Michael Brodie, Research Scientist, CSAIL, MIT


michaelbrodie bio"On Data, The World’s Most Valuable Resource, and Data Science"


- Thursday 26/10, 09:00           

Short bio:


Dr. Michael L. Brodie is a research scientist in the Computer Science and Artificial Intelligence Lab at MIT. As Chief Scientist of Verizon, the 2nd largest Telco in the world, for 25 years, he has a keen interest in advanced technology and its applications in the real world. His responsibility on the Scientific Advisory Board of two of the world’s 60+ Data Science Research Institutes [Insight Center for Data Analytics, Ireland, (2015-), and Swinburne Data Science Research Institute (2017-)] is to understand the opportunities, state of the art, and research challenges for the emerging discipline of Data Science. This lecture presents the Big Picture of Big Data and of Data Science and the consequent revolutions in science and industry.






Data is being conceived as having potential for transforming all human endeavors for which adequate data is available. While data analytics has been used since before Pharaonic Egypt, it is now becoming a powerful force in discovery and prediction, notwithstanding domain expertise, e.g., in economics, that economic trends are inherently unpredictable. On the other hand, data science has led to accelerating discovery in many domains, e.g., cancer cures, exoplanets, paleontology, FinTech, and retail optimization. Equally powerful threats abound, e.g., influencing the 2016 US election.

Seven of the world’s largest ten enterprises are data-driven companies, mere startups two decades ago. To compete, corporations are transforming themselves to be data-driven. Based on Big Data and Data Science, science, engineering, and the humanities are entering the 5th paradigm of discovery. Every major university has developed a Data Science Research Institute (DSRI) most within the last two years. Yet, Data Science is in its infancy without adequate principles to distinguish correlation from causation.

This keynote explores the emergence of Big Data and Data Science by looking at the state of the art, industrial use cases, and research conducted in DSRIs.






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