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2026 10th International Conference on Artificial Intelligence and Virtual Reality (AIVR2026) brings together researchers and scientists, both industrial and academic, developing novel Artificial Intelligence and Virtual Reality outcomes. Research in Virtual Reality (VR) is concerned with computing technologies that allow humans to see, hear, talk, think, learn, and solve problems in virtual and augmented environments. Research in Artificial Intelligence (AI) addresses technologies that allow computing machines to mimic these same human abilities. Although these two fields evolved separately, they share an interest in human senses, skills, and knowledge production. Thus, bringing them together will enable us to create more natural and realistic virtual worlds and develop better, more effective applications. Ultimately, this will lead to a future in which interaction between man and machine are made naturally in virtual worlds, with use cases and benefits we are only just beginning to imagine.

Email: Dunn@iact.net

System techniques, performance, and implementation: System components; Virtual reality platforms; AI platforms for VR/AR; Cloud-based platforms; Data generation, manipulation, analysis, and validation; Tracking; Physical environment mapping; Registration; Vision for VR/AR; Deep learning for VR/AR; Standards and theoretical models for AI and/or VR.

Rikkyo University, Japan

We are thrilled to announce that the 9th International Conference on Machine Learning and Machine Intelligence (MLMI 2026) will be held in Tokyo, Japan, from July 17 to 20, 2026. Organized by Rikkyo University, Japan, MLMI 2026 will bring together leading researchers, academics, and industry professionals to explore the latest advancements in machine learning and machine intelligence. The conference will feature insightful presentations, engaging discussions, and vibrant networking opportunities, all set in the culturally rich city of Tokyo. MLMI 2026 aims to advance the field of machine learning and machine intelligence by fostering interdisciplinary collaboration and showcasing cutting-edge research. The scope of MLMI 2026 includes, but is not limited to, deep learning, reinforcement learning, natural language processing, computer vision, robotics, AI ethics, and the integration of machine intelligence in domains such as healthcare, finance, autonomous systems, and environmental sustainability. By providing a platform for knowledge exchange and collaboration, MLMI 2026 seeks to drive innovation and inspire the development of intelligent systems that benefit society.

Email: aimee@iacsit.net

Track 1: Deep Learning and Neural Architectures ▪ Architectural Advances ▪ Advanced Reinforcement Learning Algorithms ▪ Efficient Training Techniques ▪ Multi-Agent Reinforcement Learning ▪ Graph Neural Networks ▪ Time Series and Sequential Data Track 2: Reinforcement Learning and Sequential Decision Making ▪ Generative Models ▪ Predictive Modeling ▪ Neural Architecture Search ▪ Anomaly Detection ▪ Transfer Learning ▪ Sequential Decision Making ▪ Real-Time AI Systems