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4th International Conference on Artificial Intelligence & Machine Learning (AIM-2027)

Event artwork for 4th International Conference on Artificial Intelligence & Machine Learning (AIM-2027)

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About this event

What to expect

AIM-2027 brings AI and machine learning researchers, industry experts and innovators to Orlando and online from 26–28 April 2027 for three days of research exchange, practical insight and global networking.

Where AI research meets real-world application

Organised by United Scientific Group, the 4th International Conference on Artificial Intelligence and Machine Learning is a hybrid event hosted at Courtyard by Marriott across Universal Orlando. Its central aim is to bridge academia and industry, helping attendees share breakthroughs, form collaborations and explore how emerging AI and ML technologies translate into applications across healthcare, finance, robotics, automation and other sectors.

The programme combines plenary and keynote presentations, panel discussions, interactive sessions, workshops, networking and an innovation showcase. The three-day structure opens with keynotes and panels on 26 April, moves into workshops and networking on 27 April, and concludes with an innovation showcase on 28 April. The opening-day schedule begins with registration and badge pickup at 07:30, followed by a plenary session, keynote sessions, a networking break, group photo and networking lunch.

Speakers and conference themes

Announced plenary and keynote contributors include James Hendler of Rensselaer Polytechnic Institute, Kristy Elizabeth Boyer of the University of Florida, Paul A Pavlou of Miami Herbert Business School, Tianzhen Hong of Lawrence Berkeley National Laboratory, David G Stork of Stanford University, Douglas C Schmidt of William & Mary, Seth Dorbin of ARYA Labs and Vasant Honavar of The Pennsylvania State University.

Conference tracks span a broad range of technical and applied subjects, including:

  • Large language models, generative AI and natural language processing
  • Machine learning, deep learning, neural networks and AI algorithms
  • Computer vision, robotics, autonomous systems and expert systems
  • AI infrastructure, tools, applications and cloud automation
  • Data mining, data science, big data engineering and high-performance computing
  • Cybersecurity, quantum computing and virtual or augmented reality
  • AI in medicine, education and economics
  • Human-computer interaction, mathematics, ethics and governance

Who should attend?…

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