Intro

Hello!

Background

I'm a recent Mathematics graduate from the University of Edinburgh and I'm currently studying an MRes in Statistics and Operational Research at Lancaster University. Upon completing my MRes year, I will start my PhD in a relevant field.

Why I came to STOR-i

During my penultimate year at Edinburgh, I decided to apply to STOR-i's Summer Internship Programme in 2016.

During my time there, I was given the opportunity to experience life as a PhD researcher in the Mathematics and Statistics department.

I spent 8 weeks conducting research on 'Assigning Drones for Military Research', under the supervision of a current STOR-i PhD student. I enjoyed my time there so much so that I decided to return to Lancaster University in October 2017.

Summer Interns at the STOR-i Ball, August 2016

Personal Life

Whilst at university, I have been a enthusiast for learning the Finnish language and culture (and all things Moomin). As for sports, I am a member of Lancaster University's Trampolining Club (LUTC) and Swing Dance society (LUSDA).

Lancaster University Trampolining Club at NEUT Manchester Competition, December 2017

Research

STOR-i's 2017/18 MRes Students

Recommending Mallows | PhD Project

Recommender systems have become prevalent in present-day technological developments. They are machine learning algorithms which make recommendations, by selecting a specific range of items for each individual, which they are most likely to be in interested in. For example, on an e-commerce website, having a search tool or filter is simply not enough to ensure a good user experience. Users want to receive recommendations for things, which they may not have considered or knew existed. The challenge recommender systems face is to sort through a large database and select a small subset of items, which are considered to be the most attractive to each user depending on the context.

In a recommendation setting, we might assume that an individual has specified a ranking of the items available to them. For a group of individuals, we may also assume that a distribution exists over the rankings. The Mallows model can summarise the ranking information in the form of a consensus ranking and a scale parameter value to indicate the variability in rankings within the group of individuals.

We aim to incorporate the Mallows model to a recommender system scenario, where there are thousands of items and individuals. Since the set of items that an individual may be asked to rank is too large, we usually receive data in the form of partial rankings or pairwise comparisons. Therefore, we need to use methods to predict a user's ranking from their preference information. However, many users will be interacting with a recommender system regularly in real time. Here, the system would have to simultaneously learn about its unknown environment that it is operating in whilst choosing alternative items with potentially unknown feedback from users. Hence, the open problem we are most concerned about is how to use the Mallows model to make better recommendations to the users in future.

This project is under the supervision of David Leslie (Lancaster University) and Arnoldo Frigessi (Oslo University).

STOR-i

STOR-i was established in 2010 as an EPSRC Centre for Doctoral Training. It is a joint venture between the departments of Mathematics and Statistics and Management Science, offering a four-year PhD programme in Statistics and Operational Research, developed and delivered with industrial partners.

The first year of the programme (MRes year) comprises of taught courses, problem solving days, group projects and masterclasses, to give students a robust grounding in Statistics and Operational Research, and develop their key research skills. Students then progress to PhD study for the remaining three years. During the four years at STOR-i, students will attend a range of events including regular seminars and forums where visiting lecturers and members of STOR-i present their research.

Internship

STOR-i also offers the opportunity for undergraduates to take part in their eight-week summer internship programme to experience life as a PhD student in the department. I strongly encourage anyone who is interested in the possibility of doing postgraduate study in Statistics and/or Operational Research to apply.

Further information can be found on the here. Applications for the Summer 2018 intake open in December 2017.

Contact

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STOR-i

STOR-i Centre for Doctoral Training
Science and Technology Building
Lancaster University
Lancaster
United Kingdom
LA1 4YR

stor-i@lancaster.ac.uk

+44 (0)1524 593940

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