Conference: The 9th International Conference on Machine Learning and Machine Intelligence (MLMI 2026)

General NEWS

Machine Learning and Machine Intelligence MLMI 2026 Japan Deep learning Reinforcement learning Sequential decision making NLP Multimodal learning Human-Centered AI

The 9th International Conference on Machine Learning and Machine Intelligence (MLMI 2026)

Conference Theme: "AI-Driven Innovations for a Sustainable Future"
https://mlmi.net

Submission Deadline: February 5, 2026

Notification Deadline: March 5, 2026

Registration Deadline: March 20, 2026

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.

MLMI 2026 offers a unique opportunity to engage with the latest research, connect with global experts, and contribute to the future of machine intelligence. We invite you to join us for four days of learning and networking. You are guaranteed to leave the event with a suitcase full of knowledge and inspiration.

Submitted papers will be peer reviewed by conference committees, and accepted papers after proper registration and presentation will be published into Lecture Notes in Electrical Engineering (Electronic ISSN: 1876-1119 & Print ISSN: 1876-1100) as a proceedings book volume. The book series will be indexed by EI Compendex, SCOPUS, INSPEC, SCImago and other database.

Topics of interest for submission include, but are not limited to:

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

Track 3: Applied Machine Intelligence	Track 4: Natural Language Processing and Multimodal Learning
▪ Machine Learning in Healthcare	▪ Large Language Models
▪ AI in Robotics	▪ Multilingual and Low-Resource NLP
▪ AI for Cybersecurity	▪ Multimodal Machine Learning
▪ Biometric and Behavioral Analytics	▪ Cross-Modal Retrieval and Generation
▪ Industry-Specific Applications

Track 5: Emerging Paradigms and Future Directions	Track 6: Explainable, Ethical, and Human-Centered AI
▪ Quantum Machine Learning	▪ Explainable AI (XAI)
▪ Federated and Distributed Learning	▪ Ethical AI and Fairness
▪ AutoML and Meta-Learning	▪ Privacy-Preserving Machine Learning
▪ Sustainable and Green AI	▪ Human-Centered AI
▪ Hybrid Models	▪ Augmented Intelligence

Jan 17, 2026 at 10:57 AM