Special Exhibition Track on the Chinese-Hungarian AI Innovation Summit

The exhibition is open to Track proposals. Please click HERE to submit your proposal.CLOSED
Track I.: AI Solutions for System Efficiency
Organizers: Károly Nehéz and Oliver Hornyák (University of Miskolc)

This track aims to explore and discuss innovative applications of artificial intelligence across diverse domains. Topics may include but are not limited to, AI in the process industry, AI for sustainable Technologies. Participants can expect insights into cutting-edge approaches, case studies, and future trends in utilizing AI for the advancement of system efficiency.

Section 1: AI Applications in Industry

Organizer: Olivér Hornyák (University of Miskolc)

The session explores the diverse and transformative ways artificial intelligence is applied across industrial sectors. From robotics and automation to software development and beyond, this section provides a comprehensive overview of how AI applications are reshaping and advancing various facets of the industrial landscape. Insights will be given into real-world implementations, emerging trends, and the potential impact of AI technologies on industrial practices.

Section 2: AI in Sustainable Technologies

Organizer: Károly Nehéz (University of Miskolc)

Sustainable technologies refer to technological solutions and practices that aim to meet current needs without compromising the ability of future generations to meet their own needs. These technologies are designed to have minimal negative impact on the environment, conserve resources, and contribute to the long-term well-being of both ecosystems and human societies. By integrating AI with sustainable technologies, there is significant potential to create smarter, more efficient systems that contribute to a more sustainable and environmentally friendly future. This convergence allows for the development of innovative solutions to address global challenges related to climate change, resource depletion, and environmental degradation.


Track II.: Cognitive Mapping of Decision Support Systems
Organizer: Ádám Csapó (CIAS at the Corvinus University of Budapest)

This session focuses on challenges and opportunities relevant to how humans can communicate with AI systems through digital interfaces. Mathematical and cognitive modeling tools which can help describe such communicataion are of special interest. In addition, the ability to characterize and better understand how information is accumulated during human-AI decision-making processes can contribute to such modeling tools. Key questions we are looking to explore include: How can human understanding be better supported when working with AI? Is it necessary and even possible to bring AI-supported decision processes more human-like? How can the benefits of analogy-based thinking close to humans be brought to bear alongside the mathematical algorithms driving AI?

Track III.: AI Transformation in Arts
Organizer: László Koppány Csáji, Anna Mária Bólya ( Research Institute of Art Theory and Methodology)

The session will present case studies of AI and AI and VR solutions in the performative and non-performative arts, in the fields of University-level dance education, theatre space creation, architecture and visual arts.

Track IV.: Deep Tech AI Engineering
Organizers: Péter Ekler, Bertalan Forstner, Kristóf Csorba (Budapest University of Technology and Economics)

This track aims to delve into the forefront of AI engineering, focusing on research and development that drives innovation in the field. Attendees will explore the intersection of AI-based technologies and services are reshaping industries. From discussing model training techniques to navigating MLOps approaches in AI service development, participants will gain actionable insights from industry leaders. Delve into the nuances of computer vision, and machine learning, and witness firsthand the prototype demonstrations showcasing pioneering solutions. With a focus on applied AI application and service development, this track promises to be a hub of knowledge exchange and exploration in Deep Tech AI Engineering.

Section 1: AI based Services and Applications

Organizer: Péter Ekler (Budapest University of Technology and Economics)

The ‘AI-based Services and Applications’ section examines the latest advancements in leveraging artificial intelligence for various services and applications across industries. Topics include but not limited to real-world implementations, challenges, ethical considerations, and future prospects in deploying AI-based services and applications.

Section 2: AI Assisted Cognitive Development

Organizer: Bertalan Forstner (Budapest University of Technology and Economics)

The ‘AI Assisted Cognitive Development’ section delves into groundbreaking methodologies for measuring cognitive abilities, harnessing AI for cognitive enhancement through training tasks, simulating data and procedures, and utilizing AI tools for estimating task difficulty, alongside potential discussions on innovative psychometric models.

Section 3: Computer Vision and Machine Learning

Organizer: Kristóf Csorba (Budapest University of Technology and Economics)

The ‘Computer Vision and Machine Learning’ section explores the intersection of computer vision and machine learning techniques, showcasing recent advancements, challenges, and applications in this rapidly evolving field. Topics include but not limited to deep learning-based object detection and recognition, image segmentation, scene understanding, video analysis, generative models for image synthesis, visual perception in robotics, and the fusion of computer vision with other domains such as natural language processing and augmented reality. Additionally, discussions will encompass theoretical foundations, algorithmic innovations, practical implementations, and ethical considerations in leveraging computer vision and machine learning technologies.

Track V.: Domain-Specific AI Solutions
Organizer: Prof. András Hajdú and Dr. Balázs Harangi (University of Debrecen)

This conference track will provide a comprehensive overview of domain-specific AI solutions at a large multidisciplinary research center like the University of Debrecen. The specialty of the approaches here is that it is not sufficient to know the modern AI technologies, but they must be tailored to meet the needs of the individual disciplines. In order to properly present the subject area, we will therefore try to present the approach of the different disciplines, by inviting speakers from fields such as healthcare, agriculture, life sciences, economics, and engineering in addition to AI experts. In all cases, the related AI research is aimed at solving real-world problems that originate in the field.

Track VI.: Deep Learning Technology and Applications
Organizer: Dr. Bálint Gyires-Tóth (Budapest University of Technology and Economics)

We invite researchers, practitioners, and industry participants to present their novel research ideas and practical implementations in the field of deep learning for the „Deep Learning Technology and Applications” track. This track aims to showcase interesting advancements and applications of deep learning across various domains, including but not limited to: computer vision, natural language processing, speech technology, graph neural networks, generative methods and real-world applications. The track provides a platform for knowledge sharing, collaboration, and discussion among participants from diverse backgrounds. In addition, we welcome demonstrations of deep learning systems and applications. Demonstrations can include live presentations, interactive exhibits, or video showcases of your work.