Yunjie Yang

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What is your research focus?  

My research focus lies in the areas of sensing and imaging with AI-powered tomography, machine learning, digital twins, and flexible sensors for wearables and robotics. It originated during my Ph.D. studies at The University of Edinburgh, where I delved into the field of engineering electronics. Initially, my research centered around developing techniques to improve observability in industrial applications, specifically multiphase flows.

Over time, my research has evolved and expanded to encompass a broader range of interdisciplinary domains. I have extended my work to include robotics, particularly soft robotics, and biomedical engineering. This expansion has allowed me to explore the pressing challenges associated with efficiently utilising and interpreting vast amounts of sensory data. I have been investigating novel approaches that leverage AI and machine learning to enhance the capabilities of tomography and develop intelligent sensing systems.

The evolution of my research has been driven by the need to address real-world problems and bridge the gap between academic research and practical applications. By integrating advancements in AI, machine learning, and flexible sensor technologies, my research has sought to improve the understanding of complex systems in various fields.

What is your innovation idea? 

My innovation idea revolves around the development and deployment of flexible perception systems empowered by machine learning for soft robots. I developed a smart electronic skin which is like a "smart" layer that can be used on soft robots. It helps these robots understand and "feel" their environment by detecting changes in shape and movement.

This technology can be very helpful in improving the control and accuracy of soft robots, which are robots made of soft materials. It can also have important applications in fields like prosthetics, where it could be used to make more natural-feeling artificial limbs, wearable technology that can sense and respond to movement in real time, or the next generation of soft surgical robots that can feel touch and its shape within the human body.

Why does this idea matter, what impact will it have on the world and what problem will it solve? 

Soft robotics as an emerging robotics technology is the strategic focus of the UK and many other countries around the world. It holds great promise to create next-generation robotic systems that can better interact with humans and the environment. However, perceiving body motion and environmental stimuli such as touch have been challenging and the bottleneck of soft robots. This idea holds significant importance due to its potential to address such critical challenges and has a transformative impact. The e-skin can achieve simultaneous body shape and tactile sensing and can be seamlessly integrated with the robots. These breakthroughs will push the boundaries of what is currently possible. This will eventually facilitate the wide adoption of soft robots in significant social areas, such as healthcare, assisted living and industrial automation, thus revolutionising healthcare delivery and improving the quality of life for individuals.

Personally, this idea matters to me because it aligns with my passion for leveraging cutting-edge technologies to solve real-world problems. It offers an opportunity to bridge the gap between academia and industry, translating research into practical applications that have a positive impact.

What is the future of your research?

In the future, I envision further advancements in smart sensing and perception systems by integrating emerging technologies such as multi-modality sensors, advanced materials, edge computing, and advanced data analytics. There is immense potential to enhance the capabilities of perception capability of future machines by enabling edge intelligence and seamless connectivity with other devices and platforms.

Currently, I am leading a team to develop the first perceptive soft surgical robots, which aims to construct a surgical robot that is safer, more environment-friendly, and can better perceive its own movement, body shape and surroundings. I believe there is scope for exploring many other new applications and domains where intelligent perception systems can make a significant impact. This includes areas such as space and deep sea exploration, environmental monitoring, agriculture, and human-robot interaction.

What motivated you to apply to the Bayes Innovation Fellows programme and what do you hope to gain from it?

I applied to this programme because I saw it as a tremendous opportunity to advance my research translation and make an impact. The program's focus on research commercialisation and its comprehensive support structure stood out to me. I believe that participating in this program will provide me with the guidance, resources, and exposure needed to translate my research into real-world applications. The support offered by the program will enable me to develop a strong entrepreneurial mindset and gain essential skills in navigating the complexities of commercialisation.

Additionally, the program's emphasis on exposure to the research commercialisation ecosystem is highly appealing. Collaborating with private and public sector partners will not only enhance the relevance and applicability of my research but also foster connections and potential future collaborations. I am also excited about the program's integration with the Venture Builder Incubator and AI Accelerator programs. This integration offers a pathway for sustained support and growth beyond the fellowship period, ensuring that the impact of my research can be further developed and leveraged for commercial success.

I hope to gain a deeper understanding of the research commercialisation process, acquire entrepreneurial skills, establish meaningful collaborations through this program, and eventually accelerate the translation of my research outcomes. By participating in the Bayes Innovation Fellows program, I aim to bridge the gap between academia and industry, solve real-world problems, and contribute to the advancement of knowledge and innovation, especially in the field of robotics perception.

Links

School of Engineering