir characterization and modeling, and fracture reservoir prediction. Experts will jointly analyze the latest developments, discuss key technical challenges, and envision future innovation directions in this field.
Topics of Interest Include (but not limited to):
1.Intelligent prediction of lithology and sedimentary facies
2.Intelligent characterization of complex fractured reservoirs and 3D geological modeling
3.Intelligent technologies for 3D geological modeling and sweet spot prediction in oil and gas reservoirs
4.Theories and methods for explainable AI models in oil and gas applications
5.Construction and application of large-scale models in oil and gas exploration and development
6.Innovative practices of digital twin technologies in smart oilfield development.
Ⅳ.NTCI 2025 Symposium on Data-Driven Learning and Optimization
Symposium Overview: Data-driven learning, as a core driver of intelligent system development, is profoundly transforming fields such as manufacturing, finance, and biomedicine. However, with the continuous growth of data volume and model complexity, issues such as computational cost, optimization efficiency, model adaptability, and security control have become critical bottlenecks. Achieving efficient, scalable, and controllable optimization has thus emerged as a key challenge. This forum invites high-quality submissions focusing on theoretical advances, algorithmic innovations, and practical applications in data-driven learning and optimization. We welcome interdisciplinary research contributions, including efficient optimization frameworks for large-scale data and complex systems, novel approaches integrating dynamic optimization, transfer learning, automated machine learning, and deep neural networks, as well as explorations addressing frontier challenges such as adaptive optimization in open environments, cross-domain knowledge transfer, and multimodal data fusion.
Topics of Interest Include (but not limited to):
1.Theoretical analysis and optimization of deep learning models
2.Data-driven strategy optimization in reinforcement learning
3.Optimization strategies for multimodal data fusion
4.Data-driven meta-heuristic algorithm optimization
5.Distributed data-driven optimization algorithms
6.Optimization of data-driven learning in biomedical and healthcare applications
7.Data-driven risk prediction and optimization in financial technology
8.Data-driven production optimization in intelligent manufacturing
9.Adaptive data preprocessing methods based on data-driven learning
10.Optimization of personalized learning paths in education through data-driven approaches
11.Optimization of data-driven learning in medical image diagnostics
Ⅴ: NTCI 2025 Symposium on Intelligent Computing and Pattern Recognition
Session Overview: With the rapid advancement of artificial intelligence technology, intelligent computing serves as a core engine for efficiently processing complex data and deeply integrates with pattern recognition—a key application field. This synergy is reshaping numerous sectors such as healthcare, transportation, finance, and industry, continuously transforming the paradigms of scientific research and industrial innovation. We cordially invite experts and scholars in the field to discuss the latest research advances in intelligent computing and pattern recognition, exchange academic ideas, and promote interdisciplinary collaboration as well as industry-academia-research integration.
Topics of interest include (but are not limited to):
1.Intelligent optimization algorithms and applications
2.Theoretical models and frameworks of computational intelligence
3.Hybrid intelligent systems and ensemble learning
4.Big data-driven intelligent computing
5.High-performance intelligent computing and distributed algorithms
6.Complex system modeling and simulation
7.Computer vision and image/video understanding
8.Speech recognition and natural language processing
9.Feature extraction, selection, and dimensionality reduction techniques
10.Multimodal information fusion and cross-modal learning
11.Generative AI and large model technology with applications
12.AI and IoT intelligent perception
13.Intelligent unmanned systems, autonomous driving, and robotics
14.Pattern recognition and intelligent decision-making in smart cities
15.Industrial intelligence and defect detection
16.Bioinformatics and health big data analysis
Ⅵ：NTCI 2025 Symposium on Intelligent Information Processing and Analysis for Complex Scenarios
Session Overview: Intelligent information processing and analysis for complex scenarios serves as the core engine driving artificial intelligence from ideal environments to real-world applications, bringing about paradigm shifts in critical domains such as marine exploration, climate science, and smart cities. However, real-world data often exhibits complex characteristics, including high dimensionality, strong dynamics, heterogeneity, and even quality degradation. The resulting challenges—such as algorithmic scalability, model generalization, result interpretability, and decision reliability—are becoming key bottlenecks that constrain technological advancement. Therefore, designing advanced computational theories and methods to efficiently extract robust features, accurately predict dynamic trends, and ultimately empower intelligent decision-making from complex data has emerged as a core scientific challenge that urgently needs to be addressed. This special session focuses on this theme, inviting high-quality submissions to jointly explore the theoretical progress, algorithmic innovations, and practical applications of intelligent information processing for complex scenarios. We look forward to novel approaches that integrate feature learning (e.g., NMF), dynamic systems modeling (e.g., spatiotemporal forecasting), and signal restoration (e.g., underwater enhancement), as well as explorations into frontier directions such as multimodal fusion, cross-domain adaptation, and human-computer collaboration in open environments.
Topics of interest include (but are not limited to):
1.Theories and models for Deep/Graph-regularized Non-negative Matrix Factorization
2.Scalable NMF, Tensor Decomposition, and their optimization algorithms for massive data
3.Theoretical analysis and convergence studies of Non-negative Matrix Factorization
4.Deep learning architectures for spatiotemporal sequence forecasting
5.Multimodal information fusion and prediction for complex dynamic systems
6.Physics-based modeling and data-driven methods for signal restoration
7.Applications of Physics-Informed Neural Networks in image and sequence analysis
8.Underwater image enhancement methods based on Generative Adversarial Networks
9.Real-time color correction and dehazing algorithms for underwater images
10.Unified analysis frameworks combining NMF and deep learning
Ⅶ: NTCI 2025 Symposium on Optimization Scheduling and Decision-Making Session
Session Overview: With the accelerated digital transformation of the global industry, optimization scheduling and decision-making, as the core technical support for improving resource allocation efficiency, reducing operating costs, and ensuring the stable operation of systems, have been deeply integrated into many key fields such as manufacturing, logistics, energy, and services. It provides scientific and effective solutions for solving problems such as resource conflicts, task allocation, and path planning in complex systems, and continuously promotes the development of various industries towards high efficiency, intelligence, and refinement. We sincerely invite experts, scholars, and enterprise representatives in this field to gather together to discuss the cutting-edge research results in the field of optimization scheduling and decision-making, share practical application experience, promote academic exchanges and in-depth integration of industry, university, and research, and help the innovative development of the industry.
Topics of interest include (but are not limited to):
1.Production Scheduling Optimization and Intelligent Manufacturing Collaboration
2.Logistics Network Planning and Transportation Route Optimization
3.Energy System Scheduling and Supply-Demand Balance Optimization
4.Service Resource Allocation and Queuing System Optimization
5.Supply Chain Collaborative Scheduling and Inventory Optimization
6.Project Schedule Planning and Resource Allocation Optimization
7.Multi-Objective Optimization Decision-Making Models and Algorithms
8.Robust Scheduling and Decision-Making in Uncertain Environments
9.Application of Intelligent Algorithms (such as Genetic Algorithms, Particle Swarm Optimization, etc.) in Scheduling
10.Big Data and Artificial Intelligence-Driven Scheduling Decision Support Systems
11.Emergency Resource Scheduling and Disaster Rescue Decision Optimization
12.Urban Traffic Signal Scheduling and Traffic Flow Optimization
13.Dynamic Scheduling Strategies in Flexible Manufacturing Systems
14.Medical Resource Scheduling and Medical Treatment Process Optimization
15.Financial Portfolio Optimization and Risk Decision-Making
16.Agricultural Production Scheduling and Resource Allocation Optimization
Ⅷ: NTCI 2025 Symposium on Special Session on Trustworthy and Explainable Intelligent Reasoning: Theory and Applications
Session Overview: Trustworthy and explainable intelligent reasoning is essential for achieving transparent, verifiable, and controllable decision-making, which directly affects the deployment of AI models in high-risk and complex scenarios as well as public trust in their outcomes. It has demonstrated wide-ranging applications in areas such as medical diagnosis and treatment planning, financial risk control and auditing, autonomous driving and robotic decision-making, materials genome engineering, and cybersecurity. This special session focuses on the theoretical foundations, optimization methods, and practical applications of trustworthy and explainable intelligent reasoning. We welcome contributions in, but not limited to, the following areas: symbolic knowledge representation and logical reasoning, fuzzy theory and algorithms, disentangled representation learning, causal reasoning, feature extraction and fusion, uncertainty quantification, surrogate modeling, and optimization.
Topics of interest include (but are not limited to):
1. Trustworthy and Reliable Reasoning Models
2. Conditional Probability Density Estimation Modeling
3. Disentangled Representation Learning
4. Surrogate Optimization Models
5. Fuzzy Theory and Methods
6. Fractional Fourier and Ritz Transforms
7. Feature Extraction, Fusion, and Knowledge Graph Construction
8. Image Enhancement and Reconstruction Methods
9. Trustworthy and Reliable Models in Smart Healthcare
10. Trustworthy and Reliable Models in Smart Construction Materials
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