Ziqiu Jiang
Project: Explaining structure-property relations in the materials space
Supervisors: Vitaliy Kurlin, Andy Cooper
What inspired you to pursue this project and join the DAMC CDT?
During my previous research, I developed protein invariants designed to enhance dataset quality and facilitate more accurate protein folding predictions. This experience solidified my motivation to pursue a PhD: I am driven by the transition of theoretical mathematics into functional, real-world applications.
I chose this specific project because it extends my work on protein structural invariants. The DAMC CDT is the ideal environment for this work due to its emphasis on digital analysis and interdisciplinary collaboration. My background includes a 20-week intensive Data Science program and experience collaborating with hardware engineers and medical students on diagnostic devices. This cohort-based model aligns with my belief that the most significant breakthroughs in structural chemistry occur at the intersection of data science, chemistry, and mathematics. I am committed to contributing my expertise in computer science, while supporting my peers through the CDT’s collaborative framework.
What is your research project about, and what impact do you hope it will have?
My research focuses on the development and application of mathematical descriptors to characterize structure-property relationships in crystalline materials. By leveraging large-scale datasets such as the Cambridge Structural Database (CSD) and the Protein Data Bank (PDB), I aim to optimize the search space for new materials. The core of the project involves improving the structural representations to better predict properties of materials. This objective is significant because traditional methods are computationally expensive and time-consuming, while AI-powered methods remains a 'black box' with little interpretation. I hope to develop a robust framework that allows researchers to propose specific target properties and efficiently identify the corresponding material structures. Ultimately, this work seeks to accelerate the discovery of functional materials essential for future technological advancements, bridging the gap between abstract mathematical theory and tangible chemical engineering.
What has been the most exciting or rewarding part of your PhD journey so far and how does your project benefit from being part of an interdisciplinary CDT?
The most rewarding aspect of my journey has been the synthesis of different fields. Specifically, applying new algorithms to material structures has been providing fresh perspectives on interpretation of material structure and properties. My project benefits immensely from the DAMC CDT’s interdisciplinary structure. The complexity of chemical materials cannot be solved through mathematics alone; it requires the integration of software engineering, data science, and domain-specific chemical insights. Being part of a CDT allows me to gain more foundational knowledge and different insights from peers in different area.