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The 7th International Conference on Industrial Engineering and Artificial Intelligence (IEAI 2026)23-25 April , 2026, Krabi, ThailandLink: https://ieai.net/index.htmlSubmission Deadline: December 30, 2025Acceptance Notification: February 2, 2026Registration Deadline: February 28, 2026Conference Dates: April 23-25, 2026The 7th International Conference on Industrial Engineering and Artificial Intelligence (IEAI 2026) will be held in Krabi, Thailand, 23-25 April , 2026. It is a premier forum dedicated to the convergence of industrial engineering and artificial intelligence (AI). As industries worldwide rapidly adopt AI to enhance efficiency, productivity, and innovation, this conference aims to explore the latest advancements, research, and applications at this intersection.Key topics of interest include smart manufacturing, robotics, machine learning, predictive maintenance, digital twins, and the integration of AI into industrial processes. As we stand on the brink of the Fourth Industrial Revolution, IEAI 2026 will serve as a critical venue for discussing how AI can drive innovation and sustainability in industrial systems.Whether you are an academic researcher, a practitioner in the field, or an industry leader, IEAI 2026 will offer valuable insights and opportunities to engage with the cutting-edge developments that are shaping the future of industrial engineering and artificial intelligence.IEAI PublicationThe submitted papers will be peer reviewed by Technical Committee. Accepted papers will be published in the International Conference Proceedings. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences. Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conferenceCall for Papers1. Applications of AI in Industrial EngineeringIntelligent Manufacturing SystemsAI-Driven Process OptimizationSmart Factories and Industry 4.0AI for Predictive Maintenance in Industrial SystemsRobotics and Automation in ManufacturingAI in Supply Chain and Logistics OptimizationData-Driven Decision Making in Industrial Environments2. Industrial Optimization and AIAI for Industrial Scheduling and PlanningMulti-Objective Optimization using Machine LearningAI-Enhanced Process Control SystemsEnergy Efficiency Optimization in Manufacturing using AIAI-Enabled Simulation and Modeling for Industrial Systems3. AI for Quality Control and Safety in IndustryMachine Learning in Industrial Quality ControlAI for Predicting Failures and Defects in Production LinesSafety Monitoring and Hazard Prevention in Industrial 4. Artificial Intelligence in Industrial Supply ChainsAI and Blockchain Integration for Industrial Supply ChainsSupply Chain Management with Deep Learning TechniquesAI in Logistics and Transportation NetworksData Analytics for Improving Inventory Management in IndustryAI for Risk Management and Resilience in Supply Chains5. Smart Manufacturing and IoTIoT and AI Integration for Real-Time Industrial MonitoringAI in Predictive Maintenance using IoT SensorsDigital Twin Technology for Industrial ApplicationsAI-Driven Decision Support Systems in Industrial Operations6. Industrial Robotics and Autonomous SystemsAI and Machine Learning in Industrial RoboticsAutonomous Mobile Robots in ManufacturingHuman-Robot Collaboration in Industrial EnvironmentsAI for Vision-Based Robotic Systems in Production Lines7. AI in Industrial Process AutomationDeep Learning for Process Automation in IndustryIntelligent Automation Systems in Industrial EnvironmentsAI-Driven Adaptive Control Systems for Industrial ProcessesEdge AI for Real-Time Process Control and Decision Making8. AI-Enabled Sustainability in Industrial SystemsAI for Sustainable Manufacturing PracticesMachine Learning for Energy Consumption OptimizationSmart Waste Management and Recycling Systems using AIAI Solutions for Reducing Carbon Footprint in Industrial Operations9. AI for Data-Driven Industrial Decision MakingPredictive Analytics for Industrial Process ImprovementAI in Industrial Big Data AnalyticsDecision Support Systems using AI in Industrial OperationsMachine Learning for Process Optimization in Real-Time Manufacturing10. AI in Industrial Human-Machine InteractionHuman-Centered AI Design for Industrial ApplicationsAI for Improving Human Performance in Industrial SystemsCognitive Computing and Human Factors in Industrial AIAI and Virtual Reality for Industrial Training and Simulation11. AI and Industrial CybersecurityAI for Threat Detection and Prevention in Industrial NetworksIndustrial Cybersecurity with Machine LearningAI-Driven Risk Management for Industrial IoTAutonomous Systems for Securing Critical Infrastructure in Industry12. AI in Smart Energy and Industrial SystemsAI for Smart Grid and Industrial Energy ManagementAI in Energy Optimization for Industrial FacilitiesMachine Learning for Predicting Energy Demand in Industrial SystemsAI-Driven Energy Efficiency in Industrial Operations

The 2026 17th International Conference on E-Education, E-Business, E-Management, and E-Learning (IC4e 2026)Fukuoka, Japanhttps://www.ic4e.net/index.htmlWelcome to the 17th IC4e 20262026 17th International Conference on E-Education, E-Business, E-Management and E-Learning (IC4e) will be held at Kyushu University Fukuoka, Japan during April 1-4, 2026.Conference Theme: "Innovating E-Systems for a Smarter Future"E-education, e-business, e-management, and e-learning are vital pillars of the digital society's development. With the deep integration of cloud computing, artificial intelligence, and big data technologies, these fields are undergoing rapid transformation. E-education breaks traditional educational boundaries of time and space, e-business accelerates the digitalization of global trade, e-management enhances the efficiency of public services and business operations, and e-learning optimizes knowledge dissemination and learning experiences. These domains have become central drivers of technological innovation and sustainable socio-economic development.The 17th International Conference on E-Education, E-Business, E-Management and E-Learning (IC4e 2026) will be held in Fukuoka, Japan during April 1-4, 2026, sponsored by IEEE, and co-sponsored by Rajamangala University of Technology Tawan-ok, Thailand with patrons from Purdue University Northwest, USA, De La Salle University-Manila, Philippines, China West Normal University, China, Bulacan State University, Philippines, and Prince Sultan University, Saudi Arabia.Call for Papers The 2026 17th International Conference on E-Education, E-Business, E-Management, and E-Learning (IC4e 2026), with the theme "Innovating E-Systems for a Smarter Future," serves as the premier forum for presenting new advances and research results in the fields of theoretical, experimental, and applied E-Education, E-Business, E-Management, and E-Learning. This conference will bring together leading researchers, engineers, and scientists worldwide to share their latest research, insights, and developments in these domains. Topics of interest for submission include, but are not limited to:e-Education:Innovative e-learning technologies and platformsSystems, Design and TechnologiesPractices and cases in e-educationSystems and technologies in e-educationApplications and integration of e-educatione-learning evaluation and contentCampus information systemse-learning technologies, standards and systemsMobile learningComputer aided assessmentsKnowledge managementVirtual learning environmentsMultimedia in e-learningMarketing and promoting e-learningSocial benefits of e-learningOrganization learningTechnology adoption and diffusion of e-learninge-Business:Mobile and pervasive commerceElectronic Markets and Multiagent SystemsDigital goods and productsB2B, B2C, and C2C modelsAgent-mediated e-Commercee-Marketplaces, e-Hubs, and portalsPervasive technologies for eCommerceDynamic pricing modelsP2P-computing for e-Commercee-Payment systemse-Commerce content managementConsumer protection in eCommerceUser behavior modelingInnovative business modelsEnterprise application integrationBusiness process re-engineeringVirtual enterprises and virtual marketsVirtual organizations and coalitionsMobile businesse-Learning:Systems, Design and Technologiese-Learning platformsCourse designEmerging and best practicesPartnerships in e-LearningEvaluation of e-Learninge-Learning strategiesSocial benefits of e-Learninge-Learning effectiveness and outcomesWeb-based learningSecurity and confidentialitySelf-learning integrated methodologyAmbient intelligenceAssertive and assistive educational technologyComputer-aided assessmentLearning content management systemsAV-communication and other mediaDigital classroomsBlended learningCollaborative on-line learninge-Management:Leadership in the digital eraKnowledge management systemse-Audite-Control and Risk Managemente-Planninge-Organisinge-Supervisione-Politicse-Communicatione-RecruitmentSystems, Design and TechnologiesKnowledge ManagementTechnology Adoption and Diffusion of eManagemente-Management Strategiese-Management Effectiveness and OutcomesSocial Benefits of e-ManagementCurrent Trends in e-ManagementThreats in e-Management

The 10th International Conference on Deep Learning TechnologiesJuly 17-19, 2026, Kunming, Chinahttps://www.icdlt.orgSubmission Deadline: March 1, 2026Notification of Acceptance: April 1, 2026Camera Ready Deadline: April 15, 2026Registration Deadline: April 15, 2026Conference Dates: July 17-19, 2026You are invited to attend 2026 10th International Conference on Deep Learning Technologies will be held during July 17-19, 2026 in Kunming, China. It's sponsored by Kunming University of Science and Technology, China, organized by the Faculty of Information Engineering and Automation of Kunming University of Science and Technology. It's to provide a valuable opportunity for researchers, scholars and scientists to exchange their ideas face to face in Deep Learning Technologies.We invite researchers from deep learning technologies to participate and submit their work to the program. Likewise, any work on deep learning that has a relation to any of these fields or potential for the usage in any of them is welcome. Please refer to the different submission categories under "Call for Papers" above for further details.Track 1: Deep Learning Model and AlgorithmRecurrent Neural Network (RNN) Sparse Coding Neuro-Fuzzy Algorithms Evolutionary Methods Convolutional Neural Networks (CNN) Deep Hierarchical Networks (DHN) Dimensionality Reduction Unsupervised Feature Learning Deep Boltzmann Machines Generative Adversarial Networks (GAN) Autoencoders Deep Belief Networks Meta-Learning and Deep Networks Deep Metric Learning Methods MAP Inference in Deep Networks Deep Reinforcement Learning Learning Deep Generative Models Deep Kernel Learning Graph Representation Learning Gaussian Processes for Machine Learning Clustering, Classification and Regression Classification ExplainabilityTrack 2: Machine Learning Theory and TechnologyNovel machine and deep learningActive learningIncremental learning and online learningAgent-based learningManifold learningMulti-task learningBayesian networks and applicationsCase-based reasoning methodsStatistical models and learningComputational learningEvolutionary algorithms and learningFuzzy logic-based learningGenetic optimizationClustering, classification and regressionNeural network models and learningParallel and distributed learningReinforcement learningSupervised, semi-supervised and unsupervised learningTensor Learning Deep and Machine Learning for Big Data Analytics:Deep/Machine learning based theoretical and computational modelsMachine learning (e.g., deep, reinforcement, statistical relational, transfer)Model-based reasoningTrack 3: Deep and Machine Learning ApplicationsDeep Learning for Computing and Network PlatformsRecommender systemsDeep Learning for Social media and networksDeep Learning in Computer VisionDeep learning in speech recognitionDeep Learning in Nature Language Processing,Deep Learning in Machine TranslationDeep learning in bioinformaticsDeep Learning in Medical Image AnalysisDeep Learning in Climate ScienceDeep Learning in Board Game ProgramsDeep and Machine Learning for Data Mining and KnowledgeTrack 4: Responsible AI, Security, and GovernanceAI safetyPrivacy preservationAlgorithmic FairnessFairness and ethicsClassification Explainability and Explainable AI (XAI)AI EthicsAI governanceGreen Deep LearningSynthetic Data GenerationSocial and Economic Impact of AISustainable AIAI Risk AssessmentThe accepted paper will be included into ICDLT 2026 Conference ProceedingsPUBLICATION HISTORYICDLT 2025 Proceedings - 979-8-4007-1852-6 | ACM Digital Library | Ei & SCOPUS IndexICDLT 2024 Proceedings - 979-8-4007-1686-7 | ACM Digital Library | Ei & SCOPUS IndexICDLT 2023 Proceedings - 979-8-4007-0752-0 | ACM Digital Library | Ei & SCOPUS IndexICDLT 2022 Proceedings - 978-1-4503-9693-6 | ACM Digital Library | Ei & SCOPUS IndexICDLT 2021 Proceedings - 978-1-4503-9016-3 | ACM Digital Library | Ei & SCOPUS IndexICDLT 2020 Proceedings - 978-1-4503-7548-1 | ACM Digital Library | Ei & SCOPUS IndexICDLT 2019 Proceedings - 978-1-4503-7160-5 | ACM Digital Library | Ei & SCOPUS IndexICDLT 2018 Proceedings - 978-1-4503-6473-7 | ACM Digital Library | Ei & SCOPUS IndexICDLT 2017 Proceedings - 978-1-4503-5232-1 | ACM Digital Library | Ei & SCOPUS Index

Chief Data and AI Officer Programmehttps://cmu.to/OG1O6 Join usProgramme OverviewNUS School of Computing has launched the Chief Data and AI Officer Programme to help you lead the data strategy and analytics agenda of your organisation. This programme will teach you the technologies, tools and methodologies to manage data as a strategic asset, generate actionable analytical insights, foster innovation and reach closer to tangible business benefits. Unlock enterprise data value, align strategy with business needs, and become a trusted business partner.Learning OutcomesEvaluate strategic implications and innovative value generation through proficient data managementAnalyse strategies for capitalising on data monetisationExplore innovation and emerging technologies in the domainExamine cyber risk through proficient application of data analytics and ethical considerations, resulting in effective management of risks and complianceEmpower the team through the acquisition of advanced leadership proficiencies in team management, negotiation, influence, and change managementWho is this programme for?Become a data strategist to drive tangible business valueSeasoned executives eager to champion AI strategies and leverage data as a key asset to spearhead sustainable and profitable growth.Senior professionals with a working knowledge of data management who want to foster innovation through the power of data, and AI to propel business expansion and assume CXO positions.Business leaders looking to explore latest opportunities to drive digital innovation and long-term strategic growth. Programme ModulesPillar 1: Data Foundations for Enterprise Value CreationPillar 2: Strategic Levers for Business GrowthPillar 3: Intelligent Technologies and Scalable AIPillar 4: Risk, Resilience and Responsible GovernancePillar 5: Transformational Leadership in the Age of AI

International Journal of Information Technology & Decision MakingISSN (print): 0219-6220 | ISSN (online): 1793-6845 International Journal of Information Technology and Decision Making (IJITDM) provides a global forum for exchanging research findings and case studies which bridge the latest information technology and various decision-making techniques. It promotes how information technology improves decision techniques as well as how the development of decision-making tools affects the information technology era. The journal is peer-reviewed and publishes both high-quality academic (theoretical or empirical) and practical papers in the broad ranges of information technology related topics.Call for PapersSpecial Issue onExploring Data Science in IT and Quantitative ManagementSupply Chain Management, Sustainability, and Productivity Efficiency EvaluationsDecision Making in Risk AnalysisOperations Research and Optimization Submission Guidelines https://www.worldscientific.com/page/ijitdm/submission-guidelinesAbstracted & Indexed in(https://www.worldscientific.com/page/ijitdm/abstracted-indexed)ABDC Journal Quality List by Australian Business Deans CouncilAcademic OneFileBaiduBusiness Source Index (Ebsco)CabellCNKI ScholarCnpLINKerCompendexCompuMath Citation Index (CMCI)CrossRefDBLP Computer Science BibliographyDimensionsEbsco Discovery ServiceEbsco Electronic Journal Service (EJS)Ebsco Science & Technology Collection, Computer Science IndexExLibris Primo CentralGoogle ScholarINSPECISI Alerting ServicesJ-GateJournal Citation Reports/Science EditionNaverNSTL - National Science and Technology LibrariesOCLC WorldCat®ProQuest CentralProQuest Computer & Information Systems AbstractsProQuest Technology Collection (Advanced Technologies Database with Aerospace)RePECScience Citation Index Expanded (SCIE)ScopusThe Summon® Service

Natural Hazards ResearchVolume 4, Issue 1, March 2024, Pages 87-96AbstractUnderstanding the spatiotemporal distribution of forest fires and future predictions is very important for management strategies. To identify the present status of forest fires in the Kingdom of Thailand and their risk in the future, ten-year forest fire data were used, and a forest fire hotspot was prepared. A geospatial technique was used in the study to characterize the parameters of forest fires in the country and identify future forest fire risk areas. Most of the forest fires in the country were found to be seasonal. Deciduous forests in higher elevations and on moderate slopes were most vulnerable to forest fire. The level of aridity, soil moisture, temperature, precipitation, vegetation status, and topography influenced the spatiotemporal distribution of forest fires in the country. Greater than 50% of fire risks were observed in 22 administrative divisions, and 17 of the 209 protected areas are also in the high-risk category. The final forest fire hotspot map can be used in policy development and successful management strategies. A better monitoring strategy should be used in the fire hotspot areas as a precautionary measure to minimize the anthropogenic causes of forest fires.Read more at https://www.sciencedirect.com/science/article/pii/S2666592123000847

SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)Location: SingaporeClosing date: 24 Jan 2025As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets that are relevant to industry demands while working on research projects in SIT. The primary responsibility of this role is to deliver on an industry innovation research project where you will be part of the research team to develop future-ready display technologies and demo applications for virtual reality, augmented reality and mixed reality.Key ResponsibilitiesParticipate in the research project with Principal Investigator (PI), Co-PI and the research team members to ensure all project deliverables are met.Undertake these responsibilities in the project:Conduct in-depth AI research towards proof-of-concept (POC) prototypes for future-ready display technologies for VR/AR/MRDevelop demonstration applications for the POC prototypeCarry out Risk Assessment, and ensure compliance with Work, safety and health regulations.Coordinate procurement and liaison with vendors/suppliers.Work independently, as well as within a team, to ensure proper operation and maintenance of equipment.Job RequirementsA PhD degree in computer or related programmes and have relevant competence in the areas of VR/AR/MR and AI.Knowledge and experience in optics will be advantageous.Able to build and maintain strong working relationships with people within and external to the university.Self-directed learner who believes in continuous learning and developmentShow strong initiative and take ownership of work.>=3 years of research experience in VR/AR/MR/AI.Hands-on experience of developing POC systems to demonstrate research results.

Environmental HealthLink: https://ehjournal.biomedcentral.com/aboutSubmission guidelines: https://ehjournal.biomedcentral.com/submission-guidelinesAims and scopeEnvironmental Health publishes manuscripts on important aspects of environmental and occupational medicine and related studies in toxicology and epidemiology that elucidate the human health implications of exposures to environmental hazards. Environmental Health articles are published with open access, and the journal operates a single-blind peer-review system.The journal is aimed at scientists and practitioners in all areas of environmental science in which human health and well-being are involved, either directly or indirectly, and with a view to improving the prevention of environmentally-related risks to human health. Environmental Health is a public health journal serving the public health community and scientists working on matters of public health interest and importance pertaining to the environment.Before submitting a manuscript, please see our submission guidelines for author guidance.Indexing servicesAll articles published in Environmental Health are included in:CABICASCitebaseCurrent contentsDOAJEmbaseEmBiologyGlobal HealthMEDLINEOAIsterPAIS InternationalPubMedPubMed CentralScience Citation Index ExpandedScopusSOCOLARZetocThe full text of all articles is deposited in digital archives around the world to guarantee long-term digital preservation. You can also access all articles published by BioMed Central on SpringerLink.Why publish your article in Environmental Health?We are a well-established and highly influential open access journal publishing high quality research in all aspects of environmental and occupational medicine.We are a highly accessed resource for scientists and practitioners working in environmental and occupational medicine. With more than one million direct article downloads per year, We are ranked in Q1 in the SCIE 2022 Journal Citation Reports for both the Public, Environmental and Occupational Sciences and Environmental Sciences categories.Supported by our highly-respected Editorial Board, we are committed to open research and transparency, encouraging preprint deposition, and operating a single-blind peer-review system.Open access publication ensures that your article can be easily discovered, accessed, used, and shared, maximising your impact and acting as a springboard for further discovery.