Brexit and ERC funding

The Guardian posted Brexit causes collapse in European research funding for Oxbridge last weekend, yet another article on the negative impact of Brexit (or rather of the non-implementation of the Northern Ireland agreement) on UK research (and in particular Oxford and Cambridge), with the rather obvious remark that hardly any UK-based researcher is now receiving ERC funding. Actually, the only exception (mentioned in the article) happens to be an ERC-Synergy grant where the Oxford team is the only non-EU team in the synergy. This is not the case for our own OCEAN project, where Gareth Roberts at Warwick is funded by the compensation fund set (for now) by the UK Government. The article also mentions that, out of the 150 ERC grants allotted to UK-based researchers last year, about one in eight was activated by the rewarded researcher leaving the UK research sytem. Along with the collapse in foreign students attending UK universities (presumably moving to collapsing further since Sunak’s current government considers them as immigration figures to be curbed!), this state of affairs confirms the degree of absurdity of Brexit, undoubtedly the worst political move of the Century!

 

manifold learning [BNP Seminar, 11/01/23]

An incoming BNP webinar on Zoom by Judith Rousseau and Paul Rosa (U of Oxford), on 11 January at 1700 Greenwich time:

Bayesian nonparametric manifold learning

In high dimensions it is common to assume that the data have a lower dimensional structure. We consider two types of low dimensional structure: in the first part the data is assumed to be concentrated near an unknown low dimensional manifold, in the second case it is assumed to be possibly concentrated on an unknown manifold. In both cases neither the manifold nor the density is known. Atypical example is for noisy observations on an unknown low dimensional manifold.

We first consider a family of Bayesian nonparametric density estimators based on location – scale Gaussian mixture priors and we study the asymptotic properties of the posterior distribution. Our work shows in particular that non conjuguate location-scale Gaussian mixture models can adapt to complex geometries and spatially varying regularity when the density is supported near a low dimensional manifold.

In the second part of the talk we will consider also the case where the distribution is supported on a low dimensional manifold. In this non dominated model,we study different types of posterior contraction rates: Wasserstein and where is the Haussdorff measure on the manifold supporting the density. Some more generic results on Wasserstein contraction rates are also discussed.

 

Poisson-Belgium 0-0

“Statistical match predictions are more accurate than many people realize (…) For the upcoming Qatar World Cup, Penn’s model suggests that Belgium (…) has the highest chances of raising the famous trophy, followed by Brazil”

Even Nature had to get entries on the current football World cup, with a paper on data-analytics reaching football coaches and teams. This is not exactly prime news, as I remember visiting the Department of Statistics of the University of Glasgow in the mid 1990’s and chatting with a very friendly doctoral student who was consulting for the Glasgow Rangers (or Celtics?!) on the side at the time. And went back to Ireland to continue with a local team (Galway?!).

The paper reports on different modellings, including one double-Poisson model by (PhD) Matthew Penn from Oxford and (maths undergraduate) Joanna Marks from Warwick, which presumably resemble the double-Poisson version set by Leonardo Egidi et al. and posted on Andrews’ blog a few days ago. Following an earlier model by my friends Karlis & Ntzoufras in 2003. While predictive models can obviously fail, this attempt is missing Belgium, Germany, Switzerland, Mexico, Uruguay, and Denmark early elimination from the cup. One possible reason imho is that national teams do not play that often when players are employed by different clubs in many counties, hence are hard to assess, but I cannot claim any expertise or interest in the game.

off to BNP!

Today I am off to Chile, to attend the 13th Bayesian non-parametric conference, BNP13. Which follows BNP11 that took place in Paris. And BNP12, which took place in Oxford (just prior to O’Bayes in Warwick, which in retrospect was the wrong strategy as most attendees did not extend their stay…). The programme is quite diverse and exciting, plus involving a lot of friends I had not seen for quite a while (as they weren’t at ISBA in Montréal). And the location is fabulous, sitting by Lake Llanquihue [whose waters may prove too cold!] and facing the [tantalizing] volcán Osorno (2652m). Which was observed by Darwin on his second trip, during a 1835 eruption. (The last eruption was in 1869, hopefully staying the same for the whole week!)

postdoc shortage

An interesting tribune in Nature (30 August) about the difficulty in hiring postdocs… I myself faced this difficulty in the recent years but though it was mostly due to unattractive French salaries and working conditions, or COVID issues (or myself!). Nature mentions politics, economics, ethics, and personal priorities as main reasons for the postdoctoral drought. In Britain, Brexit is definitely a central factor as candidates face enormous bills to secure entry to the United Kingdom (as Hai-Dang Dau, now in Oxford, was explaining to us after his successful PhD defense at ENSAE-CREST this morning). But more globally this may reflect a general exodus from academia towards company jobs, and their much more attractive salaries. Especially in STEM where Amazon and buddies created a new definition of “dream jobs”… Anyway,  I still have a prAirie postdoc position open in Paris Dauphine and the new PariSanté campus provides a great working environment, so feel free to contact me!