Branch Meeting - Wednesday, 17th June 2020
The South Australian Branch of the Statistical Society would like to invite you to the June meeting of the 2020 program.
Virtual Venue: Join the Zoom meeting using your PC or device https://unisa.zoom.us/j/98123603373?pwd=T29HNlpoSlpSOFVLbm1OWEx6NVNzUT09
or Join from dial-in phone line: Dial: +61 2 8015 2088
Meeting ID: 981 2360 3373
Speaker: Dr Oscar Perez-Concha, The University of New South Wales
Topic: Machine Learning: From damned lies to statistics, where does machine learning lie within the field of data science?
Mark Twain's quote, "Lies, damned lies, and statistics", shows how even over 100 years ago, people were concerned about the power of numbers they did not understand. I think you will agree that machine learning and artificial intelligence have become ubiquitous terms for concepts that promise to change our lives. Many believe that we can apply machine learning to solve any problem related to data; and what is more, that machines can learn without any human intervention. Could such things be true? Coming from a computer science background, my world was always and only machine learning oriented. It was only when I started working in the area of health that i started to be exposed to other statistical techniques. It took me a while to put together the puzzle of where machine learning fits within the broader areas of data science and classical statistical analysis. When I did, I understood the connections and possibilities of them all better.
This presentation tried to take participants along the same journey to an understanding of where machine learning techniques and other techniques lie within data science frameworks.
Dr Oscar Perez-Concha is a health data scientist with almost 15 years' experience in machine learning and statistical modelling. He trained as a telecommunications engineer at the Polytechnic University of Madrid (2003) and completed his PhD in 2008 on the area of machine learning and sequential analysis applied to video surveillance (Carlos III University of Madrid).
Oscar currently works as a Lecturer at the Centre for Big Data Research in Health (CBDRH), UNSW Sydney, where is research focuses on answering questions related to health and healthcare. He applies statistical and machine learning methods to large electronic health record datasets. This is to identify and explore outcomes for these patient groups, improve patient care and make clinical processes more streamlined and effective. Topics of interest include outcomes for sepsis patients; phenotyping ICU patients; and outcomes and health services utilisation for cancer patients.
In addition to these research activities, Oscar is also passionate about teaching and supervising students. In 2017 he developed an introductory course to Machine Learning which he convenes and teaches as part of the UNSW Master of Science in Health Data Science, the first such program in the southern hemisphere. Oscar also supervises master's and PhD students.
Oscar is the founder of the CBDRH Machine Learning Club, a weekly group meeting to discuss ideas about machine learning and its application to health data science. This is an open forum which attempts to break down traditionally siloed views of machine learning and statistics. This has introduced non-specialists from with the UNSW community and beyond to new ideas and methods to help address their research questions. Oscar is also a founder member of the Spanish Researchers Association in Australia-Pacific, which mission is to "disseminate high quality science and facilitate collaboration; aiming to contribute with out work to the cultural enrichment of both Australian and Spanish society".Feel free to forward this meeting notice to colleagues, all welcome.