Dr Yiyang Ge joined King's College London in January 2025 and is currently working within Dr Raquel Iniesta's group, focusing on Topological Data Analysis (TDA). He holds a master’s degree from the University of Sydney, where he specialised in machine learning, and earned his PhD from King’s College London, with a research focus on TDA.

His work explores the intersection of topology and data science, applying advanced mathematical frameworks to extract meaningful insights from complex, high-dimensional data structures.

His research interests include the development of new topological methods for data analysis, the integration of TDA techniques into machine learning models, and their applications in real-world problems, such as precision medicine and healthcare. By leveraging TDA, he aims to enhance the interpretability and robustness of machine learning models, particularly in cases where traditional approaches struggle with intricate data patterns.

His current research focuses on evaluating the quality of missing data imputation using TDA. By leveraging TDA, he aims to investigate whether and to what extent imputed data preserves the intrinsic data topology by quantifying the structural differences between complete and imputed datasets. TDA provides a robust framework for analysing data structure, offering insights that enhance the reliability and interpretability of machine learning models.

Research interests

• Machine Learning for Precision Medicine
• Topological Data Analysis