Just read the news that my friend [and co-author] Arnaud Doucet (Oxford) is the winner of the 2020 Guy Silver Medal award from the Royal Statistical Society. I was also please to learn about David Spiegelhalter‘s Guy Gold medal (I first met David at the fourth Valencia Bayesian meeting in 1991, where he had a poster on the very early stages of BUGS) and Byron Morgan‘s Barnett Award for his indeed remarkable work on statistical ecology and in particular Bayesian capture recapture models. Congrats to all six recipients!
Archive for Arnaud Doucet
learning and inference for medical discovery in Oxford [postdoc]
Posted in Kids, pictures, Statistics, Travel, University life with tags Arnaud Doucet, England, Great-Britain, medical statistics, postdoctoral position, UCLA, University of Oxford on January 10, 2017 by xi'an[Here is a call for a two-year postdoc in Oxford sent to me by Arnaud Doucet. For those worried about moving to Britain, I think that, given the current pace—or lack thereof—of the negotiations with the EU, it is very likely that Britain will not have Brexited two years from now.]
Numerous medical problems ranging from screening to diagnosis to treatment of chronic diseases to management of care in hospitals requires the development of novel statistical models and methods. These models and methods need to address the unique characteristics of medical data such as sampling bias, heterogeneity, non-stationarity, informative censoring etc. Existing state-of-the-art machine learning and statistics techniques often fail to exploit those characteristics. Additionally, the focus needs to be on probabilistic models which are
interpretable by the clinicians so that the inference results can be integrated within the medical-decision making.
We have access to unique datasets for clinical deterioration of patients in the hospital, for cancer screening, and for treatment of chronic diseases. Preliminary work has been tested and implemented at UCLA Medical Center, resulting in significantly management care in this hospital.
The successful applicant will be expected to develop new probabilistic models and learning methods inspired by these applications. The focus will be primarily on methodological and theoretical developments, and involve collaborating with Oxford researchers in machine learning, computational statistics and medicine to bring these developments to practice.
The post-doctoral researcher will be jointly supervised by Prof. Mihaela van der Schaar and Prof. Arnaud Doucet. Both of them have a strong track-record in advising PhD students and post-doctoral researchers who subsequently became successful academics in statistics, engineering sciences, computer science and economics. The position is for 2 years.
afternoon on Bayesian computation
Posted in Statistics, Travel, University life with tags advanced Monte Carlo methods, Antonietta Mira, Arnaud Doucet, Bayesian computation, CRiSM, estimating a constant, Ingmar Schuster, Monte Carlo Statistical Methods, pub, United Kingdom, Université Paris Dauphine, University of Oxford, University of Reading, University of Warwick on April 6, 2016 by xi'anRichard Everitt organises an afternoon workshop on Bayesian computation in Reading, UK, on April 19, the day before the Estimating Constant workshop in Warwick, following a successful afternoon last year. Here is the programme:
1230-1315 Antonietta Mira, Università della Svizzera italiana 1315-1345 Ingmar Schuster, Université Paris-Dauphine 1345-1415 Francois-Xavier Briol, University of Warwick 1415-1445 Jack Baker, University of Lancaster 1445-1515 Alexander Mihailov, University of Reading 1515-1545 Coffee break 1545-1630 Arnaud Doucet, University of Oxford 1630-1700 Philip Maybank, University of Reading 1700-1730 Elske van der Vaart, University of Reading 1730-1800 Reham Badawy, Aston University 1815-late Pub and food (SCR, UoR campus)
and the general abstract:
The Bayesian approach to statistical inference has seen major successes in the past twenty years, finding application in many areas of science, engineering, finance and elsewhere. The main drivers of these successes were developments in Monte Carlo methods and the wide availability of desktop computers. More recently, the use of standard Monte Carlo methods has become infeasible due the size and complexity of data now available. This has been countered by the development of next-generation Monte Carlo techniques, which are the topic of this meeting.
The meeting takes place in the Nike Lecture Theatre, Agriculture Building [building number 59].