We are delighted to announce our complete list of keynote speakers for the upcomingDataTech19 conference (organised by The Data Lab as part of DataFest), which now includes Debbie Bard, expert in machine learning at scale and data-intensive computing for experimental science, from the National Energy Research Scientific Computing Center(NERSC).
With this update, we would like to take the opportunity to extend the deadline for talk/poster proposals until the 9th of December 2018 (more details below).
DataTech19 will welcome members of industry, the public sector, and academia alike for a day of technical discussions surrounding important topics in data science. Join us on 14 March 2019, in Edinburgh, to share emerging research, technical expertise, and engage in networking and collaboration with other data scientists, analysts, developers, and engineers.
Debbie Bard will be joining us as keynote speaker at DataTech19, alongside Jared Lander, Chief Data Scientist of Lander Analytics and Adjunct Professor of Statistics at Columbia University, and Mine Çetinkaya-Rundel, Associate Professor of the Practice, Duke University, and Data Scientist + Professional Educator, RStudio.
Debbie leads the Data Science Engagement Group at the NERSC at Berkeley National Lab. 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) National Accelerator Laboratory 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.
To join data science experts such as Jared Lander, Mine Çetinkaya-Rundel and Debbie Bard, consider submitting a talk/poster proposal for DataTech19 before the revised deadline on 9th of December 2018. 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 many more! Find out how to submit your proposal and register to attend here:https://www.datafest.global/data-tech
For any questions, please get in touch at: email@example.com.