Lídia André

I submitted my PhD thesis in late 2024 under the supervision of Professor Jennifer Wadsworth. The main focus of my PhD was to develop dependence models that provide an accurate representation of multivariate data across the body (defined by non-extreme observations) and the tail (described by large values) regions, without specifying such an extremal region. Motivated by the computational requirements of such models, we later explored likelihood-free approaches to perform inference to aid their routine use.

Since leaving STOR-i, I have taken up a postdoctoral position at Université de Namur, Belgium, where I continue my research in multivariate extreme value theory exploring X-vine models.

Eleanor D'Arcy

I completed my PhD in 2024 under the supervision of Jon Tawn, with a thesis titled "Extreme value methods for protecting and maintaining critical infrastructure from natural hazards." This research was in collaboration with EDF Energy, the Environment Agency and the University of Southampton. Throughout my time at STOR-i, I was encouraged to engage externally, from showcasing my research in competitions such as STEM for Britain and TakeAIM, to developing my communication skills as the Royal Statistical Society’s William Guy Lecturer.

Since completing my PhD, I’ve been working at the Environment Agency as a Senior Statistical Advisor, based in Manchester. I work on the Defra-funded Natural Capital Ecosystem Assessment programme, which is focused on collecting and analysing data on the extent, condition and changes over time of England’s land and water environments, supporting the UK government’s goal of leaving the environment in a better state for future generations. My collaboration with the Environment Agency during my PhD highlighted the vital role of statistics in shaping government and policy decisions, which inspired me to pursue a career in the public sector.

Libby Daniells

I completed my PhD in late 2024, supervised by Professor Thomas Jaki, Dr Pavel Mozgunov, Dr Helen Barnett, along with my industrial supervisor at Roche, Dr Alun Bedding. My PhD looked at various aspects of the design and analysis of basket clinical trials, where I developed and implemented Bayesian information borrowing models to allow for more accurate estimation of treatment response when working with rare diseases.

I am incredibly grateful to have been a part of the STOR-i CDT. The exposure to several areas across statistics and operational research, and the collaboration with others in the centre has truly benefitted me as a researcher. The activities STOR-i provide such as the problem solving days, data-dives, masterclasses and conferences has enabled me to develop communication and research skills that continue to benefit me beyond STOR-i.

Since leaving STOR-i, I have joined the MRC Biostatistics Unit at the University of Cambridge, where I continue to work alongside Professor Thomas Jaki and Dr Pavel Mozgunov on developing novel trial designs and statistical approaches whilst working with clinicians on real-life trials.

Peter Greenstreet

I completed my PhD in 2024 under the supervision of Professor Thomas Jaki and Dr Pavel Mozgunov, along with my industrial supervisors from Roche, Dr Alun Bedding and Chris Harbron. My dissertation was titled "Design and Analysis of Platform Trials."

During my time at STOR-i, I successfully secured a grant from the STOR-i research fund, which provided full funding for a 6-week placement at the Ottawa Hospital Research Institute (OHRI). There, I had the opportunity to shadow Dr Tim Ramsey, the scientific director and senior scientist.

Following my PhD, I undertook a postdoctoral position at the University of Exeter, where I joined the team at Exeter Clinical Trials Unit. In this role, I have been involved in the design, setup, and analysis of multiple clinical trials across various therapeutic areas. I am now preparing to start a new role at OHRI, where I have been awarded the CANSTAT fellowship.

Maddie Smith

I submitted my PhD thesis in September 2024, under the supervision of Dr Adam Sykulski and Dr Nicos Pavlidis. My thesis was entitled "Dynamic forecast combination and problems in multivariate nonstationary time series", and considered how to combine forecasts from multiple sources is a dynamic manner, as well proposing a new model for nonstationary stochastic oscillations.

Since leaving STOR-i, I have been working as a Data Scientist (recently moving companies and gaining a promotion to Data Scientist II - yay!). I currently work as part of the Forecasting team at Flyr for Hospitality, where our product is a revenue strategy platform designed specifically for the hospitality industry. This means that I have an active role in developing the product, rather than just delivering internal data insights, which is great! The team is entirely made up of people with PhDs, so we have a big focus on research and modelling. I spend most of my time developing new forecasting models and assessing their performance, so I get to apply the skills developed in my PhD every day.

George Bolt

I completed my PhD in 2023, under the supervision of Dr Simón Lunagómez (ITAM, Mexico; formerly Lancaster) and Professor Christopher Nemeth (Lancaster). My project was framed in collaboration with Elsevier, with a focus on the development of methodologies suitable to analyse online platform usage data. To this end, my research focussed on the development novel modelling frameworks to analyse a previously unexplored type of data structure that arises naturally when observing these user-platform interactions.

The decision to pursue a PhD, and particularly one at the STOR-i CDT, is one I am now very glad I took. The inclusive and inquisitive environment, the links with industry, and the great faculty at Lancaster, led to the development of skills and knowledge which I am sure will stick with me for the rest of my career.

Since leaving STOR-i, I have gone on to work as a Quantitative Analyst for Smartodds, where I develop models for predicting sporting outcomes.

Holly Jackson

I completed my PhD in 2023, supervised by Professor Thomas Jaki and Professor Andrew Titman and in collaboration with Quanticate, a clinical research organisation. The main focus of my PhD was novel, efficient, and adaptive methodologies for the design of clinical trials. Taking a new drug from discovery to market is a lengthy and costly process, the use of more efficient trial designs in the form of adaptive clinical trials could greatly reduce the time and cost of this process.

I enjoyed my time at the STOR-i CDT, I particularly benefitted from the cohort structure which facilitated collaboration across different statistical and operational research disciplines and gave me a great sense of community and support through those difficult PhD moments. In addition to the industry exposure at STOR-i, I participated in the Roche Internships for Scientific Exchange in the Department of Neuroscience and Rare Diseases for 12 months. This extra industry experience introduced me to cross-discipline working as well as specific medical statistical methodologies.

Since leaving STOR-i, I now work as a postdoctoral researcher at Hôpitaux Universitaires de Genève in Switzerland in collaboration with ECRAID, where I support the design and analysis of perpetual observational studies and continue my research on novel efficient clinical trial designs.

Graham Laidler

Concluding in 2023 under the supervision of Barry Nelson (Northwestern University), Lucy Morgan, and Nicos Pavlidis (both Lancaster), my PhD research combined machine learning methods with the data and theory of stochastic simulation. At STOR-i, I benefited from the exposure to a wide range of topics across the spectrum of statistics and operational research, and now work as a statistical analyst for global wildlife trade at TRAFFIC, a conservation programme based in Cambridge.

Callum Murphy-Barltrop

I completed my PhD in 2023, supervised by Dr Jennifer Wadsworth and Dr Emma Eastoe. The focal point of my PhD, supported by funding from the UK's Office for Nuclear Regulation, centred on the domain of statistics known as extreme value theory. In practical terms, this domain holds enormous significance as it equips us with tools for evaluating risks stemming from natural hazards, such as floods, storms and heatwaves - events whose occurrence has grown more frequent due to the impact of climate change. My research focused on developing novel techniques for estimating and modelling extreme risks across multiple hazards simultaneously. Additionally, I also developed a methodology for modelling climate trends in the extreme setting.

I am incredibly grateful to have completed my PhD at the STOR-i CDT. The quality of research and expertise within the CDT, combined with the sense of community and strong industry connections, made STOR-i an ideal research environment for me. Being part of STOR-i also enabled me to develop a wide range of skill sets, both personal and professional, that have been massively beneficial in my career as a young researcher.

Since leaving STOR-i, I now work as a postdoctoral researcher at Technische Universität Dresden in Germany, where I continue to do research in extreme value theory.

Srshti Putcha

I completed my PhD at the end of 2023, supervised by Professor Paul Fearnhead and Professor Chris Nemeth. The main focus of my research was to develop scalable Bayesian inference for big data, specifically for the class of stochastic gradient Markov chain Monte Carlo samplers.

I have been working in the consumer finance sector for just over three years. I currently work at Capital One as a Senior Data Scientist. My team works to support the UK business’ customer acquisition credit risk model. Prior to my current role, I worked at the UK&I Experian DataLabs in London.

Alongside work, I am actively involved in the Royal Statistical Society and I am currently a member of the Council.

Jess Spearing

I completed my PhD in 2023, supervised by Jonathan Tawn, Tim Paulden, David Irons and Grace Bennett (ATASS Sports). My PhD centred on the field of statistical ranking systems, and utilised methodology in the areas of extreme value theory, paired comparison, Bayesian inference, and longitudinal data analysis. These methodological developments were primarily demonstrated on sports data, although kept general throughout.

Particularly upon starting the PhD, I greatly benefitted from my cohort structure, from the social aspects more broadly, and from the sense of community, which made for a welcoming atmosphere. In addition to the crucial industry exposure at STOR-i, e.g., problem-solving days, I also took a year-long internship opportunity working at the Behavioural Neuroscience Lab at Roche, Basel. As well as the technical statistical skills I learnt here, I picked up further industry experience, such as collaborative coding, and working cross-discipline with experts from other fields.

I now work as a statistician for Shell's Decision Science department in Amsterdam, NL.

Ed Austin

My PhD was supervised by Idris Eckley and in partnership with BT. The research was focussed on developing novel methods for identifying anomalous structures within streaming data.

One of STOR-i’s main appeals to me was the opportunity to engage in industry-driven research. Not only did this allow me to develop my problem-solving skills, but it allowed me to support the downstreaming of my work into BT and I have found making such an impact highly satisfying.

Since obtaining my PhD I have continued as a postdoctoral researcher working closely with BT on a range of statistical challenges.

Matt Bold

I completed my PhD in 2022 and was supervised by Marc Goerigk, Burak Boyaci and Chris Kirkbride. My thesis was titled "Algorithmic Developments in Two-stage Robust Scheduling". It focussed on the study of scheduling problems with uncertain task durations, where after you've decided on your initial schedule (stage one), you get the chance to slightly amend it after learning about the actual duration of the tasks (stage two). I also collaborated with Sellafield Ltd to build a mathematical model and prototype business tool for the optimisation of long-term decommissioning schedules.

Following my PhD, I joined AstraZeneca to work on optimising a range of scheduling and supply chain problems within manufacturing operations. I am now based in Bristol and work for Ecotricity, building an optimisation platform for controlling flexible electricity generation and storage assets.

Thu Dang

My PhD research was conducted with the STOR-i CDT, utilizing both exact algorithms and heuristic methods to tackle large-scale and complex Vehicle Routing Problems. My supervisors were Professor Adam Letchford and Dr Burak Boyaci, and the research was in collaboration with Routeware, Inc.

The STOR-i program has been an incredible environment for learning and personal growth. I was exposed to a wide range of research topics and benefited greatly from the diverse training courses. The support and encouragement I received from both the staff and the friends I made in my year group were invaluable.

Since completing my PhD in July 2022, I have held a position as a Lecturer in Management Science here, allowing me to continue working on Combinatorial Optimization Problems.

Jake Grainger

I completed my PhD in 2022, which was supervised by Dr Adam Sykulski and Professor Phil Jonathan from Lancaster, and Professor Rob Lamb from the JBA Trust. My PhD work focussed on the statistical modelling of data related to ocean waves, especially in the frequency domain.

I greatly enjoyed my time at STOR-i, the mixture of industrial and academic expertise, various problem-solving days and additional training courses, and the concentrated group of other PhD students made for a dynamic and constructive environment.

I am now a Post-Doctoral research associate at EPFL, where my research focuses on frequency domain spatial statistics.

Stephen Ford

I finished my PhD "On The Dynamic Allocation of Assets Subject to Failure and Replenishment" in 2021, looking at how to assign assets that need refuelling to various tasks to maximise return. My supervisors were Kevin Glazebrook and Peter Jacko at Lancaster University, and Mike Atkinson from the Naval Postgraduate School in Monterey, California.

Since graduating, I’ve been working for GORS, the Government Operational Research Service, and have greatly appreciated all the presentations we were made to do, and how I now look forward to them. I’ve also found a use for several of the statistical techniques that were mentioned in STOR-i's Friday morning talks.

Tom Grundy

My PhD was on changepoint detection, which aims to detect abrupt structural changes in time series data. I was supervised by Rebecca Killick (Lancaster University), Ivan Svetunkov (Lancaster University) & numerous supervisors from Royal Mail throughout the PhD.

The cohort model was the main reason I chose STOR-i and was the highlight of the PhD. Being part of a group where everyone was going through the same experiences was pivotal in navigating the inevitable difficult moments in a PhD.

Since graduating from STOR-i, I joined the Data Science team at Peak. I work in the Pricing Intelligence Team, helping Retailers and Manufacturers optimise their prices to boost profits.

Nicola Rennie

I finished my PhD in 2021, supervised by Adam Sykulski, Catherine Cleophas, and Florian Dost, with support from Philipp Bartke and Valentin Wagner at Deutsche Bahn. My PhD research focused on the topic of detecting outliers in demand for railway services, using functional data analysis and clustering methods.

STOR-i's focus on collaboration with industry was a particular highlight of the programme, as this allowed me to see the impact that my work can have. Since finishing my PhD, I've worked in both academic (as a Lecturer in Health Data Science) and industry (in data science consultancy) roles. I'm now a data visualisation specialist at the Office for National Statistics where my work focuses on improving the way we visually communicate statistics and data.

Jordan Richards

I completed my PhD in 2021 under the supervision of Jon Tawn, Jenny Wadsworth, and Simon Brown (UK Met Office). During my PhD, I developed models for extremes of aggregates of random variables and spatial processes. At the beginning of my PhD, I was uncertain about the topic that I wanted to pursue. However, thanks to the breadth of research topics offered for STOR-i PhDs, and the opportunities I had to learn about many areas of statistics and their application, I was quickly able to decide on a PhD topic that suited me.

After leaving STOR-i, I completed a two-year postdoc at the King Abdullah University of Science and Technology (KAUST) in Saudi Arabia, and will subsequently join the University of Edinburgh as a lecturer in 2024. My current research focus is on the combination of spatial statistics, extreme value theory, and statistical deep learning, with applications to climatic and environmental extremes, as well as natural hazards.

Jake Clarkson

I completed my PhD in 2020, supervised by Kevin Glazebrook from Lancaster and Kyle Lin from the Naval Postgraduate School in Monterey, CA. The project focused on searching for an object hidden in one of several discrete locations. A new formulation where the searcher could choose between a fast and a slow speed was studied, as well as a classic problem where the object is an intelligent hider trying to avoid detection.

I enjoyed my time at STOR-i. The Master's year is a great opportunity to gain insight into a wide range of topics and choose which area you would like to study further in the PhD. The supportive and social environment in particular made my time at STOR-i an enjoyable experience!

After my PhD, I remained at STOR-i for a year's post doc, before doing another 18-month post doc at the Inria Centre at Université Côte d'Azur. I now work as a statistician at National Highways.

Aaron Lowther

I completed my PhD under the supervision of Matt Nunes, Paul Fearnhead and Kjeld Jensen. My PhD was a collaborative project with BT Applied Research. We developed semi-automated algorithms to produce sparse and interpretable multivariate time-series models. The work has been applied to several projects within the organisation.

Following the completion of my PhD, I completed a postdoc position with Rebecca Killick and Idris Eckley. I then became a Senior Statistician at National Highways where I worked with a team to develop a novel hypothesis testing approach to compare casualty rates on the Strategic Road Network. I am currently a Senior Data Scientist at NatWest Group.

The training I received at STOR-i provided me with skills that have been invaluable during my career in the industry. I am glad that I chose to complete my PhD at the Doctoral Training Centre. The centre provided me with a huge number of amazing staff and peers who created a collaborative, supportive and fun learning environment.

Euan McGonigle

I completed my PhD in 2020, supervised by Rebecca Killick at Lancaster University, Matthew Nunes at the University of Bath, and Martyn Byng at the Numerical Algorithms Group (NAG). My PhD project was in collaboration with NAG, developing new wavelet-based methods for the modelling and analysis of nonstationary time series.

One of the key benefits of STOR-i was the cohort model, which meant there was a large, supportive network of peers throughout my time at Lancaster. I feel that STOR-I enabled me to develop a wide breadth of knowledge of topics in both Statistics and Operational Research, which has helped me in my career after finishing my PhD.

After completing my PhD, I worked at the University of Bristol as a postdoctoral researcher, working on problems in change point detection. Since June 2023, I have been a Lecturer in Statistics at the University of Southampton, where I continue to work on problems in nonstationary time series and change point analysis.

Hankui Peng

I completed my PhD in 2020 under the supervision of Nicos Pavlidis and Idris Eckley. My PhD project was in collaboration with the Office for National Statistics (ONS), with the main focus being cluster analysis. Specifically, my PhD research looked at subspace clustering and active learning with constraints, which finds its applications in text mining and image recognition. I appreciate the unique PhD partnership model that STOR-i offers, which allowed me to work on meaningful research topics motivated by industry applications. I also think that the strong industry connections that STOR-i has, either via problem-solving days or alumni events, prepared the students well in terms of exploring different career prospects.

Upon completing my PhD, I conducted postdoctoral research at the University of Cambridge working on the applications of unsupervised learning, specifically image segmentation. Currently, I am a Deployment Strategist at Palantir Technologies in London working on the development and deployment of analytical and operational software solutions for large enterprise clients.

Georgia Souli

I completed my PhD in 2020 and I was supervised by Adam Letchford (Lancaster University) and Alex Armstrong (Morgan Stanley). My PhD thesis is entitled "New Valid Inequalities for Knapsack and Fixed-Charge Problems". During my PhD, I developed families of valid inequalities that can help speed up the solution process of large-scale optimization problems.

An aspect of STOR-i that was particularly beneficial for me was the cohort model, which created a supportive and lively learning environment. Another key benefit of STOR-i was the exposure to a wide breadth of topics, in Statistics and Operations Research, academia and industry. Since graduating from STOR-i, I have been working as a Quantitative Analyst at Morgan Stanley.

James Grant

I completed my PhD in 2019, working with David Leslie, Kevin Glazebrook, and Roberto Szechtman (Naval Postgraduate School). My PhD research combined ideas from Statistics, Operational Research, and Machine Learning to design algorithms which learn to optimally collect spatial data in surveillance settings. I’ve since worked in two industrially engaged postdoctoral roles at Lancaster and have been a Lecturer in Statistics here since 2021. I continue to research at the interface of Statistics and Operational Research and now supervise several STOR-i PhD students. You can find more details of my research on my website James Grant.

For me, one of the main benefits of STOR-i was its cohort model, along with the breadth of topics researched within the Centre. This meant that whilst I was studying my research topic in detail, I built awareness of a range of other topics through watching the progress of my peers – something I feel I wouldn’t have had the chance to do in a smaller, more specialised group. This broad awareness has been really useful for me since moving beyond my PhD research into the wider discipline and helps me to engage with a range of academic and industry partners in my current role.

Lucy Morgan

I completed my PhD in 2019, working with David Worthington, Andrew Titman and Barry Nelson (Northwestern University). My PhD research used Statistical techniques for uncertainty quantification to quantify error in Simulation, a widely used Operational Research tool.

When I completed my PhD I worked as a Lecturer in Simulation and Stochastic Modelling at Lancaster University Management School. In August 2021, I moved to a role at BT as an AI and Modelling Research Specialist. At the start of 2025, I moved to The Strategy Unit, an internal NHS consultancy, to lead the simulation team. As an analytics manager in the NHS, I use OR and Statistics on a daily basis to inform decision making. I continue to work as a visiting researcher at Lancaster University.

I enjoyed my time as a PhD student at STOR-i CDT and felt I came away from the experience with a wide breadth of knowledge of research going on in Statistics and Operational Research. This has served me very well within my role at BT and has enabled me to identify appropriate methods to tackle an array of problems. I also appreciated the time we spent on building additional skills at the centre. Knowing the tools for how to effectively communicate my research has been extremely useful in my career.

Emma Simpson

I completed my PhD at STOR-i in 2019, under the excellent supervision of Jenny Wadsworth and Jonathan Tawn. My PhD research focused on estimating and modelling dependence in multivariate extremes, such as developing methods to identify combinations of variables that can take their most extreme values simultaneously. The project had links to the University of Oslo, where I enjoyed a week-long research visit during the second year of my PhD.

I have very fond memories of my time at STOR-i. I particularly enjoyed the opportunities to learn about topics in statistics and OR beyond the focus of my PhD, through activities like the weekly forums and problem-solving days. It was also great to have so many other students studying topics in extremes, allowing us opportunities to share interesting discussions at our weekly “extremes coffee” sessions and regular reading group meetings.

Following my PhD, I stayed at Lancaster for a postdoc on developing a methodology for spatio-temporal extremes, which involved collaborations with academics at INRAE (Avignon) and KAUST. Since April 2021, I have been a Lecturer in the Department of Statistical Science at UCL. I continue to conduct research in extreme value analysis and enjoy ongoing collaborations through connections made during my time in Lancaster. Up-to-date information about my current research and publications can be found on my webpage Emma Simpson.

Helen Barnett

Upon completing my PhD in 2017, I started my post as a Senior Research Associate in Medical and Pharmaceutical Statistics at Lancaster University. My research is funded by Janssen Pharmaceutica, who was the industrial partner for my PhD with STOR-i. I am working closely with Janssen on the topic of dichotomisation of continuous biomarkers, a very interesting and relevant subject in the area of personalised medicine.

Lawrence Bardwell

My PhD looked at methods to efficiently perform inference for changepoint models in high-dimensional time series. It was industrially sponsored by British Telecom and I was supervised by Idris Eckley and Paul Fearnhead from Lancaster and Martin Spott from BT.

I now work as a Statistician at an educational consultancy company, AlphaPlus consultancy.

Matt Ludkin

I completed my PhD at STOR-i in 2018 under the supervision of Professor Peter Neal and Professor Idris Eckley with sponsorship from Ralph Mansson at the Defense Science and Technology Laboratory (DSTL). My PhD thesis, titled "The autoregressive stochastic block model with changes in structure", looked at statistical models for network data collected through time. Specifically, models to detect if the group structure within the network had changed. I now work as a senior research associate with Dr Chris Sherlock on the EPSRC project "New developments in non-reversible Markov chain Monte Carlo" (EP/P033075/1). Traditional reversible MCMC aims to draw samples from a target distribution by simulating a Markov chain whose stationary distribution is the target. One downside to reversible algorithms is that they lose a sense of direction in regions where the target is flat. This leads to a slow exploration. Conversely, non-reversible methods keep a sense of direction. Current methods have great potential but practical problems limit their usability. My research currently aims at creating new non-reversible algorithms that are more efficient than standard MCMC and can be applied to real problems with ease. Link to my website: www.lancaster.ac.uk/~ludkinm

Paul Sharkey

I completed my PhD in 2018 under the supervision of Jonathan Tawn, Simon Brown (Met Office) and Hugo Winter (EDF Energy). My PhD research focused on developing multivariate methods for modelling extratropical cyclones that incorporated the meteorology of these weather systems. Since leaving STOR-i, I became a statistician at JBA Consulting as part of the Flood Risk Science team, where I work with a group of specialists from the physical sciences to model impacts arising from coastal, river and weather extremes. This has allowed me to continue research into extreme value statistics, and explore new and exciting environmental applications that could benefit from this methodology.

Mark Bell

Since completing my PhD in 2015 I have tried my hand at both industry and academia. Initially, I worked as a Data Scientist at Dunnhumby (the company behind the Tesco Clubcard) in the Price and Promotions Science team. Projects centred around demand models for retail. These effectively involve understanding customers’ responses to changes in the key levers over which the retailer has control, such as their sensitivity to price change, promotion and display location in the store.

I have since moved back to academia and now work as a postdoc at the University of Reading. The project involves modelling network data as an exponential random graph model (ERGM) and performing Bayesian inference, using Monte Carlo methods such as MCMC and SMC. Inference for ERGMs is infeasible for all but small networks – the project’s focus is on improving inference for larger networks.

Rhian Davies

Since completing my PhD thesis, I have been working as a data scientist at Arctic Shores, a company which develops game-based psychometric assessments. Before working at Arctic Shores, I hadn't studied psychology at all, now I work with psychologists, game developers and graphic artists daily. One of the things I love about statistics is how interdisciplinary it is. I get to learn something new every day.

The media training which I received at STOR-i has been invaluable in the development of my statistical communication skills and I have recently been appointed a statistical ambassador for the Royal Statistical Society. This voluntary role involves engaging with journalists and members of the public to help them understand everyday statistical concepts. Recently, I was consulted by Panorama to advise on their analysis of drunken behaviour at airports for their documentary "Plane Drunk".

‌James Edwards

Before joining STOR-i I studied Mathematics at the Open University and an MSc in Management Science and Operational Research at Lancaster.

My PhD was on Bayesian sequential decision problems and the multi-armed bandit. These problems involve taking actions in sequence under uncertainty where outcomes resulting from actions give information that can help in future decisions. This creates the need to trade-off exploration, to learn for the long term, against exploitation of current knowledge for good results in the short term. Part of this work was sponsored by Google and concerned with the problem of choosing multiple website elements to display to a user.

After finishing I continued research in this area as a senior research associate at Lancaster on a project with a commercial partner on adaptive pricing.

George Foulds

After STOR-i I joined Summit as a data scientist in their Insight Team, working on the online bid optimisation and budget planning platform, Forecaster. I quickly moved into a consultancy role, working with some of the UK's largest retail companies, helping to optimise marketing strategies and provide customer insights driven by statistical modelling and machine learning. I am now (2019) the lead data scientist across all of Summit’s data functions and working within a new product area: demand planning for retail giants across the world, using our newly developed platform Purchase Predictor. The platform employs time series forecasting, clustering, natural language processing, changepoint techniques and more to identify key opportunities for profit.

STOR-i gave me the means to interrogate academic research and understand the concepts within. The industry-led workshops which I attended through STOR-i (with the likes of Shell and BT) were invaluable in developing great consultancy and leadership skills.

‌Kaylea Haynes

I completed my PhD thesis on "Detecting Abrupt Changes in Big Data" in December 2016, supervised by Idris Eckley and Paul Fearnhead. During the final 3 months of my PhD, I worked part-time as a Data Scientist at Sporting Data Science looking at modelling outcomes of cricket and football matches. On completing my PhD I joined Sporting Data Science full time. In April 2017 I started working at Peak as a Data Scientist. Peak is a pioneering Artificial Intelligence-as-a-Service company that helps businesses of all sizes do great things with data. At Peak, I get involved in lots of different Data Science problems for various companies across the retail and industry sectors. In January 2018 I was promoted to Team Leader of the forecasting and optimisation team which has brought lots of fun and exciting challenges.

David Hofmeyr

My PhD, which I completed in 2015, was supervised by Nicos Pavlidis and Idris Eckley and looked at dimension reduction techniques for clustering and semi-supervised classification applications.

After submitting my thesis I took up a position as a post-doctoral research associate within STOR-i, where I continue to work with Nicos Pavlidis. The work done in this position will look at extensions of the work done during my PhD to very high dimensional problems which arise in the modern context of "Big Data", and with particular attention to applications in bioinformatics.

Monika Kereszturi

My PhD was supervised by Jonathan Tawn and Philip Jonathan, and it looked at spatial extreme value modelling of oceanographic data. Since completing my PhD, I have been working as a statistician at JBA Risk Management. In this role, I have had the opportunity to continue using extreme-value statistics to develop models for floods and other natural hazards.

Christian Rohrbeck

I joined the STOR-i CDT as an MRes student in 2012 upon completion of my studies at the University of Heidelberg. I completed my PhD at the STOR-i CDT under the supervision of Deborah Costain, Jonathan Tawn and Emma Eastoe from Lancaster University, and Arnoldo Frigessi from the University of Oslo. My PhD considered the association between property insurance claims and weather events in Norway. I was awarded the EPSRC Doctoral Prize of the Faculty of Science and Technology in September 2016. As part of this award, I was appointed Research Associate at the [School of Mathematical Sciences] (formerly the Department of Mathematics and Statistics) at Lancaster University. In November 2017, I was awarded a 2-year post-doctoral research grant by the AXA Research Fund and continued my work at Lancaster University. My research project considers the association between small-scale weather events and property insurance claims and aims to extend my PhD research. ‌

Lisa Turner

I completed my PhD on “Inference and Decision Making in Large Weakly Dependent Graphical Models” in 2017. During that time, I did an internship at a chemical speciality company called Lubrizol.

Since finishing, I have been working as a Data Scientist at Lubrizol full-time. I mainly work within the Engine Oil Additives segment of the company, developing optimisation and analytical tools that are used to speed up the product development process.

‌Jamie Fairbrother

After joining STOR-i in October 2010, I undertook a PhD in the area in the are scenario generation, a problem concerned with the representation of uncertainty in decision-making problems for which I was jointly supervised by Amanda Turner and Stein Wallace. During my PhD, I completed an internship at BT relating to the calculation of maximum transmission powers of certain radio devices. Since completing my PhD in November 2015, I have taken up the position of research associate and am working on a problem in combinatorial optimization, motivated by a problem in telecommunications.

‌Tom Flowerdew

Before I started studying at STOR-i, I had completed a Master's degree in Mathematics and was working in the engineering sector.

My PhD was industrially sponsored by ATASS Sports and concerned with how to optimally exploit profitable betting opportunities, which arise when betting on sports, and was co-supervised by Jon Tawn, Chris Kirkbride, and Kevin Glazebrook.

Since completing my PhD, I have been working as a data scientist for Featurespace, a small company based in Cambridge that specialises in building adaptive behavioural analytic models, which are used to catch fraud in financial services, insurance and gaming.

‌Terry James

Before I started studying at STOR-i, I had completed an undergraduate Mathematics degree and was working in the civil service.

My PhD was co-supervised by Kevin Glazebrook in conjunction with Kyle Lin from the US Naval Postgraduate School. This research explored the task of identifying defensive surveillance policies that can mitigate the threats faced by adversaries in a public setting. For example, consider a surveillance resource responsible for several public areas, each of which is a potential target for an adversary. How should the resource be controlled given that the adversary can strike at any time in amongst any of the randomly evolving public crowds?

Since completing my PhD I have been undertaking PGCE training to become a mathematics teacher.

‌Jak Marshall‌‌

Before joining STOR-i, I completed my MSc in Mathematics and Statistics at Lancaster University with one year of studying abroad at UC Berkeley. I then went on to complete my MRes and PhD at STOR-i with Roberto Szetchman acting as co-supervisor. Kevin Glazebrook and Chris Kirkbride completed my supervisory team.

The project itself was concerned with modelling intelligence-gathering processes in the military using Bayesian multi-armed bandit models. The formulation of a timed-limited and mission-critical investigation as a stochastic dynamic programming problem allows for solutions whereby intelligence operatives can efficiently search for crucial information before it becomes outdated.

I have worked as a data scientist in the games industry since 2014, having worked with Sega, Rovio, Mattel, and now 2K Games.

‌Robert Maidstone

I completed my PhD at STOR-i in 2016 on “Efficient Analysis of Complex Changepoint Problems” under the supervision of Professors Paul Fearnhead and Adam Letchford. Since submitting my thesis I have been working as a Research Associate at the University of Manchester. My work in Manchester centres on developing and applying computational statistical methods to biomedical data, principally in the field of circadian biology. Working hand in hand with wet-lab scientists, we can exploit statistical and machine-learning methods to explore the inner workings of the molecular clock and its links to disease and inflammation.

‌Benjamin Pickering

My PhD research investigated 'Changepoint Detection for Acoustic Sensing Signals' in collaboration with Shell Research, under the supervision of Idris Eckley, Rebecca Killick and Philip Jonathan. After completing my PhD, I worked as a data scientist in the Pricing and Promotions Science team at Dunnhumby, a customer data science company. This involved developing and supporting the science behind a suite of price and promotions optimisation tools for the retail sector. In January 2018, I started working as a Research Scientist on the Research and Applied Data Science team at Kalibrate, who offer industry-leading fuel pricing and network planning software to fuel and convenience retailers globally. My role involves researching and developing novel approaches to modelling sales demand at fuel stations using machine learning, deep learning and other cutting-edge AI techniques.

‌Hugo Winter

Since completing my PhD thesis, I have been working as a research engineer within the EDF Energy UK R&D Centre in London. I am working within the natural hazards team and have taken the lead on the programmes concerning extreme weather, coastal flooding and hazard combinations.

As part of this job, I undertake my research in the aforementioned areas and also collaborate with many different universities across the UK and around the world. The position requires an in-depth knowledge of extreme value statistics and climate science which I developed during my PhD within STOR-i.

Pedro Crespo del Granado

Before coming to Lancaster, I had academic experiences at undergraduate and master's levels in the United States, France, Switzerland, Bolivia and China. I also worked briefly as a data scientist at the IADB bank. In Lancaster, I was a STOR-i associate PhD student under the supervision of Stein Wallace and Zhan Pang. My PhD thesis entitled “The value of end-user energy storage from intermittent renewables: an end-user perspective in Smart Grids” applied optimization modelling and stochastic programming methods to analyse various real-life case studies (energy systems of houses and communities).

After finishing my PhD in 2014 I have been a post-doc in the Energy Science Center at ETH Zurich. My project builds naturally on my PhD training as I am working in the area of integrated modelling of energy systems.

Gwern Owain

Gwern obtained his MRes in Statistics and Operational Research in 2014. He then started a PhD in the area of statistical modelling, specifically looking at models for low-count time series, supervised by Nikos Kourentzes and Peter Neal.

It was with great sadness that we received the news that Gwern died from leukaemia in October 2015. Gwern is greatly missed by STOR-i students and staff.

In recognition of Gwern’s happy experiences in STOR-i, his family (Robin, Eirian and Erin) very generously offered STOR-i substantial funding in Gwern’s name for a number of years.

Tim Park

I completed my PhD, supervised by Idris Eckley and in partnership with Unilever, in November 2014.

Soon after completing my thesis, I started a career in industry with Shell Global Solutions. This job has allowed me to apply statistical methods to a wide range of applied problems in the oil and gas industry.

I have also been able to keep up my academic links by publishing papers, attending academic conferences and helping to supervise PhD students.

‌Ross Towe

I started studying at Lancaster University in 2006 and obtained an undergraduate degree in Financial Mathematics, subsequently, I continued to study an MSc in Statistics. These courses inspired me to further my studies, with my interest in lying in Environmental Statistics. As a result, I then undertook a PhD entitled: ' Modelling the extreme wave climate of the North Sea', which was supervised by Jonathan Tawn and Emma Eastoe (Lancaster), as well as Philip Jonathan and Nicolas Fournier (Shell).

During my PhD studies, I also completed a NERC PURE internship with the JBA Trust, which focussed on modelling the short-term clustering of flood events.

Since completing my PhD, I have been working as a Knowledge Transfer Partnership (KTP) Associate. The KTP is a joint appointment between Lancaster University and JBA Consulting, to develop statistical models that can produce spatially and temporally realistic flood event footprints.

Alex Armstrong

Before starting my PhD at Lancaster, I completed my undergraduate degree in Computer Science and Mathematics at the University of York. My PhD focused on revenue optimisation strategies for passenger rail services.

Alex completed his thesis part-time whilst working at Morgan Stanley in their Prime Services and Funding division.

‌Saeideh Dehghan Nasiri

I came to STOR-i after completing an MSc in Operational Research at Lancaster University. My PhD was supervised by Adam Letchford and focused on problems linked to optimising vehicle routing on real road networks.

I completed my PhD project in 2014 with the quality of my work being recognised by my being awarded the Kingsman Prize for 2015.

After my PhD, I then went to work for a local start-up company.

‌Natasa Margarita

I completed an MRes in Statistics and Operational Research at Lancaster University in September 2014.

My dissertation was titled 'Interfacing Multivariate Extreme with Multivariate Statistics' and was supervised by Professor Jonathan Tawn.

I am currently working at Moodys Analytics in Edinburgh in the B&H division as a Modelling Operations Analyst. This involves calibrating stochastic models (e.g. interest rate models, equity models) as well as developing internal processes and quality assurance routines to help automate the production of high-quality content services.

Erin Mitchell

I began my studies at Lancaster University in 2006 when I studied for my undergraduate degree in Mathematics. I fell in love with both Lancaster and statistics and decided to stay on to complete my PhD. My research focused on the short-term prediction of wind speeds, in particular using dynamic linear models for prediction, and logistic regression for in-depth analysis of rapid wind speed changes.

Since the completion of my thesis, I have moved to Hertfordshire, and I now work in a games studio, Exient Ltd. We have recently released 'Angry Birds Go!' and will soon be releasing many more huge titles to the mobile market. I work as a data scientist/game analyst - I collect data from players to analyse how they play and spend, and to optimise future improvements to our games. I get to be involved in the design, development and analysis of our games, with my work ranging from reporting on how our games are performing, to designing and balancing new levels.

‌Chris Nemeth

I completed my PhD at the STOR-i CDT in 2014 under the supervision of Professor Paul Fearnhead. My PhD was industrially sponsored by MBDA and focused on parameter estimation for nonlinear state-space models with applications to target tracking.

After completing my PhD I was a STOR-i Impact Fellow before beginning my current role as a lecturer in Statistical Learning in the [School of Mathematical Sciences] (formerly the Department of Mathematics and Statistics). I research problems related to Bayesian inference. In particular, Gaussian processes, Markov chain Monte Carlo algorithms and sequential Monte Carlo, with a focus on applications around intractable likelihood problems and big data scenarios.‌

Devon Barrow

Soon after completing his PhD in Management Science, Devon took up a Post-Doctoral Research position within the Lancaster Centre for Forecasting. During that time he conducted research into forecasting with statistical methods and artificial neural networks while managing several applied research projects in the areas of call centre, electric load and demand forecasting. He also delivered academic and practitioner training courses in forecasting offered through the Forecasting Centre and presented at leading international conferences including the International Symposium on Forecasting (ISF) and the European Conference on Operational Research, both in 2013. Devon currently works as a Lecturer with the Strategy and Applied Management Department at Coventry Business School and serves as Course Director for the MSc in Global Distribution Management. In addition, he continues to remain research active, with publications in, and several ongoing projects aimed at leading international journals.

Karolina Krzemieniewska

The main objective of my PhD research is the classification of non-stationary time series, using wavelets. The new methods which I developed during my PhD will be used by Unilever to classify signals arising from a variety of applications. Karolina is now working at Perceptive Engineering.

Ye Liu

I hold an undergraduate degree in Mathematics and an MPhil degree in Statistics from the University of Cambridge. My PhD, supervised by Jonathan Tawn, focuses on extreme value theory with application to the analysis of financial data in collaboration with Man Investments. He is now working for JBA Risk as Head of Catastrophe Modelling.

Yiannis Papastathopoulos

I completed my BSc in Statistics and Actuarial Science at the University of Piraeus in Greece. In 2009 I completed an MSc in Statistics at Lancaster University which included a dissertation titled 'A Multivariate Extreme Value Analysis on Financial Data'. My doctoral research, in collaboration with AstraZeneca, focuses on exploring safety issues that arise in clinical studies and pharmaceutical experiments. My supervisors are Jonathan Tawn and Emma Eastoe. After my PhD, I was awarded a Bristol Brunel Fellowship and in 2014 was appointed as a Chancellor's Fellow at Edinburgh.

Jochen Schurr

I completed my PhD in the Management Science Department at the Lancaster University Management School. My research involved the operations of retailers, specifically applying multi-armed bandit models and Bayesian learning schemes to find better decision policies for assortment optimization. Jochen is now pursuing a career in industry.

Sarah Taylor

I spent an enjoyable 7 years at Lancaster, 3 studying for my undergraduate degree in Mathematics followed by a PhD in Wavelets working alongside Idris Eckley (Lancaster) and Rob Treloar and Eric Mehers (Unilever). Since completing my PhD I moved to Nottingham and now work for Boots UK at the Head office as a Data Scientist. Within my role, I am responsible for helping influence business decisions and increasing customer engagement through innovative analysis and insight. Using the Advantage Card data and other sources, I use predictive analytical techniques to understand our customers and recommend solutions for customer loyalty, business initiatives and value drivers through personalised communications.

Chiara Tumolo

The MRes at STOR-i allowed me to complete an in-depth study in a variety of statistics and operational research topics. Thanks to the data mining knowledge acquired I am currently working as a credit risk analyst, developing risk models for a consulting company in Milan.

Yifei Zhao

I completed a BSc in Finance at the South-Western University of Finance and Economics in China, followed by an MSc in Operational Research at Edinburgh University before starting a PhD at Lancaster University. My PhD research focused on investigating robust optimal solutions for stochastic integer problems, using exact methods for small-size problems and developing heuristic methods for large-scale problems. My supervisor was Professor Stein W Wallace. Since completing her PhD in January 2014, Yifei has been working as an analyst for Zurich Insurance.

Rebecca Killick

I started my undergraduate degree (BSc) in Mathematics and Statistics at Lancaster University in 2004 and followed this with an MSc in Medical Statistics, again here at Lancaster. I then started a PhD entitled Novel methods for change-point problems supervised by Idris Eckley (Lancaster) and Philip Jonathan (Shell) in October 2008.

I completed my PhD in early 2012 and then was a Senior Research Associate before taking up a lectureship in Statistics at Lancaster University in 2013.

‌Dan Reeve

I previously completed my undergraduate degree in Financial Mathematics at Lancaster.

Between my BSc and MRes courses, I completed a placement with Shell within their Statistics & Chemometrics team based near Chester.

I completed the MRes in Statistics and Operational Research at STOR-i in 2011.

Dan is now pursuing a teaching career.

‌Jenny Wadsworth

At the undergraduate level, I studied Mathematics at the University of Durham, followed by an MSc in Statistics at Lancaster. In the summer between graduating and coming to Lancaster, I completed an internship with the Statistics and Chemometrics group at Shell. My PhD, in collaboration with Shell,

focused on extreme value theory, creating new methodologies in univariate, multivariate and spatial extremes. My supervisor was Jonathan Tawn, with Phil Jonathan at Shell acting as my industrial supervisor.

After her PhD, Jenny was a Postdoctoral Research Associate at École Polytechnique Fédérale de Lausanne, Switzerland and held a Fellowship at Cambridge University, before returning to Lancaster University in 2015 as a Statistics lecturer.

Bethan Turner

I completed my undergraduate degree in Mathematics at Lancaster University and I recently completed my MRes in Statistics and Operational Research at STOR-i in 2011.

I'm now working as a Graduate Analyst at Adelphi International Research- a global market research company based in Manchester dealing with the pharmaceutical market.