Machine learning & deep learning
Algorithms, architectures, training at scale, and deployment patterns for intelligent systems.
AI & Machine Learning 2025
International Conference on Artificial Intelligence and Machine Learning
Theme: Navigating the Future: Intelligence, Innovation, and Impact
Resources
Brochures and PDFs can be linked here when ready. Questions? ai-ml@wisdomconferences.uk
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AI & Machine Learning 2025
Oct 20–22, 2025 · Tokyo, Japan
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Choose registration, sponsorship, or abstract submission. Every Wisdom Conferences event uses the same three-step structure so delegates and partners always know where to go.
About the conference
The International Conference on Artificial Intelligence and Machine Learning brings together researchers, practitioners, and industry leaders to explore the frontiers of intelligent systems, responsible innovation, and real-world impact.
Through keynote sessions, technical tracks, and collaborative workshops, participants will exchange ideas on machine learning, deep learning, NLP, computer vision, robotics, and the societal implications of AI.
Whether you are presenting new research or seeking partnerships, this conference offers a global platform to connect with peers and shape the next wave of intelligent technologies.
Important dates
Abstract submission deadline
June 15, 2025
Early bird registration
July 20, 2025
Final registration
October 10, 2025
Why present?
Networking opportunities
Meet researchers, industry experts, and funders from around the world.
Global recognition
Showcase your work on an international stage and build your academic profile.
Publication prospects
Selected work may be considered for partner journals and proceedings.
Expert feedback
Receive insights from session chairs and peers during Q&A and posters.
Industry linkage
Explore collaborations with companies investing in AI and ML innovation.
Career development
Ideal for students and early-career researchers seeking visibility and mentorship.
Scientific sessions
Topics to be discussed
We invite original contributions across AI and machine learning theory, applications, and interdisciplinary work. Present your research to an international audience and engage in structured scientific sessions.
Neural networks, NLP & computer vision
Representation learning, multimodal models, and perception for real-world applications.
Generative AI & responsible innovation
LLMs, agents, safety, governance, and trustworthy AI in research and industry.
AI in healthcare, robotics & edge
Clinical decision support, embodied AI, and efficient inference on devices and at the edge.
Data, MLOps & production ML
Pipelines, monitoring, reproducibility, and lifecycle management for production systems.
Interdisciplinary & emerging topics
Finance, climate, cybersecurity, education, and cross-domain collaboration.
Committee members
P
Prof. James Chen
Conference Chair
Tokyo Institute of Technology, Japan
D
Dr. Sarah Okonkwo
Scientific Chair
University College London, UK
D
Dr. Michael Weber
Program Co-Chair
ETH Zurich, Switzerland
D
Dr. Yuki Tanaka
Local Organizing Chair
University of Tokyo, Japan
Speakers
Keynote & invited speakers
Programme, To be announced
Invited keynotes, plenary speakers, and session chairs will be published as they are confirmed.
Explore the host city
Tokyo — culture, innovation, and iconic sights for international delegates.
Tokyo — temple at night
Tokyo — skyline
Tokyo — historic gate
Tokyo — city lights
Media partners
Partner logos can be added here. Contact ai-ml@wisdomconferences.uk for sponsorship and media kits.
Download our brochure
Get the full program overview, sponsorship options, and delegate information. Leave your details and we will send the PDF.
PDF
Get in touch
We are here to make your conference experience informative, inspiring, and memorable.
Our location
Office 12329, 182-184 High Street North, East Ham, London, E6 2JA
Phone
+44 738034 5362General contact page — the AI & ML conference team uses the inbox above.
Message the team
Questions about International Conference on Artificial Intelligence and Machine Learning? Send us a note.