Schedule

The 2017 conference schedule is below:

Day 1: Monday 26 June 2017

09.00 - Registration desk opens
09.25 – 09.30 Dean’s Opening Remarks - Prof Ivan Parkin, Dean of UCL Mathematics & Physical Sciences Faculty
09.30 - 09.40 Conference Chairs’ Opening Remarks – Prof Sofia Olhede & Prof Patrick Wolfe (UCL Centre for Data Science)
09.40 – 10.20 Tensors & Statistical Modelling – Low rank tensor completion - Prof Ming Yuan (University of Wisconsin-Madison)
10.20 – 11.00 Tensors & Statistical Modelling - Adaptive inference for matrices and tensors – Prof Peter Hoff (Duke University)
11.00 – 11.30 Coffee
11.30 – 12.10 Tensors & Statistical Modelling – Dealing with curse and blessing of dimensionality through tensor decompositions - Prof Lieven De Lathauwer (KU Leuven)
12.10 – 12.50 Tensors & Statistical Modelling - Scaling Latent Quantities from Text: From Black-and-White to Shades of Gray – Dr Patrick Perry (NYU Stern)
12.50 – 14.00 Lunch
14.00 – 14.40 Privacy-preserving inference – Towards Encrypted Inference for Arbitrary Models - Dr Louis Aslett (Durham)
14.40 – 15.20 Privacy-preserving inference – M2L: Bringing the Machine into the loop of Machine Learning - Prof Farinaz Koushanfar (UCSD)
15.20 – 16.00 Privacy-preserving inference - Building and Measuring Privacy-Preserving Mobility Analytics - Dr Emiliano de Cristofaro (UCL)
16.00 – 17.00 Afternoon tea and networking

 

Day 2: Tuesday 27 June 2017

08.45 - Registration desk opens
09.05 – 09.10 Opening remarks, day 2 – Prof Patrick Wolfe & Prof Sofia Olhede (UCL Centre for Data Science)
09.10 - 09.50 Challenges in spatial & temporal analysis – Big Data in Cosmology - Dr Jason McEwen (UCL)
09.50 - 10.30 Challenges in spatial & temporal analysis: Spectal filtering for spatial-temporal dynamics - Dr Tian Zheng (Columbia)
10.30 – 11.00 Coffee
11.00 – 11.40 Challenges in spatial & temporal analysis – Network Time Series – Prof Guy Nason (Bristol)
11.40 - 12.20 Challenges in spatial & temporal analysis – Evaluating modules in molecular networks in light of annotation bias - Prof Charlotte Deane (Oxford)
Turing Gateway to Mathematics event: Data Sharing & Governance
12.20 - 13.30 Registration, Lunch and Tea/Coffee
13.30 - 13.50 Welcome and Introduction – Jane Leeks (Turing Gateway to Mathematics) / Profs Patrick Wolfe & Sofia Olhede (University College London)
Setting the scene, Royal Society & British Academy Data Governance Project, etc.
13.50 – 14.20 Big Data and Data Sharing (Prof David Hand, Imperial)
14.20 – 14.50 Using Data from Healthcare and other Public Services (Prof Ruth Gilbert, UCL)
14.50 – 15.10 Cross-industry data sharing collaboration (Thomas Nielson, Tesco Digital)
15.10 – 15.30 Tea
15.30 – 15.50 The Opportunity to Leverage Electronic Health and Medical Records (Tom O’Leary, Icon PLC)
15.50 – 16.20 Sharing Consumer Data (Paul Longley, UCL)
16.20 – 16.50 Statistics and Research for the Public Good: Principles and Safeguarding Public Trust (Ross Young & Peter Stokes, ONS)
16.50 – 17.10 Questions and wrap-up
17.10 – 18.10 Networking and Drinks Reception

 

Day 3: Wednesday 28 June 2017

08.45 - Registration desk opens
09.10 – 09.15 Opening remarks, day 3 – Prof Sofia Olhede & Prof Patrick Wolfe (UCL Centre for Data Science)
09:15 – 10:15 Plenary - Data, data everywhere, but let’s just stop and think - Prof David Hand (Imperial College London)
10.15 – 10.45 Break
10.45 - 12.30 Short Contributed talks (15 mins each + 5 mins questions)
1. The Finite-Set Independence Criterion (Jitkrittum et al.) – view abstract
2. Quantile Graphical Models: Prediction and Conditional Independence with Applications to Financial Risk Management (Belloni et al.) – view abstract
3. Poisson intensity estimation with reproducing kernels (Flaxman et al.) – view abstract
4. What are the true clusters? (Hennig) – view abstract
5. Statistical Inference for Pairwise Graphical Models Using Score Matching (Yu et al.) – view abstract
12.30 – 14.00 Lunch and Poster Presentations – view Poster abstracts
14.00 - 14.40 High-dimensional estimation and learning – Exponentially Weighted Aggregate with the Laplace Prior – Prof Arnak Dalalyan (ENSAE ParisTech)
14.40 – 15.20 High-dimensional estimation and learning – Overlapping Variable Clustering with Statistical Guarantees – Prof Marten Wegkamp (Cornell)
15.20 – 15.50 Tea
15.50 – 16.30 High-dimensional estimation and learning - Large-scale and supersaturated studies: statistical considerations – Dr Heather Battey (Imperial)
16.30 – 17.10 High-dimensional estimation and learning – Interpretable features to compare distributions in linear time - Dr Arthur Gretton (UCL)
17.10 – 17.15 Closing Remarks (Profs Sofia Olhede & Patrick Wolfe, UCL)