Dr. Kevin Chai is an Adjunct Associate Professor within the School of Population Health. He provides high-level expertise in data, computing, analytics, and machine learning / artificial intelligence across collaborative research and industry projects.

Kevin holds a PhD in Computer Science from Curtin University. His previous roles include Research Fellow at the University of New South Wales (Centre for Health Informatics) where he developed machine learning and natural language processing models for large medical datasets as well as Data Scientist for Curtin IT Services, and Lead Data Scientist for both the Curtin Institute for Computation and the School of Population Health. His research focuses on applying AI and machine learning to high-impact challenges across health, medicine, engineering, planetary science, the humanities and many other diverse areas of research.

Kevin’s collaborative project experience at Curtin includes but is not limited to developing deep learning models for measuring blood vessel leakages in medical microscopy images with the Curtin Health Innovation Research Institute (CHIRI) for designing drugs to treat cognitive decline diseases, applying natural language processing and machine learning to accelerate systematic reviews of health and medical literature (later commercialised into Research Screener), creating computer vision models to identify and measure craters from satellite imagery of Mars with the Curtin School of Earth and Planetary Sciences and detecting meteors from optical astronomy images with the International Centre for Radio Astronomy Research (ICRAR).

Awards

• 2019: Curtinnovation Finalist Award: Teaching and Learning winner, Research Screener project. https://www.youtube.com/watch?v=OO_ptnEJQi4
• 2019: Pitchfest Finalist and People’s Choice Award: National Physiotherapy Association Conference, Adelaide.
• 2018: Research Screener: applying machine learning techniques to research article screening. EduGrowth LaunchPad Business Start EdTech business plan competition Winner.