Chirath Hettiarachchi received his BSc (Hons) degree in Electronics & Telecommunication Engineering in 2018 from the University of Moratuwa, Sri Lanka. He completed his professional qualification in Management Accounting at the Chartered Institute of Management Accountants in 2014 (CIMA-UK). He worked as a Machine Learning Engineer in the FinTech industry from 2018 - 2019, developing algorithms for identifying outliers in corporate financial transactions, forecasting, name screening and risk prediction applications. During the final year of his undergraduate studies, he pursued his entrepreneurial aspirations by co-founding a healthcare startup which achieved multiple awards and publications.
Following his passion on research & development of healthcare technologies, he completed an MSc (Research) degree at the Department of Computer Science & Engineering, University of Moratuwa in 2020. His research focused on exploring Photoplethysmography (PPG) signals & Machine Learning (ML) towards Type 2 Diabetes estimation. Currently he is pursuing his PhD at the Australian National University, in the Big Data program of the “Our Health In Our Hands (OHIOH)” project, a strategic initiative of the university, where he works on using ML to develop a control system for the artificial pancreas. His research interests include ML, reinforcement learning, control systems, biomedical signal processing, health informatics and financial data analytics.
- Machine Learning
- Health Informatics
- Control Systems
- Signal Processing
- Hettiarachchi, Chirath, et al. "A Wearable System to Analyze the Human Arm for Predicting Injuries Due to Throwing."; 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2019.
- Hettiarachchi, Chirath, and Charith Chitraranjan. "A Machine Learning Approach to Predict Diabetes Using Short Recorded Photoplethysmography and Physiological Characteristics." Conference on Artificial Intelligence in Medicine in Europe. Springer, Cham, 2019.
- Hettiarachchi, Chirath, Buddhishan Manamperi, and Dilshan Uthpala. "Identifying the Optimum Region of the Human Sole to Extract the PPG Signal for Pulse Rate Estimation." Proceedings of the 9th International Conference on Signal Processing Systems. 2017.