/tags/2017-fall/index.xml 2017 Fall - McGill Statistics Seminars
  • Our quest for robust time series forecasting at scale

    Date: 2017-09-15 Time: 15:30-16:30 Location: BURN 1205 Abstract: The demand for time series forecasting at Google has grown rapidly along with the company since its founding. Initially, the various business and engineering needs led to a multitude of forecasting approaches, most reliant on direct analyst support. The volume and variety of the approaches, and in some cases their inconsistency, called out for an attempt to unify, automate, and extend forecasting methods, and to distribute the results via tools that could be deployed reliably across the company.
  • Genomics like it's 1960: Inferring human history

    Date: 2017-09-08 Time: 15:30-16:30 Location: BURN 1205 Abstract: A central goal of population genetics is the inference of the biological, evolutionary and demographic forces that shaped human diversity. Large-scale sequencing experiments provide fantastic opportunities to learn about human history and biology if we can overcome computational and statistical challenges. I will discuss how simple mid-century statistical approaches, such as the jackknife and Kolmogorov equations, can be combined in unexpected ways to solve partial differential equations, optimize genomic study design, and learn about the spread of modern humans since our common African origins.