The amount of digital data that exists in the world is growing at a rapid rate. Recent years have witnessed a dramatic increase of data in many fields of science and engineering, due to the advancement of sensors, mobile devices, biotechnology, digital communication, and internet applications. Data is generated continuously from multiple sources by companies, users and devices in a huge velocity, volume and variety.
Big data refers to data that is so large that it cannot be processed by using traditional applications. Although significant computer technology exists, new skills are needed to fully understand the power of Big Data. Targeted training in managing, analysing, and interpreting large, complex datasets and high rates of dataflow is provided by the Liverpool Big Data Science (LIV.DAT) Centre for Doctoral Training. The PhD students in the Centre are working on research projects that involve large datasets, from Astrophysics, nuclear and particle physics to accelerator science.
The LIV.DAT Virtual Seminar Autumn Series on Data Intensive Science will cover R&D outside of our centre’s core research areas and give an insight into cutting edge research in this area.
Prof Dr Carsten P Welsch, LIV.DAT Director
Morpheus: A Deep Learning Framework for the Pixel-level Analysis of Astronomical Image Data
Professor Brant Robertson
Dept. of Astronomy and Astrophysics, University of California (UCSC)
Monday 19 October 2020 at 16:00
A Declarative Approach to Distributed Stream Processing
Professor Paul Watson
Computer Science and Director of the Digital Institute, Newcastle University
Monday 9 November 2020 at 14:00
Industrial Data Science, Machine-, Transfer- and Federated Learning
Dr Jana Kemnitz
Senior Data Scientist, Distributed-AI-Systems Research Group Siemens
Monday 7 December 2020 at 14:00
