Postgraduate Thesis - Explainable AI for Medical Diagnosis
Quantitative evaluation of explainable AI methods such as SHAP, LIME, and Integrated Gradients for skin cancer diagnosis models. Focused on enhancing the interpretability and trust in AI-based medical tools.
- Technologies: TensorFlow, Python, SHAP, LIME
- Impact: Improved model transparency in clinical settings.
BioRobotics Human Modelling Lab
Worked on developing a haptic lift assist device for General Motors to improve industrial assembly processes. Focused on human-machine interaction for enhanced safety and efficiency.
Humor Genome Project
Developed classifiers and recommendation algorithms for analysing humour using NLP and machine learning.
Project DetailsNotable Coursework
- Graduate Coursework (King's College London):
- Advanced Machine Learning for Engineers
- Systems and Controls
- Project Management
- Product Management
- Intelligence and Autonomy
- Undergraduate Coursework (Georgia Institute of Technology):
- Machine Learning and Applications
- Algorithms and Data Structures
- System Design and Modelling
- Automata and Complexity Theory
