Some of you might be interested to hear an update about the upcoming DataTech19, taking place on 14 March 2019, in Edinburgh (https://datafest.global/data-tech):
- Submission deadline extended to December 9th.
- Keynotes announced (see below).
We are welcoming submissions on topics such as: scaling algorithms, software and hardware to cope with large amounts of data, machine learning techniques, deep learning, data visualisation and query facilities, reproducible and collaborative data science, and more!
The list of keynotes now includes:
- Debbie Bard, expert in machine learning at scale and data-intensive computing for experimental science at NERSC
- Mine Çetinkaya-Rundel, Associate Professor of the Practice, Duke University, and Data Scientist + Professional Educator, RStudio, and
- Jared Lander, Chief Data Scientist of Lander Analytics and Adjunct Professor of Statistics at Columbia University.
Our most recently announced keynote, Debbie Bard, leads the Data Science Engagement Group NERSC. NERSC is the mission supercomputing center for the USA Department of Energy, and supports over 7000 scientists and 700 projects with supercomputing needs. A native of the UK, her career spans research in particle physics, cosmology and computing on both sides of the Atlantic. She obtained her PhD at Edinburgh University, and has worked at Imperial College London as well as the Stanford Linear Accelerator Center (SLAC) in the USA, before joining the Data Department at NERSC, where she focuses on data-intensive computing and research, including supercomputing for experimental science and machine learning at scale.