L4

The smooth representation theory of a p-adic reductive group G

with characteristic zero coefficients is very closely connected to the

module theory of its (pro-p) Iwahori-Hecke algebra H(G). In the modular

case, where the coefficients have characteristic p, this connection

breaks down to a large extent. I will first explain how this connection

can be reinstated by passing to a derived setting. It involves a certain

differential graded algebra whose zeroth cohomology is H(G). Then I will

report on a joint project with

R. Ollivier in which we analyze the higher cohomology groups of this dg

algebra for the group G = SL_2.

The smooth representation theory of a p-adic reductive group G with characteristic zero coefficients is very closely connected to the module theory of its (pro-p) Iwahori-Hecke algebra H(G). In the modular case, where the coefficients have characteristic p, this connection breaks down to a large extent. I will first explain how this connection can be reinstated by passing to a derived setting. It involves a certain differential graded algebra whose zeroth cohomology is H(G). Then I will report on a joint project with R. Ollivier in which we analyze the higher cohomology groups of this dg algebra for the group G = SL_2.

Niall Bootland (Scalable Two-Phase Flow Solvers)

Sourav Mondal (Electrohydrodynamics in microchannel)

Abstract: Flow of liquid due to an electric potential gradient is possible when the channel walls bear a surface charge and liquid contains free charges (electrolyte). Inclusion of electrokinetic effects in microchannel flows has an added advantage over Poiseuille flow - depending upon the electrolyte concentration, the Debye layer thickness is different, which allows for tuning of flow profiles and the associated mass transport. The developed mathematical model helps in probing the mass transfer effects through a porous walled microchannel induced by electrokinetic forces.

Dstl are interested in removing liquid contaminants from capillary features (cracks in surfaces, screw threads etc.). We speculated that liquid decontaminants with low surface tension would have beneficial properties. The colloid literature, and in particular the oil recovery literature, discusss the properties of multiphase systems in terms of “Winsor types”, typically consisting of “brine” (water + electrolyte), “oil” (non-polar, water-insoluble solvent) and surfactant. Winsor I systems are oil-in-water microemulsions and Winsor II systems are water-in-oil microemulsions. Under certain circumstances, the mixture will separate into three phases. The middle (Winsor III) phase is surfactant-rich, and is reported to exhibit ultra-low surface tension. The glycol ethers (“Cellosolve” type solvents) consist of short (3-4) linked ether groups attached to short (3-4 carbon) alkyl chains. Although these materials would not normally be considered to be surfactants, their polar head, non-polar tail properties allow them to form a “surfactantless” Winsor III middle phase. We have found that small changes in temperature, electrolyte concentration or addition of contaminant can cause these novel colloids to phase separate. In our decontamination experiments, we have observed that contaminant-induced phase separation takes the form of droplets of the separating phase. These droplets are highly mobile, exhibiting behaviour that is visually similar to Brownian motion, which induces somewhat turbulent liquid currents in the vicinity of the contaminant. We tentatively attribute this behaviour to the Marangoni effect. We present our work as an interesting physics/ physical chemistry phenomenon that should be suitable for mathematical analysis.

Currently all medical x-ray imaging is performed using point-like sources which produce cone or fan beams. In planar radiology the source is fixed relative to the patient and detector array and therefore only 2D images can be produced. In CT imaging, the source and detector are rotated about the patient and through reconstruction (such as Radon methods), a 3D image can be formed. In Tomosynthesis, a limited range of angles are captured which greatly reduces the complexity and cost of the device and the dose exposure to the patient while largely preserving the clinical utility of the 3D images. Conventional tomosynthesis relies on mechanically moving a source about a fixed trajectory (e.g. an arc) and capturing multiple images along that path. Adaptix is developing a fixed source with an electronically addressable array that allows for a motion-free tomosynthesis system. The Adaptix approach has many advantages including reduced cost, portability, angular information acquired in 2D, and the ability to shape the radiation field (by selectively activating only certain emitters).

The proposed work would examine the effects of patient motion and apply suitable corrections to the image reconstruction (or raw data). Many approaches have been considered in the literature for motion correction, and only some of these may be of use in tomosynthesis. The study will consider which approaches are optimal, and apply them to the present geometry.

A related but perhaps distinct area of investigation is the use of “structured light” techniques to encode the x-rays and extract additional information from the imaging. Most conventional structured light approaches are not suitable for transmissive operation nor for the limited control available in x-rays. Selection of appropriate techniques and algorithms, however, could prove very powerful and yield new ways of performing medical imaging.

Adaptix is a start-up based at the Begbroke Centre for Innovation and Enterprise. Adaptix is transforming planar X-ray – the diagnostic imaging modality most widely used in healthcare worldwide. We are adding low-dose 3D capability – digital tomosynthesis - to planar X-ray while making it more affordable and truly portable so radiology can more easily travel to the patient. This transformation will enhance patient’s access to the world’s most important imaging technologies and likely increases the diagnostic accuracy for many high incidence conditions such as cardiovascular and pulmonary diseases, lung cancer and osteoporosis. 
 

Hotels.com is one of the world’s leading accommodation booking websites featuring an inventory of around 300.000 hotels and 100s of millions of users. A crucial part of our business is to act as an agent between these two sides of the market, thus reducing search costs and information asymmetries to enable our visitors to find the right hotel in the most efficient way.

From this point of view selling hotels is one large recommendation challenge: given a set of items and a set of observed choices/ratings, identify a user’s preference profile.  Over the last years this particular problem has been intensively studied by a strongly interdisciplinary field based on ideas from choice theory, linear algebra, statistics, computer science and machine learning. This pluralism is reflected in the broad array of techniques that are used in today’s industry applications, i.e. collaborative filtering, matrix factorization, graph-based algorithms, decision trees or generalized linear models.

The aim of this workshop is twofold.

Firstly we want to give some insight into the statistical modelling techniques and assumptions employed at hotels.com, the practical challenges one has to face when designing a flexible and scalable recommender system and potential gaps between current research and real-world applications.

Secondly we are going to consider some more advanced questions around learning to rank from partial/incomplete feedback (1), dealing with selection-bias correction (2) and how econometrics and behavioral theory (eg Luce, Kahneman /Tversky) can be used to complement existing techniques (3).