James Hinns

XAI PhD Candidate at the University of Antwerp.

  • Research interests include:
    • XAI
    • Deep ML
    • Visualisation
    • Uncertainty Quantification
  • Mediocre Climber and Musician

About Me

I am a committed computer scientist specialising in explainable AI. My academic journey, from a Bachelor's degree in Computer Science to a Master’s focusing on explainable AI, and currently a PhD researching multi-modal counterfactual explanations, has consistently emphasised the development and evaluation of reliable and fair machine learning methods. Since my Bachelor’s, I have taken on teaching responsibilities, including lecturing, leading lab sessions, and supervising Master’s theses, cementing my expertise and further contributing to the academic community through conference publications and presentations. I aim to leverage these experiences to advance the field of interpretable machine learning.

Publications

For the most up-to-date list of my publications, please visit my Google Scholar profile.

Research Interests

As a PhD student in Explainable AI, I am deeply invested in advancing the state of AI and its explainability. My primary areas of interest are:

Explainable AI (XAI)

Leading my PhD research in this domain, I'm exploring methods to make AI models more interpretable and transparent.

Deep Machine Learning

Understanding the intricacies of deep neural networks and how they can be optimised for various applications.

Visualisation

Employing visual techniques to better understand and represent complex data and AI model outputs.

Uncertainty Quantification

Investigating methods to quantify and manage uncertainty in AI models to improve their reliability and robustness.