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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

2026 the 8th International Conference on Computer Science and Technologies in Education (CSTE)Wuhan, China | April 17-19, 2026Link: https://cste.net/index.htmlSubmission Deadline: December 30, 2025Notification Deadline: January 30, 2026Registration Deadline: February 15, 2026Conference Venue: Central China Normal University (Nanhu Campus), Wuhan, Hubei, China2026 the 8th International Conference on Computer Science and Technologies in Education (CSTE) will be held in Wuhan, China during April 17-19, 2026. CSTE 2026 is co-sponsored by Central China Normal University, China and IEEE, hosted by Faculty of Artificial Intelligence in Education, Central China Normal University, China.At CSTE 2026, participants will have the opportunity to engage with leading experts in education technology, and to gain insights into the latest research and best practices in the field. The conference will also provide a platform for networking and collaboration, enabling participants to build valuable connections with colleagues from around the world.Please visit our website for more information on the conference, including important dates, submission guidelines, and registration details. If you have any questions or concerns, please do not hesitate to contact us. We hope to see you in Wuhan in 2026!Submitted papers will be peer reviewed by program committees and technical committee, and accepted papers will be published into conference proceedings by IEEE after registration and presentation. The proceedings will be submitted for inclusion into IEEE Xplore and indexed by Ei Compendex & Scopus.Selected papers will be published into Lecture Notes in Educational Technology(Electronic ISSN: 2196-4971 & Print ISSN: 2196-4963) as a proceedings book volume, which has been accepted by Springer. Final publication will be subject to the manuscript review by Springer. Those papers will be sent to indexing databases like: Scopus, ACM Digital Library, ERIC, INSPEC, Norwegian Register for Scientific Journals and Series, SCImago. Call for PapersTrack 1: Educational Technologies and Systems▪ E-learning platforms and tools▪ Computer-supported collaborative learning▪ Mobile and ubiquitous learning▪ Gamification and game-based learning▪ Virtual and augmented reality in education▪ Adaptive learning systems▪ Educational robotics and automation▪ Emerging technologies in education▪ Cloud computing in education▪ Immersive learning environments▪ Wearable technology in educationTrack 2: Computer-supported Collaborative Learning and Social Computing▪ Collaborative learning theories and models▪ Social computing and learning▪ Online communities and networks in education▪ Social media in education▪ Collaborative technologies in education▪ Computer-supported argumentation and debateTrack 3: Artificial Intelligence in Education▪ Intelligent tutoring systems▪ Natural language processing in education▪ Knowledge representation and reasoning in education▪ Intelligent educational systems and applications▪ Smart learning environments▪ Cognitive modelling and educational implicationsTrack 4: STEM Education and Computational Thinking▪ STEM education and pedagogy▪ Computational thinking and coding education▪ Robotics and automation in STEM education▪ Computational modeling and simulation in education▪ Educational applications of Internet of Things▪ Digital fabrication and maker educationTrack 5: Educational Data Mining and Learning Analytics▪ Data-driven approaches to education▪ Learning analytics and visualization▪ Educational data mining and machine learning▪ Big data in education▪ Personalized learning▪ Educational decision making▪ Assessment and evaluation in e-learningTrack 6: Digital Technologies for Human Development▪ Digital technologies for social-emotional learning▪ Digital technologies for psychological wellbeing▪ Digital technologies for self-management and regulation▪ Digital technologies for teacher development▪ Digital technologies for labor/moral/character education▪ Sustainable development in a digital world▪ Innovative solutions to address educational inequityTrack 7: Inclusive EdTech: Diversity, Equity, and Innovative Pedagogies▪ AI-enhanced pedagogy for diverse learners▪ Learning analytics-driven differentiation▪ Accessible immersive learning pedagogies▪ Culturally responsive edtech solutions▪ Equity-focused digital assessments▪ Micro-credentialing for diverse learners▪ Smart pedagogy training for educators▪ Multilingual learning support in EdTech▪ Inclusive gamification frameworks▪ Student-centered digital pedagogy▪ AI-augmented project-based learning▪ Hybrid flipped classroom models▪ UDL-based digital resource design

International Conference on Artificial Intelligence and Mathematics (ICAIM - 25)15th - 16th September 2025 Denver, USA (Hybrid Event)https://www.iirst.com/event/important-dates.php?id=3086069Important Dates: - Early Registration Deadline → 16th August 2025- Paper Submission Deadline → 26th August 2025- Conference Date → 15th - 16th September 2025 Call for Paper- Mathematics and Artificial Intelligence- Applications in Science and Engineering using Mathematical Methods- Applied logics, Algorithms and Complexity- Applying Quantitative, Combinatorial, Logical, Algebraic and Algorithmic Methods to Artificial Intelligence Areas- Artificial Intelligence Theory- Automated Deduction- Computational Geometry- Computational Mathematics- Computer Vision- Decision Support- Knowledge-based Systems- Machine Learning- Reasoning- Robotics and PlanningPublication OpportunityAll accepted abstracts will be published in a conference proceedings e-book with ISBN.All accepted full papers have the opportunity to be published in reputable international journals indexed by various databases, subject to terms and conditions and selection by the Scientific Editorial and Reviewer Committee.All papers will receive international exposure and scientific feedback from scholars around the world during the conference.sAreas of Importance in Journal PublicationSelect the most appropriate journal for your paper based on its aims, scope, and guidelines.Prepare your manuscript to conform to the journal's requirements and guidelines, including language and grammar checks.Ensure the language, flow, and scholarly writing style of the paper are of key importance, and consider adding an international flavor to your submission.Follow academic ethics and avoid plagiarism.Pay attention to the quality of graphics and artwork, and format the reference list according to the preferred referencing style of the journal.Benefits of Journal Publication:Receive guidance and support to prepare your manuscript according to journal requirements.Benefit from comprehensive review comments and opportunities to improve your paper.Enjoy the peace of mind of leaving the submission and publication process to the IIRST team, with its years of experience dealing with leading academic journals.Advance your career through journal publications and support for your undergraduate or postgraduate studies.

41st Conference on Uncertainty in Artificial IntelligenceRio de Janeiro, BrazilJuly 21-25, 2025Link: https://www.auai.org/uai2025/The Conference on Uncertainty in Artificial Intelligence (UAI) is one of the premier international conferences on research related to knowledge representation, learning, and reasoning in the presence of uncertainty. UAI is supported by the Association for Uncertainty in Artificial Intelligence (AUAI).Important DatesNameDatePaper submission deadline (incl. supp. material)February 10th, 2025 (23:59 Anywhere on Earth, AoE)Author response/discussion periodApril 3rd - April 10th, 2025 (23:59 AoE)Author notificationMay 6th, 2025 (23:59 AoE)Camera-ready deadlineJune 6th, 2025 (23:59 AoE) Subject AreasBelow you find a non-exhaustive list of relevant topics for your reference.AlgorithmsApproximate InferenceBayesian MethodsBelief PropagationExact InferenceKernel MethodsMissing Data HandlingMonte Carlo MethodsOptimization - CombinatorialOptimization - ConvexOptimization - DiscreteOptimization - Non-ConvexProbabilistic ProgrammingRandomized AlgorithmsSpectral MethodsVariational MethodsApplicationsCognitive ScienceComputational BiologyComputer VisionCrowdsourcingEarth System ScienceEducationForensic ScienceHealthcareNatural Language ProcessingNeurosciencePlanning and ControlPrivacy and SecurityRoboticsSocial GoodSustainability and Climate ScienceText and Web DataLearningActive LearningAdversarial LearningCausal LearningClassificationClusteringCompressed Sensing and Dictionary LearningDeep LearningDensity EstimationDimensionality ReductionEnsemble LearningFeature SelectionHashing and EncodingMultitask and Transfer LearningOnline and Anytime LearningPolicy Optimization and Policy LearningRankingReinforcement Learning and BanditsRelational LearningRepresentation LearningSemi-Supervised LearningStructure LearningStructured PredictionUnsupervised LearningModelsFoundation ModelsGenerative ModelsGraphical ModelsModels for Relational DataNeural NetworksProbabilistic CircuitsRegression ModelsSpatial, Temporal and Spatio-Temporal ModelsTopic Models and Latent Variable ModelsPrinciplesCausalityComputational and Statistical Trade-OffsExplainabilityFairnessPrivacyReliabilityRobustness(Structured) SparsityRepresentationConstraintsDempster-Shafer(Description) LogicsImprecise ProbabilitiesInfluence DiagramsKnowledge Representation LanguagesTheoryComputational ComplexityControl TheoryDecision TheoryGame TheoryInformation TheoryLearning TheoryProbability TheoryStatistical Theory