Topics

Artificial Intelligence & AI algorithms

The scope of the journal includes but is not limited to the following research topics: Multi-agent systems, automated reasoning, constraint processing and search, knowledge representation, machine learning, natural language, robotics and vision, and uncertainty in AI, cognition and AI, automated reasoning and inference, case-based reasoning, commonsense reasoning, computer vision, constraint processing, ethical AI, heuristic search, human interfaces, intelligent robotics, machine learning, multi-agent systems, natural language processing, planning and action, and reasoning under uncertainty.

Computer networks and communication

Natural language processing (NLP)

We welcome manuscripts that explore, but are not limited to, the following areas: Text and speech processing, speech recognition, optical character recognition (OCR), speech segmentation, text-to-speech, word segmentation, natural-language understanding, and natural-language generation, development and application of trustworthy artificial intelligence to analyze, process, or model human language across various multimodal contexts, domains, and intelligent systems, including hybrid artificial intelligence, human artificial intelligence interaction and social system, neural networks, statistical NLP, neural NLP, statistical methods, morphological analysis, syntactic analysis, lexical semantics, relational semantics, higher-level NLP applications, machine translation, natural-language understanding, natural-language generation, natural language processing for recommender systems, plagiarism detection using natural language processing techniques, text simplification, accessibility, and readability, neurocomputational models of language processing, explainable AI in natural language processing, natural language processing in bibliometrics, emotion processing: text and multi-modal data, automatic stance detection, multimodal communication and multimodal computing, text complexity and simplification, information extraction for health documents, techniques and tools in modern machine translation, neural computing in medical informatics, perspectives for natural language processing between ai, linguistics and cognitive science, bias, subjectivity and perspectives in natural language processing.

Explainable artificial intelligence (XAI)

Robotics and automation

The scope of the journal includes but is not limited to the following research topics: Intelligent Control and Applications for Robotics; Industrial Robotics; Automation; Robotic devices and systems; Design and Control; Optimal design of systems for material processing; Real-time algorithms for measurement, prediction, and control; Intelligent transportation systems; Computer-aided Manufacturing; Biocybernetics; Digital Electronics and Microprocessors; Robot Manipulators; Air Traffic And Management Systems; Signal Processing; Medical Robotics; Robot Motion Planning; Computer Integrated Manufacturing System; Micro-Robotics; Bio-Cybernetics; Signal Processing; Robot Motion Planning; Computational Geometry; Computer Aided Manufacturing; Digital Electronics and Micro-Processors; Mechatronics; Robot-Aided Rehabilitation and Assistance; Advances in Robot Motion and Control; Design, Optimization and Performance Analysis of Soft Robots; Human-Robot Collaboration in Industry; Advances in Unmanned Aerial Vehicle (UAV) System; Biorobotics and Bionic Systems; Recent Advances in Autonomous Systems and Robotics; Human-Robot Interaction; Advances in Mechatronic and Robotic Systems; Adaptive Dynamic Programming and Control Application in Intelligent Systems; Swarm Robotics; Advances in Robot Path Planning; Augmented and Mixed Reality Based Assistive Technologies in Social Robots; Robotic Systems for Inspections and Surveillance of Industrial Infrastructure; Advanced Pattern Recognition & Computer Vision; Application of Robots in Medical Diagnosis and Treatment; Bio-Inspired Robots for Medical Applications; Trajectory Analysis, Positioning and Control of Mobile Robots; Collaborative Robotics; Intelligent Robots and Precision Machining; Statistical Signal Processing; Intelligent and Sustainable Machinery; Smart Wearable and Interactive Mechatronic Systems; Underwater Robot; Computer Science in Mobile Robots; Future Autonomous Drones

Imbalanced learning

The scope of the journal includes but is not limited to the following research topics: Imbalanced Big Data; Applications in imbalanced domains; data-partition; Geometric-SMOTE; deep learning; intelligent data analysis; pattern recognition; data mining; cost-sensitive learning; Class imbalance; Imbalanced classification; imbalanced classification framework; Theoretical/experimental reviews of classic and recent approaches in imbalanced classification; unbalanced learning; data preprocessing; data mining; Class-Imbalanced Datasets; Classification, ordinal classification; imbalanced data streams; Imbalanced time series and spatio-temporal forecasting; Imbalanced regression; Graph classification with imbalanced data; One-Class Learning; New approaches to data pre-processing; Post-processing approaches; Feature Selection and Transformation; Evaluation Metrics and Methodologies; Deep Learning

AI-driven automation and robotics

Predictive modeling and forecasting

Software engineering and development

Reinforcement learning for real life

The scope of the journal includes but is not limited to the following research topics: Reinforcement Learning in robotics manipulation; Real-Life Applications of Reinforcement Learning; Applications in self-driving cars; Industry automation with Reinforcement Learning; Reinforcement Learning applications in trading and finance; Reinforcement Learning in NLP (Natural Language Processing); Reinforcement Learning applications in healthcare; Reinforcement Learning applications in engineering; Reinforcement Learning in gaming; Reinforcement Learning applications in marketing and advertising; Supervised Learning; reinforcement learning algorithms

Quantum machine learning

AI and ML tools and platforms

Deep learning theories and models

The scope of the journal includes but is not limited to the following research topics: Deep learning technologies; Applications of deep learning in software; Applications of deep learning in hardware; Caption generation; Cognitive architectures; Intelligent agents; Narrative intelligence Visual reasoning; Ambient intelligence; Autonomic computing; Computer games; Image processing; Information retrieval and reuse; multimodal deep learning; Combining multiple sources in deep learning; Combining multiple deep learning models; Multimodal deep metric learning; Transfer learning in multimodal deep learning; Hierarchical deep learning models for information fusion; Cross modality learning; Joint deep feature learning; Big Data Analytics

Data science & Big data analytics

The scope of the journal includes but is not limited to the following research topics: Secure federated learning with real-world applications, Big data analytics and its impact on marketing strategy, Impact of big data on business decision-making, Implementing big data to understand consumer behaviour, Applications of big data to predict future demand and forecasting, The importance of data exploration over data analysis, Data science and software engineering, Machine Learning Foundations for Data Science, Auto-ML, Information fusion from disparate sources, Feature engineering, embedding, mining and representation, Learning from network and graph data, Learning from data with domain knowledge, Reinforcement learning, Non-IID learning, nonstationary, coupled and entangled learning, Heterogeneous, mixed, multimodal, multi-view and multi-distributional learning, Online, streaming, dynamic and real-time learning, Causality and learning causal models, Multi-instance, multi-label, multi-class and multi-target learning, Semi-supervised and weakly supervised learning, Representation learning of complex interactions, couplings, relations, Deep learning theories and models, Evaluation of data science systems, Open domain/set learning, Emerging Impactful Machine Learning Applications, Data preprocessing, manipulation and augmentation, Autonomous learning and optimization systems, Digital, social, economic and financial (finance, FinTech, blockchains and cryptocurrencies) analytics, Graph and network embedding and mining, Machine learning for recommender systems, marketing, online and e-commerce, Augmented reality, computer vision and image processing, Risk, compliance, regulation, anomaly, debt, failure and crisis, Cybersecurity and information disorder, misinformation/fake detection, Human-centered and domain-driven data science and learning, Privacy, ethics, transparency, accountability, responsibility, trust, reproducibility and retractability, Fairness, explainability and algorithm bias, Green and energy-efficient, scalable, cloud/distributed and parallel analytics and infrastructures, IoT, smart city, smart home, telecommunications, 5G and mobile data science and learning, Government and enterprise data science, Transportation, manufacturing, procurement, and Industry 4.0, Energy, smart grids and renewable energies, Agricultural, environmental and spatio-temporal analytics and climate change.

Data preprocessing and cleaning

Data privacy and security

AI and ML in the internet of things (IoT)

Real-world AI and data science applications

Data warehousing and business intelligence

Computer architecture and hardware design

Machine learning foundations for data science

The scope of the journal includes but is not limited to the following research topics: Explainable machine learning; Interpretable machine learning; Model interpretability; Model-agnostic techniques; Internet of Things (IoT) systems; Rare event prediction; Extreme event prediction; Feature selection; Interpretability; Explainable AI decision support systems; Intelligent transportation systems

AI in speech recognition for healthcare records

Explainable AI in finance: Risk assessment models

Human emotion recognition with machine learning

Machine learning for cybersecurity threat detection

Emerging Impactful Machine Learning Applications

The scope of the journal includes but is not limited to the following research topics: The applications of machine learning in radiotherapy, chemotherapy, endoscopic images, laryngoscopic images, MRI, CT imaging; Genomic sequence determinations and analysis of gene expression patterns; Processing and analysis of biomedical signals and images; Modifying living organisms according to human purposes; Improving cell and tissue culture technologies; Development of deep learning architectures in analysis of biomedical data; Validation, analysis, and learning of data representation for medical imaging diagnosis; Theoretical or methodological developments in machine learning for personalized medicine; Acute treatments or diagnoses for specific clinical domains; natural language applications for society; healthcare management and modelling; hospitality and tourism; financial analysis and business; Advanced uncertainty quantification using machine learning; Explainable AI for geosciences; Advanced analytics for efficiency and automation in petroleum and/or geothermal operations; Machine learning approaches or workflows to improve and optimize data acquisition; Physics-informed machine learning for oil and gas and geothermal systems; Machine learning to discover and exploit geothermal resources

Artificial Intelligence (AI) Ethics and Social Implications

We welcome manuscripts that explore, but are not limited to, the following areas: Robot ethics, Machine ethics, Ethics principles of artificial intelligence, Transparency, accountability, and open source, Bias and discrimination in AI, Privacy and security issues in AI, The impact of AI on employment and the job market, Responsibility and accountability in AI decision-making, Power imbalances in AI development and deployment, Transparency in AI systems, Fairness in AI development and deployment, Algorithmic Decision-Making, Data Governance, Social and Cultural Values, Public trust and confidence in AI systems, Ethical considerations in AI design and development, Social and cultural implications of AI, The regulation of AI and emerging technologies, The integration of human values into AI systems, The role of AI in shaping society and the future of work, The responsibility of AI stakeholders (developers, businesses, governments, and individuals) in shaping AI ethics and social implications.

Quantum machine learning: Algorithms and applications

AI and ML in healthcare, finance, education, and industry

Deep Learning Applications in Natural Language Processing

Machine learning for healthcare, finance, and other domains

We welcome manuscripts that explore, but are not limited to, the following areas: Learning Model-based Clustering Modelling High-Dimensional, Complex Data Natural Language Processing, Text Mining Optimization in Classification, Clustering Symbolic Data Analysis Applications of the above methods in relevant domains. Fairness and/or safety in machine learning, Safe reinforcement learning, Safe robot control, Bias in machine learning, Adversarial examples in machine learning and defense mechanisms, Applications of transparency to safety and fairness in machine learning, Verification techniques to ensure safety and robustness, Safety and interpretability by having a human in the loop, Backdoors in machine learning, Transparency in machine learning, Robust and risk-sensitive decision making.

Deep learning for multimodal data fusion and analysis

Machine learning for predictive maintenance in industry 4.0

Transfer learning techniques for small and imbalanced datasets

Artificial Intelligence (AI) in Aerospace Science and Engineering

The scope of the journal includes but is not limited to the following research topics: Aviation Safety; Astrodynamics and Celestial Mechanics; Machine Learning and Optimal Control to Aerospace Systems; Advancements in Unmanned Aerial Vehicles; Advanced Guidance and Control of Hypersonic Vehicles; Positioning and Navigation Technologies; Space Propulsion Technology; Intelligence Sense, Optimization, and Control in Space Vehicles; Galaxy Clusters; Aerodynamics; Aeroacoustics; Space Debris; Aerospace Vehicle Design; Flight Dynamics and Autonomous Control of UAVs; Superhydrophobic and Icephobic Coatings as Passive Ice Protection Systems; Wind Turbine Design; Computational Fluid Dynamics; Morphing Enabling Technologies; Bionic Design and Manufacturing of Innovative Aircraft; Laser Ranged Satellites; Aerodynamics; Aeroacoustics; Thermoacoustics; Thermal Fluids; Climate Impact of Aviation; Advanced Fault Diagnosis and Fault-Tolerant Control Technology of Spacecraft

Applications of AI in the Aerospace and Defense Industry

Artificial Intelligence (AI) Developments for Healthcare Applications

The scope of the journal includes but is not limited to the following research topics: Predictive Medicine, Clinical Decision Support, Drug Discovery, Imaging Analysis, Electronic Health Records, Clinical Trials, Telemedicine, Genomic Analysis, Precision Medicine, Public Health Surveillance, Diagnostic Support, Personalized Medicine, Clinical Decision Support, Drug Discovery, Medical Imaging Analysis, Electronic Health Records, Clinical Trials, Telemedicine, Genomic Analysis.

Responsible AI and data science: Bias detection and mitigation

Data science techniques for anomaly detection in IoT networks

Machine learning for human-robot interaction and collaboration

Blockchain technology for secure and transparent data sharing

AI-powered mental health diagnostics: Ethical considerations

AI-enhanced cybersecurity strategies for critical infrastructure

Cognitive neuroscience meets AI: Insights into human intelligence

AI in criminal justice: Bias detection and fairness in sentencing

AI and ML ethics in autonomous weapons systems

AI in gaming: Player behavior prediction and content generation