The rapid digitization of our world requires a fundamental shift in how we prepare the future workforce. Traditional training methods for complex professions are often costly, geographically constrained, and may not effectively prepare individuals for dynamic, technology-driven environments. This research area confronts this challenge directly by investigating, developing, and deploying digital reality solutions that bridge the widening skills gap. We focus on creating scalable, accessible, and effective training platforms that prepare workers for modern demands, ensuring that skill acquisition can keep pace with technological advancement.

This research area pioneers new training paradigms using immersive technologies. Inspired by research on virtual reality for skill acquisition, our primary goal is to validate the efficacy of VR and MR simulations for soft skills development. Our research design and test next-generation training modules that transcend physical limitations, allowing trainees to practice complex tasks in a safe, controlled, and data-rich virtual setting. By focusing on measuring skill transfer from the virtual to the real world, we aim to optimize human performance, enhance decision-making, and dramatically improve the efficiency and accessibility of workforce education.

This research area aims to address the urgent global challenge of low literacy levels, which continue to affect millions of children and adults worldwide. Despite advancements in education, a significant portion of the global population still lacks basic reading and writing skills—an issue that hinders academic achievement, economic mobility, and social participation. To tackle this issue, our work explores the intersection of immersive technologies and artificial intelligence to design adaptive virtual reality (VR) experiences that support literacy skills development. By integrating intelligent algorithms capable of analyzing learner behavior, attention, and performance in real time, these immersive environments dynamically adjust to each individual. Developed through co-creation and co-design with educators and learners, the experiences are grounded in authentic classroom needs, fostering engagement through interactive storytelling, embodied learning, and meaningful context

From a research perspective, this work seeks to advance understanding of how adaptive immersive systems can enhance learning outcomes and motivation through personalized feedback and embodied cognition. It investigates the mechanisms by which immersion, joyful learning experiences and engagement interact with literacy acquisition processes, drawing on insights from cognitive psychology, learning sciences, and human-computer interactio . Through close collaboration with teachers and students, the research aims to establish evidence-based frameworks for designing AI-driven immersive learning environments that are inclusive, scalable, and effective in addressing the literacy crisis—empowering learners around the world to develop essential reading and comprehension skills for lifelong success.

There is a growing need for mental health resources, and among those most affected by gaps in care are children and parents. Healthy family dynamics and strong caregiver-child attachment are key indicators of positive outcomes for children, yet traditional therapy and support systems often fall short in meeting these needs.

Our research investigates how immersive technology can help meet the needs of families. We seek to design and develop digital experiences informed by attachment theory, cognitive behavioral therapy, and play therapy. Each intervention is rigorously evaluated to ensure it is human-centered, engaging, and effective in supporting families. By leveraging immersive technology, we aim to create interventions that are scalable, accessible, and enjoyable—meeting families where they are with tools that resonate.

Psychological interventions can significantly boost endurance performance, with studies showing improvements of 2–8%; yet, current coaching methods often fail to deliver support when it's most effective for the individual. Traditional approaches rely on static, fixed-interval cues or self-initiated strategies, ignoring the rider's unique physiological state and moment-to-moment effort perception—the core limiting factor in endurance, according to the psychobiological model of performance. Our project addresses this critical gap by developing an adaptive AI coaching system that learns precisely when motivational support will be most effective for each individual cyclist. This innovative system uses machine learning to analyze real-time physiological data (like heart rate and power output patterns) and deliver personalized verbal affirmations at the optimal moment, aiming to reduce perceived exertion and increase the motivation to tolerate discomfort.

This study's primary objective is to evaluate whether these adaptive, AI-delivered personalized affirmations can enhance indoor cycling power output during a 20-minute time trial compared to static-affirmation and exercise-only control groups. Specifically, we will compare the effectiveness of adaptive vs. static affirmations on key cycling performance metrics, examine the relationship between physiological markers and optimal affirmation timing, and assess the impact on the cyclists' perceived exertion and motivational states. This research is an important step in applying digital media and adaptive machine learning to real-time exercise coaching. If successful, this technology could be seamlessly integrated into commercial cycling apps and smart trainers, democratizing access to highly personalized, effective coaching for people worldwide.

It can be hard to connect with environmental problems that seem invisible or are happening far away, like the slow changes deep in our oceans. Our research uses cutting-edge technologies like virtual reality (VR) to make these issues real and personal. Instead of just reading an article or watching a video, we build experiences that let you feel like you are actually there. You might stand on a melting glacier or swim through a changing coral reef, turning abstract concepts into a powerful, memorable experience that helps you understand the world in a new way.

Our goal is to figure out what makes these virtual experiences truly effective at inspiring people. We study how different design choices—like the stories we tell, the way you interact with the virtual world, and the emotions you feel—can lead to lasting understanding and a stronger motivation to help. By figuring out what works best, we aim to create powerful tools that not only educate but also empower people to engage on positive environmental behaviors.

Multisensory research in extended reality (XR) explores how human perception, cognition, and emotion are shaped through the integration of visual, auditory, and haptic modalities within XR environments. Through technological innovation and interdisciplinary research, this branch of inquiry explores new frontiers of multisensory experiences, aiming to contribute new knowledge to the development of multisensory systems shaping the next generation of intelligent XR environments.

This branch of research operates at the intersection of psychology, design, and technology. Grounded in a phenomenological understanding of perception and embodiment, this research seeks to bridge the divide between physical and virtual experience, investigating how tactile perception, movement, and spatial awareness contribute to discovering new pathways in education, wellbeing, and communication within XR contexts. The objective extends beyond enhancing immersion; it aims to advance human connection, emotional resonance, and cognitive development through multisensory and embodied engagement.

This research area develops methodologies for the verification and validation of cyber-physical systems controlled by artificial intelligence. It addresses the limitations of conventional testing methods to guarantee safety in complex, real-world environments. This issue is especially pressing in safety critical domains, such as autonomous vehicles, where system failures can have catastrophic consequences.

Our core approach employs simulations as virtual testbeds. These virtual worlds provide the scalable, automated, and safe framework needed for rigorous stress testing. This approach allows us to explore countless edge cases that are impractical or too dangerous to test in the real world. In these simulations, we develop and apply novel AI-driven techniques to systematically find system vulnerabilities and accelerate the verification and validation process of cyber-physical systems.