I obtained my PhD degree at CBDRH UNSW in Australia. I work as Senior Data Scientist at the Centre for Big Data Research in Health (CBDRH) at University of New South Wales Sydney, and Data Scientist at the George Institute for Global Health (TGI).
The focus of his research is on the utilization of natural language processing and deep learning techniques to extract information from unstructured health data, including clinical notes. His primary research areas involve the de-identification a...
I obtained my PhD degree at CBDRH UNSW in Australia. I work as Senior Data Scientist at the Centre for Big Data Research in Health (CBDRH) at University of New South Wales Sydney, and Data Scientist at the George Institute for Global Health (TGI).
The focus of his research is on the utilization of natural language processing and deep learning techniques to extract information from unstructured health data, including clinical notes. His primary research areas involve the de-identification and clinical coding of free-text data found in electronic medical records (EMRs), and predictive modelling based on brain imaging using convolutional neural networks and transformer-based architectures. He has proposed an end-to-end deep learning-based named entity recognition framework, which effectively removes personally identifiable information (PII) from health free-text data. This framework has been utilized to de-identify clinical notes for the Cardiac Analytics and Innovation (CardiacAI) project. Additionally, he has explored Transformer-based models for clinical coding tasks. He is currently engaged in the Next-generation Clinical Registry project at CBDRH and is leading the machine learning model development for the Outcome PredicTion in IntraCerebral Hemorrhage Study (OPTICS) at TGI.
With his strong machine learning skills, solid software engineering technology background, and expertise in big data analysis and data management, he possesses a unique and valuable combination of knowledge and skills.
