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Experimental Design and Big Data

8th May, 2015

The amount and quality of information extracted from data is strongly determined by how they were collected. Quoting R.A. Fisher: "To consult the statistician after an experiment is finished is often merely to ask him to conduct a post-mortem examination. He can perhaps say what the experiment died of." Unfortunately, careful design of Big Data collection seems to have been largely overlooked. We aim to discuss current challenges and review some successful approaches in a variety of fields, including efforts to combine clinical trials with personalized medicine, signal acquisition, astronomy and online data collection.


  • Matthias Seeger (Amazon, Germany)
  • Yuan Ji (Director of Biomedical Studies, NorthShore University Health System and Dept. of Health Studies, The University of Chicago)
  • Jason McEwen (UCL)
  • Tristan Henderson (University of Saint Andrews)
  • Camille Stephan-Otto Attolini (IRB Barcelona, Spain)


Full program is available here. Talks will be held in MS.03, Zeeman Building

9.45--10.00 Registration
10.00--10.10 Welcome Address

Session 1
10.10--11.00 Matthias Seeger
Large scale variational Bayesian inference and sequential experimental design for signal acquisition optimization
11.00--11.50 Tristan Henderson
Reliable, reproducible and responsible data collection from online social networks
11.50--12.40 Jason McEwen
Optimising radio interferometric imaging with compressive sensing
12.40--12.50 Floor Discussion

12.50--14.00 Lunch

Session 2
14.00--14.50 Yuan Ji
Subgroup-Based Adaptive (SUBA) Designs for Multi-Arm Biomarker Trials
14.50--15.40 Camille Stephan-Otto Attolini
A Bayesian framework for personalized design in alternative splicing RNA-seq studies
15.40--15.50 Floor Discussion

15.50 End


Registration for this event has now closed. If you would like to be added to the waiting list please email wdsi dot enquiries at warwick dot ac dot uk