I am a Lecturer in Computer Science. My research interests are machine learning and its various applications such as behaviour analysis, wearable and ubiquitous computing, etc.
My research agenda is to develop practical AI tools for solving the challenges of real-world applications. In essence, it is to model the practical problems using mathematical languages and develop machine learning algorithms for the optimal solution, bridging the gap between signal/data and human-understandable knowledge. I have extensive experience working with time-series data, such as biosignals, which have broad applications in physical behaviour assessment, health, and well-being monitoring, etc. I am also developed mechanisms for increasing the transparency/interpretability of complex AI models, which is crucial for many applications such as automated medical diagnosis.
Area of expertise: Machine Learning, Activity Recognition, Automated Health Assessment, Wearable/Ubiquitous Computing.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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