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
Deep Reinforcement Learning for Multi-Agent Interaction
Dr Stefano V. Albrecht
Head of the Autonomous Agents Research Group, University of Edinburgh
Tuesday 19 October 2021 at 13:00 GMT
Modeling, testing, and adaptive experimental design in high-throughput cancer drug screens
Dr Wesley Tansey
Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center (USA)
Tuesday 7 December 2021 at 15:00 GMT
Is education AI-ready
Professor Rose Luckin
Learner Centred Design, University College London Knowledge Lab
new date: Tuesday 8 March 2022 at 13:00 GMT
