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7th International Conference on Artificial Intelligence and Machine Learning (CAIML 2026)

CAIML 2026

Date of beginning

Saturday, 24 October 2026

Duration

2 days

Deadline for abstracts

Saturday, 22 August 2026

City

Vienna, Austria

Country

Vienna, Austria

Contact

CAIML 2026

E-Mail

This email address is being protected from spambots. You need JavaScript enabled to view it.

Memo

7th International Conference on Artificial Intelligence and Machine Learning (CAIML 2026) October 24 ~ 25, 2026, Vienna, Austria https://cbiot2026.org/caiml/index Scope 7th International Conference on Artificial Intelligence and Machine Learning (CAIML 2026) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence and Machine Learning. The Conference looks for significant contributions to all major fields of the Artificial Intelligence, Machine Learning in theoretical and practical aspects. The aim of the Conference is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field. Authors are solicited to contribute to the conference by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in the following areas, but are not limited to:: Topics of interest include, but are not limited to, the following   Artificial Intelligence Algorithms Knowledge Representation and Reasoning AI Agents, Multi‑Agent Systems and Autonomous AI Neuro‑Symbolic AI Machine Learning Algorithms and Theory Deep Learning and Neural Networks Generative AI and Diffusion Models Foundation Models and Large‑Scale Pretraining Multimodal Learning (Vision‑Language‑Audio) Self‑Supervised and Representation Learning Causal Machine Learning and Counterfactual Reasoning Efficient ML: LoRA, MoE, Distillation and Quantization Federated, Distributed and Parallel Learning Continual, Lifelong and Streaming Learning TinyML, Edge AI and On‑Device Intelligence Adversarial ML, Robustness and AI Red‑Teaming Explainable AI (XAI) and Interpretability Data Mining, Knowledge Discovery and Neural Search Knowledge Graphs and Semantic Technologies Natural Language Processing and LLMs Computer Vision, Pattern Recognition and Vision‑Language Models Robotics, Reinforcement Learning and Embodied AI Sim‑to‑Real Transfer and Robot Learning Bioinformatics, Healthcare AI and Scientific Machine Learning Climate AI, Sustainability and Geospatial Intelligence Ambient Intelligence and Pervasive Computing AI Ethics, Policy and Governance   Paper Submission Authors are invited to submit papers through the conference Submission System by August 22, 2026 . Submissions must be original and should not have been published previously or be under consideration for publication while being evaluated for this conference. The proceedings of the conference will be published by Computer Science Conference Proceedings in Computer Science & Information Technology (CS & IT) series (Confirmed). Selected papers from CAIML 2026, after further revisions, will be published in the special issue of the following journal. Machine Learning and Applications: An International Journal (MLAIJ) The International Journal of Artificial Intelligence & Applications (IJAIA) International Journal on Soft Computing ( IJSC ) International Journal of Database Management Systems (IJDMS) International Journal on Soft Computing, Artificial Intelligence and Applications (IJSCAI) Advances in Vision Computing: An International Journal (AVC) International Journal of Network Security & Its Applications (IJNSA) Important Dates   (Batch 2: Submissions after Aug 10) Submission Deadline: August 22, 2026 Authors Notification: September 30, 2026 Registration & camera – Ready Paper Due: October 07, 2026 Contact Us Here’s where you can reach us : This email address is being protected from spambots. You need JavaScript enabled to view it. (or) This email address is being protected from spambots. You need JavaScript enabled to view it.