Sponsorship and Exhibition Prospectus for IEEE CAI 2024 is now available.
IEEE CAI 2024
The 2024 IEEE Conference on Artificial Intelligence (IEEE CAI 2024) is the 2nd edition of the new conference and exhibition with an emphasis on the applications of AI and key AI verticals that impact industrial technology applications and innovations. Â
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Plan now to attend this highly anticipated inaugural event, taking place June 25-27, 2024, at Marina Bay Sands, Singapore.
Important Deadlines
Workshop & Panels proposal: 20 Nov 2023
Abstract submission: 2 Jan 2024
Paper submission (long & short papers): 8 Jan 2024
Acceptance notifications & reviewers’ comments: 25 Mar 2024
Final reviewed submission: 25 Apr 2024
Welcome Message From General Co-Chairs
On behalf of the Organising Committee, we would like to extend our warmest welcome to you to the 2024 IEEE Conference on Artificial Intelligence (IEEE CAI 2024), to be held in the sunny island of Singapore.
The year 2024 will see the 2nd edition of IEEE CAI and will take place at Marina Bay Sands, Singapore from 25 – 27 June 2024.
Come and join us for an experience that will prepare you to learn about new research and breakthroughs in AI, gain a valuable insight into new start-ups and leading AI establishments, grow your network and get inspired by the brightest minds working in this multi-faceted field.
We look forward to meeting you at the IEEE CAI 2024 in Singapore.
Professor Ivor TSANG
Professor Yew Soon ONG
Professor Hussein ABBASS
General Co-Chairs, IEEE CAI 2024
SUBMISSIONS TO
Conference Subjects
AI and Education
Involve the creation of adaptive learning systems, personalised content delivery, and administrative automation. It also utilises predictive analytics to monitor student progress and identify learning gaps.
AI and Sustainability
Employ AI to optimise sustainable energy resources, reduce wastage, and support renewable energy initiatives. It leverages AI’s problem-solving capabilities to address environmental challenges and contribute to a sustainable future.
AI in Healthcare and Life Science
Explore the need for improved decision making to assist medical practitioners as well as additional medical issues including personnel allocation and scheduling, automated sensing, improved medical devices and manufacturing processes, and supply chain optimisation.
AI in Metaverse
Venture into a sophisticated combination of virtual reality (VR), augmented reality (AR), and advanced artificial intelligence (AI) in this vast, interconnected 3D virtual space. It examines how AI-driven non-human avatars further enhance Digital Twin technologies and enrich the Metaverse experience, blurring boundaries between reality and the virtual space.
AI in Multi-agents and Robotic Systems
Multi-Agent Systems (MAS) in Artificial Intelligence study how multiple intelligent agents or robots work together to achieve tasks under common goals or distinct interest scenarios. It involves mixing agents with humans to address raising trust and safety concerns.
Foundation Models and Generative AI
Delve into the power of foundation models and generative AI, leveraging knowledge representation, crossing modality gaps, and reshaping data generation. It harnesses generative AI to innovate and ensure robustness, fairness, transparency, while understanding the challenges in deploying the foundation models.
Industrial AI
Revolutionise aerospace, transportation, and manufacturing sectors through optimising system design, autonomous navigation, and management logistics. Its application to power systems enhances grid efficiency, predictive maintenance, and cybersecurity, shaping a smarter and more resilient energy landscape.
Resilient and Safe AI
Develop AI systems that are reliable, secure, and able to withstand unexpected situations or cyberattacks. It emphasises the importance of creating AI technologies that function correctly and safely, even under adverse conditions, while also maintaining data privacy and system integrity.
Societal Implications of AI
Explore the impact of artificial intelligence on society, including issues related to ethics, privacy, and equity. It examines how AI influences job markets, decision-making processes, and personal privacy, while also considering the importance of fairness, transparency, and accountability in AI systems.
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