Andres Bustillo Andres Bustillo

Machine Learning integration in Virtual Reality environments: present and prospective future

Andres Bustillo

Computer Engineering Department
University of Burgos, Spain

ABSTRACT

Over the past decade, improvements in Virtual Reality (VR) headset capabilities, combined with a decrease in prices, have allowed the rapid development of VR applications across various sectors. These applications have proven highly effective in providing immersive and active learning/training experiences. However, to boost their efficiency, these applications should adapt themselves to individual users. This involves giving Virtual Reality systems the ability to learn and take their own decisions. Machine Learning techniques are the most suitable solution for this need, given their capacity to process extensive and diverse datasets, including those derived from human learning experiences. This conference aims to showcase the primary Machine Learning techniques currently used to enhance adaptability and intelligence in VR applications, especially in Serious Games. Additionally, it aims to outline the key trends expected in applying these techniques in the years ahead.

SPEAKER BIOGRAPHY

Andres Bustillo is Associate Professor at the University of Burgos (Spain) and Head of the R&D group DigiUBU (www.3dubu.es) in applications of Virtual Reality. He received his Ph.D. in Physics from the University of Valladolid (Spain) in 2000. He has worked in different disciplines, from Laser development for Plasma Diagnostic, his Ph.D. topic at the Physikalish-Technische Bundesanstalt Berlin, to simulation and integration of new technologies in machine-tool industry, as R&D Project Manager at Nicolas Correa S.A., a Spanish world leader in the design and manufacture of huge milling machines. In 2007 he was recruited by the University of Burgos to join the Computer Engineering Department. His research interests focused then on the application to manufacturing industry of different machine learning and data mining techniques. During the last 10 years, he has opened a new research line in smart applications of Virtual Reality environments, specially to Industry and Cultural Heritage. He has published more than 50 JCR-indexed articles in the last 15 years in machine learning and virtual reality topics, being therefore included in the last two editions of the Ranking of World Scientists (worldwide top-cited scientists) published by the University of Stanford.

Emanuele Frontoni Emanuele Frontoni

XR in the era of GenAI: creativity in human-AI content creation environments

Emanuele Frontoni

University of Macerata, Italy

ABSTRACT

In the wide landscape of Extended Reality (XR), the emergence of Generative AI (GenAI) technologies has revolutionized the paradigms of content creation. This talk presents a comprehensive exploration of the symbiotic relationship between human creativity and AI-driven processes within XR environments. By integrating cutting-edge GenAI methodologies, we delve into the transformative impact on XR domains, encompassing Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR). The speech will cover also the augmentation of human creative capabilities through AI-assisted tools, addressing both the technological advancements and the ethical considerations that arise in this nexus. The speach also critically evaluates the role of GenAI in enhancing immersive experiences, fostering innovation in design, and enabling novel forms of storytelling within XR. Through a multidisciplinary approach, we draw insights from computational creativity, human-computer interaction, and cognitive science, offering a forward-looking perspective on the future of human-AI collaboration in XR content creation.

SPEAKER BIOGRAPHY

Emanuele Frontoni is a Full Professor of computer science with the University of Macerata and the Co-Director of the VRAI Vision Robotics & Artificial Intelligence Lab.
He is Affiliated Researcher at the Italian Institute of Technology (IIT) in Genoa, Italy (https://inbot.iit.it/).
Since 2022, he has been the Scientific Director of the Center for Scientific Research and Technological Innovation in the Neurological Field, NemoLab, at Niguarda Hospital in Milan, Italy (https://nemolab.it/).
His research interests include computer vision and artificial intelligence with applications in robotics, video analysis, human behavior analysis, extended reality and digital humanities.
He is the author of over 300 international articles and collaborates with numerous national and international companies in technology transfer and innovation activities.
Since 2021, he has been included in the annual "World's Top 2% Scientists" list curated by Stanford University and Elsevier, which lists the top 2% of the world's most cited scientists within the "Artificial Intelligence & Image Processing" category.
He is also involved in several national and international technology transfer projects in the fields of AI, Deep Learning, data interoperability, cloud-based technologies, and big multimedia data analysis, extended reality and digital humanities.
He is a member of the European Association for Artificial Intelligence, the European AI Alliance, and the International Association for Pattern Recognition. He served as expert for the EU Commission in the AI H2020 and Horizon Europe Calls and as co-speaker of the European IPEI CIS (Important Project of Common European Interest - Cloud Infrastructure and Services) for the Data Exchange & AI services of the next generation of European Cloud & Edge Services.

Sergi Bermúdez i Badia Sergi Bermúdez i Badia

Applications of VR to Stroke Rehabilitation and Fitness Training

Sergi Bermúdez i Badia

University of Madeira, Portugal

ABSTRACT

Nowadays, it is widely accepted that games, as well as entertainment technologies more broadly, possess very interesting features that, if leveraged effectively, can significantly improve the effectiveness of treatments across a range of health areas. These games, often known as games-with-a-purpose, need to find a delicate yet compelling balance between scientific rigor, health considerations, engineering principles, and entertainment value. In this presentation, I will provide an overview of the methodology employed at the NeuroRehabLab. Here, we integrate games, Human-Computer Interaction techniques, and principles of clinical rehabilitation to develop interactive systems that act as innovative and effective tools for both motor and cognitive rehabilitation and fitness training, with a particular focus on stroke rehabilitation. I will explore the impact of interface technology on the interference between motor and cognitive functions during task performance, the value of VR in designing ecologically valid interventions and assessments, our participatory approach with healthcare professionals to create parameterized models for training Activities of Daily Living within simulated environments, and our use of adaptive techniques in these games. This adaptive approach ensures that these systems can be used effectively by patients with varying levels of cognitive and motor abilities, thus providing personalized training experiences.

SPEAKER BIOGRAPHY

Dr. Sergi Bermúdez i Badia is an Associate Professor with Habilitation at the University of Madeira, specializing in Virtual Reality, Human-Computer Interaction (HCI), Rehabilitation, and Cyberpsychology. He holds a Telecommunications Engineering degree from UPC and a Ph.D. from ETHZ. Dr. Bermúdez i Badia has conducted research at EPFL, ETHZ, Universitat Pompeu Fabra, and Carnegie Mellon University. He currently leads the NeuroRehabLab research group (https://neurorehablab.arditi.pt/) at the University of Madeira/ARDITI and serves as the Scientific Director of The Quality-of-Life Technologies Center of Madeira. Dr. Bermúdez i Badia has served as the President of the International Society for Virtual Rehabilitation. He has an extensive publication record, numerous awards, and has been involved in research projects covering healthcare technologies, resulting in prototypes deployed in real-world settings.

PARTNERS

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