Speaker: Cheng Soon Ong, Data61, CSIRO
Machine learning guided scientific experiments
Abstract: The AI hype claims that everything can be solved by AI. The reality is that while there are many exciting advances in recent years, many open problems remain. This high-level scientific talk has three parts. First a description of our experience in CSIRO, where we are researching, developing, and applying machine learning for scientific discovery. Second a deeper dive into a particular example of applying machine learning on a particular problem of DNA design for regulating gene expression, that illustrates the different stages in a scientific experiment. Third an open-ended discussion about methods for adaptive experimental design, where we use machine learning to guide us on what to measure in scientific studies.
Bio: Cheng Soon Ong is a senior principal research scientist at the Statistical Machine Learning Group, Data61, CSIRO, and is the director of the machine learning and artificial intelligence future science platform at CSIRO. He is also an adjunct associate professor at the Australian National University. He is co-author of the textbook Mathematics for Machine Learning, and his career has spanned multiple roles in Malaysia, Germany, Switzerland, and Australia.
About Data Science Seminar
This seminar series is hosted by EECS Data Science.
Venue
https://uqz.zoom.us/j/82950265591