Statistical Data Science
Date: 3- 5 July 2017
Time: 9:00 – 16:40
Please note, there is a registration fee for this event.
Data science is an emerging discipline, fuelled by continuing advances in technology for data acquisition, storage and curation. Data Science is fundamentally inter-disciplinary, covering computer science and machine learning, mathematics and statistics, and domain knowledge from application areas. The role of statistics in this emerging discipline is unclear.
This conference will feature invited and contributed papers exploring the nature of the relationship between statistics and data science, suggesting state-of-the-art reasoning from both areas, and developing a synergistic path forward.
The conference will feature invited talks by prestigious speakers. In addition, contributed talks are sought. The collection of talks will be published in an edited volume by Word Scientific.
On Computational Thinking, Inferential Thinking and Data Science
Michael Jordan (University of California, Berkeley)
Inference Challenges in Transportation
Emma McCoy (Imperial College London)
Title to be confirmed
Heather Battey (Imperial College London
Evaluating Statistical and Machine Learning Classification Methods
David Hand (Winton, UK)
GCHQ speaker (Government Communications Headquarters)
David Leslie (Lancaster University)
Principled Statistical Inference in Data Science
Alastair Young (Imperial College London)
Data Science in Defence and Security
Mark Briers (The Alan Turing Institute)
Retail Planning in Future Cities: A Stochastic Formulation of a Dynamical Singly Constrained Spatial Interaction Model
Mark Girolami (Imperial College London and The Alan Turing Institute)
Matt Ridley (Winton)