For people navigating physical or emotional challenges, help isn’t always accessible or easy to seek out. Ontario Tech University researcher Dr. Patrick Hung is exploring how AI-powered social robots could help bridge those gaps, offering new ways to support independence, well-being and everyday interactions.

In the university’s Human Machine Lab, Dr. Hung, Professor, Faculty of Business and Information Technology, leads research applying AI to ‘social’ robots designed to engage with people in meaningful ways. His work brings together machine learning, computer vision and language models with a clear guiding principle: AI works for humans, not to replace them.

Preparing for life with a guide dog through AI-assisted training

Guide dogs can play an important role in enhancing mobility, confidence and independence in daily life for people with sight loss. But those applying for guide-dog programs may wait two to three years just to progress through the early stages of the process. During that time, opportunities to build familiarity with guide-dog handling are limited.

In partnership with the Canadian National Institute for the Blind (CNIB), Dr. Hung’s lab is developing a robotic guide dog to help individuals learn and practice key skills before receiving a real guide dog.

“We’re not going to replace the real guide dog,” Dr. Hung explains. “We just provide a technology to train the person before they get the real dog. This way we shorten the window of waiting for training.”

Using AI for mental wellness and reflection

To explore how social robotics can complement traditional mental-health supports, Dr. Hung’s lab, in co-operation with Hongik University in Mapo, Seoul, South Korea, has developed a Buddha-inspired robot modelled on a centuries-old statue from the National Museum of Korea. The robot brings a cultural symbol into a contemporary setting: through a combination of a physical form and an immersive digital experience using a virtual reality headset, users are guided through a quiet, structured moment of reflection.

“This project shows how AI can be experienced differently: as something people can engage with more directly to get help when they need it,” Dr. Hung says.

Students exploring how people experience and trust AI

Dr. Hung’s lab emphasizes co-design and real-world testing, with students regularly bringing prototypes into the community to gather feedback. “We don’t just hide ourselves in the lab and try to solve the problem,” he says. “We go out, talk to real people, and then build a prototype, test it, collect insights and keep refining it.”

This human-centred approach also influences how his team studies trust and adoption, recognizing that public perception and acceptance of robots in everyday life is just as important as the development of the technology itself.

Dr. Hung’s students gain hands-on experience in technical development while applying their work in practical settings. Carlos Carrasco (Master of Science in Computer Science, class of 2026), joined the lab with a background in Mechatronics Engineering and a long-standing passion for building things. In Dr. Hung’s lab, Carrasco’s work bridges engineering and human experience: building robots while helping deploy them in environments like hospitals and community organizations.

Through this work, Carrasco has gained insight into the potential and limitations of AI. Students are encouraged to use AI as a productivity tool while remaining transparent and accountable in how they apply it. “You should be open about it: ‘Yes, I did this with AI, but it’s still my work,’” he says.

At the same time, he stresses the importance of human oversight: “Can you depend fully on AI? Absolutely not.”

One of the most meaningful aspects of the research is seeing it come to life in front of people. When community members interact with robots, it often changes their understanding of what AI can be.

“When people think of AI, they think of ChatGPT, Gemini, or other big LLM models that are essentially another version of Googling something,” Carrasco says. “But in this lab we’re seeing how AI is more of a complex engine, and how it can get inside different projects.”

The opportunity to explore AI openly while learning how to use it ethically has been an especially valuable part of his academic journey. “That’s one of the things I appreciate most about how we approach AI at Ontario Tech: using it as a productivity tool while recognizing where human judgment still matters,” he says.