Kai possesses a strong academic background, starting with a Bachelor of Science in Biochemistry from the University of Lincoln. Building upon a passion for interdisciplinary research, he pursued a Master’s degree in Bioinformatics at Newcastle University, gaining valuable insights into computational approaches in biological data analysis.

Currently, he is pursuing a Doctorate in Computer Science at the University of Lincoln. His academic journey has been driven by a quest to bridge the gap between traditional biological sciences and cutting-edge computational methods, allowing him to explore novel solutions to complex research questions.

Throughout his academic career, Kai has actively engaged in ground-breaking research. During his Master’s program, he delved into cancer research, employing proteomic analysis of heat shock protein 90 to elucidate its role in tumorigenesis. Subsequently, he ventured into the field of machine learning, focusing on predicting the stability of diverse proteins. His efforts then shifted towards improving healthcare, as he utilized machine learning and biomarker identification techniques to predict disease incidence in osteoarthritis patients using clinical questionnaires and quantified knee MRIs.

Kai’s prior research achievements have not only honed his analytical and technical skills but have also fostered a passion for using innovative computational tools to make significant contributions to biomedical research.

Currently, Kai is actively involved in a collaborative research project that marries his expertise in computer science and biology. Through the power of deep learning, computer vision, and machine learning, the research aims to revolutionize patient care by analysing patient movement to identify biomarkers of various knee conditions.

Employing human pose estimation and human mesh recovery, combined with mathematical approaches and biomechanics, they seek to quantitatively assess patient movement and identify patterns indicative of specific knee conditions. This novel approach has the potential to transform diagnostic accuracy and treatment strategies, paving the way for personalized and effective interventions in orthopaedic healthcare.