Jamie Duell, PhD.
Research Fellow in Explainable Artificial Intelligence
Nanyang Technological University, Lee Kong Chian School of Medicine
I carried out my PhD candidature with the UK Research and Innovation CDT in Artificial Intelligence, Machine Learning and Advanced Computing (AIMLAC). I have the desire to help others from a societal stand point through computational research, aiming to facilitate the transparency of Machine Learning methods. The combined experience from my masters and PhD have given me experience in range of fields from - Evolutionary Computing, Computational Intelligence [Machine Learning, Explainable Artificial Intelligence (XAI)] to Robotics. I am driven to pursue a career in academia and thus continue to further my existing knowledge, I strive to be at the forefront of research in XAI. My greatest interests are on the improvement and development of new XAI methods to facilitate medical science. More specifically, my recent interests surround the development of new XAI techniques, that aim leverage quantification of uncertainty in an attempt to produce more realistic explanations. I have also been exploring solutions to missing data, this to facilitate the extraction of knowledge of explanations from previously incomplete data. I possess a desire to learn new methods and implementations frequently, such that one can extract more meaningful explanations and increase the model performance for electronic health records. To help improve patient outcomes, I hope to explore multi-modal data types for medicine, so that I can provide new insights for medical data of different forms. I also wish to dive deeper into the theoretical underpinnings of XAI to produce more robust solutions that provide vaster satisfiability of key XAI properties.