UCL Women in Mathematical Sciences

Title

The leaky pipeline: Female Professors in STEM

Time & Location

11am-1pm, 30th November 2021, virtual

Abstract

In the UK, women are underrepresented at Professor level across subjects. Despite making up 46.67% of the academic workforce, women only make up 27.88% of all Professors (HESA, 2021). The effect of gender inequality in recruitment, retention, and progression of women is referred to as ‘the leaky pipeline’. The leaky pipeline effect is even more pronounced in STEM subjects, where women only make up 22.6% of all Professors (Advance HE, 2020). In Mathematical Sciences, only 11.42% of Professors are women.

Julie Jebsen will present findings from two large scale research projects on women’s successful career progression in STEM, highlighting best practice and advice for individuals and organisations that can help increase the retention and progression of women in STEM. This includes the impact of networking during early career stages, strategies in building a support system, and navigating promotional processes.

Short Bio

Julie Jebsen is a researcher specialising in women’s successful career progression in academic STEM careers. Her background is in Occupational Psychology, but she also collaborates with other STEM subject specialists on projects relating to gender inequality in STEM and research careers. Julie has previously worked at the University of Wolverhampton and the University of Glasgow, and will start a new role as a Lecturer in Organisational Psychology at the start of 2022.

Time & Location

10am-4pm, July 6th, 2021 on zoom. 

Aim and format

Our goal is to bring together ideas for improving fairness and diversity of statistical practice and culture in the workplace. The morning will be dedicated to research in the area of fairness and diversity in the practice of statistical modelling, and the afternoon will feature a panel discussion on fairness and diversity within the statistical science workplace. See the event webpage (including full schedule and speaker information) for more details.

Morning session: Fairness and diversity in the practice of statistics

• Corinna Hertweck (ZHAW Zurich University of Applied Sciences)

• Shakir Mohamed (Google DeepMind)

Afternoon panel session: Fairness and diversity in the statistics workplace

• Rebecca Hubbard (University of Pennslyvania)
• Eugénie Hunsicker (Loughborough University)
• Maria Skoularidou (University of Cambridge)
• Marc Deisenroth (University College London)

Title

Recent advances in Bayesian non-parametric clustering

Time & Location

12-2pm, room 102, 1-19 Torrington place

Abstract

In this talk I will introduce Bayesian non-parametric clustering and profile regression, a clustering method suitable for highly correlated variables. I will give a brief overview of recent work on profile regression and the application of these methods to a variety of fields, including environmental health.

Short Bio

Silvia Liverani is a Senior Lecturer in Statistics at Queen Mary University of London. She gained her PhD in Statistics at the University of Warwick in 2009 and has held positions at the University of Bristol, Imperial College London and Brunel University London. Her research interests concern Bayesian methods and their applications. Most of her work to date has been focused on Bayesian clustering models, in particular Dirichlet process clustering and conjugate agglomerative hierarchical clustering. A related area of interest is also the search and representation of uncertainty in the partition
space. She is currently also conducting research on several developments for spatial-temporal models and survival response models. She has worked and continues to work in very diverse areas of application including genetics, epidemiology, road traffic accidents, football, environmental health.

Our special event on Friday 21/06 is organised jointly by Women in Math Science UCL, Women in Data Science London and Women in Computing Imperial. The event brings research talks from leading female researchers with an opportunity to extend discussions over lunch. 

Our two speakers are:

Ruth Misener (Department of Computing, Imperial College London)

Title: How to recover quickly after a carefully-planned schedule goes wrong

Abstract: In industrial scheduling, an initial planning phase may solve the nominal problem and a subsequent recovery phase may intervene to repair inefficiencies and infeasibilities, e.g. due to machine failures and job processing time variations. We consider two applications: (i) minimum makespan scheduling and (ii) mail delivery in collaboration with the Royal Mail Data Science Group. Lexicographic optimisation is our key tool: we show why a lexicographic solution in the first stage enables effective second stage recovery.

Yvonne Rogers (UCLIC, Department of Computer Science, UCL)

Title: Revealing data about ourselves: creepy or curious?

Abstract: People are increasingly concerned about the data that is being collected about them; how it is being used, by whom and where it ends up. A latest concern is facial recognition technology, which is beginning to be deployed in physical and online stores, intended to help retailers improve how they customize the shopping experience. Smart AI platforms are emerging that can detect - at a glance - our gender, race and approximate age, where and how long we have been looking at something and what emotional state we are in. All without us knowing what is going on behind the scenes. In contrast to this creepiness, I will present in my talk a more open approach to data collection and use, that enables the general public to be more aware of, understand, accept and act upon data collected about them. In particular, I will describe some of the research we have conducted, as part of our Intel-funded, Interdisciplinary Collaboration Research Institute (ICRI) in the UK on the urban Internet of Things. A focus of our work has been on how various kinds of data can be more openly sensed in people’s homes, public places and outdoors with the aim of empowering communities to act upon it. As part of our approach, we have been designing very visible physical interfaces, intended to entice and encourage people to be both curious and comfortable with what is behind the data they help to create.

Schedule
10:30 - 11:00 Coffee and Networking
11:00 - 12:00 Ruth Misener
12:00 - 13:00 Yvonne Rogers
13:00 - 14:00 Discussion over lunch

Title

Network reconstruction and systemic risk assessment

Abstract

Modern financial markets are highly interconnected leading to huge challenges when it comes to assessing risk. In this talk I will discuss how network models can be used to assess systemic risk in financial markets. Often financial networks are not fully observable. I will discuss how networks can be reconstructed from partial information using a Bayesian approach. I will then show how these reconstructed networks can be used in financial stress tests to assess systemic risk.

Short Bio

Luitgard Veraart is an Associate Professor of Mathematics at the London School of Economics and Political Science. She has a PhD in Mathematics from the University of Cambridge. Prior to joining LSE she held positions at the Karlsruhe Institute of Technology and Princeton University. Her research interests are in financial mathematics and statistics in finance. She is particularly interested in problems related to risk management in financial markets with a special focus on systemic risk. In this context she has been working with financial regulators and has been awarded a George Fellowship by the Bank of England.

All female and non-binary MSc and PhD Students, Postdoctoral Fellows and Staff from the Department of Mathematics, the Department of Statistical Science and CoMPLEX are warmly invited to attend. We will provide lunch in an informal, friendly environment. This is a great opportunity for female students to get to know each other and to meet leading female professionals in mathematical sciences such as statistics, mathematics, computer science etc.

Date

17th July 2018, 12.00-14.00.

Room

Room 804, IOE, UCL.

Title

Instabilities in Viscoelastic Fluids: a long story

Abstract 

Complex fluids are fluids that don’t behave according to the standard Newtonian model used to explain, for example, air, water and honey. They fall into many different categories, including multiphase fluids - mixtures of a liquid and solid particles, or a bubbly liquid, for example - but one of the most industrially important is viscoelastic fluids. These are typically fluids with a high molecular weight component, such as polymer solutions or melts (used widely in the manufacture of plastic products), and the large molecules have the ability to store energy through being deformed by flow, giving the fluid an intrinsic memory. In viscoelastic fluids, there is potential for instability mechanisms that persist even at negligibly low inertia: purely elastic instabilities. Some of these are well understood - including long-wave interfacial instabilities, and curved-streamline instabilities. However, some such instabilities are either predicted theoretically and never seen in experiments, or cause unexplained trouble in ex- periments. I will present my experience with an instability that was an unfulfilled theoretical prediction for over a decade before being seen in experiment.

Short Bio

Helen Wilson studied mathematics at Cambridge before spending time in Boulder, Colorado as a postdoc in chemical engineering. She returned to the UK in 2000, taking up a lectureship in Leeds before moving to UCL in 2004. She is an editor of several journals in fluid mechanics and rheology, including the Journal of Engineering Mathematics and Proceedings of the Royal Society A. From 2015-2017 she was president of the British Society of Rheology; and from next September she will be the head of UCL Mathematics.

All female and non-binary 4th year, MSc and PhD Students, Postdoctoral Fellows and Staff from the Department of Mathematics, Department of Statistical Science and CoMPLEX are warmly invited to attend. We will provide a delicious lunch in an informal, friendly environment. This is a great opportunity for female students to get to know each other and to meet leading female professionals in mathematical sciences such as statistics, mathematics, computer science etc.

Date

21st February 2018, 12.00-14.00.

Room

Room 102, 1-19 Torrington place

All female MSc and PhD Students, Postdoctoral Fellows and Staff from the Department of Mathematics, the Department of Statistical Science and CoMPLEX are warmly invited to attend. We will provide tea/coffee and delicious cakes in an informal, friendly environment. This is a great opportunity for female students to get to know each other and to meet leading female professionals in mathematical sciences such as statistics, mathematics, computer science etc.

Title

Harnessing the power of mobile phones and big data for global health

Abstract

Worldwide many infections remain undiagnosed and untreated due to poor diagnostic tools at the point of care. Professor Rachel McKendry will present her research to create a new generation of mobile phone-connected diagnostic tests for infectious diseases. The widespread use of mobile phones could dramatically increase access to testing outside of hospital settings, particularly in developing countries. This research sets the foundations of a global early-warning system, linking the millions of symptoms that are self-reported on the web each day to mobile phone-connected tests, in real-time and with geographically-linked information. This research lies at the cutting edge of infectious diseases, nanotechnology, telecommunications, big data and public health.

Short Bio

Rachel McKendry is Professor of Biomedical Nanotechnology at UCL and holds a joint position at the London Centre for Nanotechnology and Division of Medicine. She is Director of i-sense, a national £11M EPSRC Interdisciplinary Research Centre in Early Warning Sensing Systems for Infectious Diseases and Director of Biomedicine and Life Sciences at the London Centre for Nanotechnology, UCL. Rachel has won several prestigious fellowships and awards including a Royal Society Dorothy Hodgkin Fellowship, Institute of Physics Paterson Media and a Royal Society Wolfson Merit Award. Most recently, Rachel was awarded a Royal Society Rosalind Franklin Award for her scientific achievements, suitability as a role model and proposal to launch a national competition to create mobile phone apps to inspire women to become leaders in STEM.

Date

Friday, 1 May 2015, 13.00-14.00.

Room

Room 102, 1-19 Torrington Place.

All female 4th year, MSc and PhD Students, Postdoctoral Fellows and Staff from the Department of Mathematics, Department of Statistical Science and CoMPLEX are warmly invited to attend. We will provide a delicious lunch in an informal, friendly environment. This is a great opportunity for female students to get to know each other and to meet leading female professionals in mathematical sciences such as statistics, mathematics, computer science etc.

Date

Thursday, 26th February 2015, 12.00-14.00.

Room

Room 102, Department of Statistical Science, 1-19 Torrington Place.

All female 4th year, MSc and PhD Students, Postdoctoral Fellows and Staff from the Department of Mathematics, Department of Statistical Science and CoMPLEX are warmly invited to attend. We will provide a delicious lunch in an informal, friendly environment. This is a great opportunity for female students to get to know each other and to meet leading female professionals in mathematical sciences such as statistics, mathematics, computer science etc.

Date

Thursday, 30 October 2014, 12.00-14.00.

Room

Room 502, Department of Mathematics, 25 Gordon Street.

Title

Handling missing values in cross-national surveys: a latent variable approach

Abstract

Sample surveys collect information on a number of variables for a randomly selected number of respondents. Among other things, the aim is often to measure some underlying trait(s) of the respondents through their responses to a set of questions. In the paper, we focus on cross-national surveys. The main research objective is to compare the distribution of the latent variables across countries (structural model). In some applications, latent variables will be considered continuous (e.g. ability) and in some other applications discrete (e.g. health state). Here, our focus will be primarily the modelling of item non-response and studying its effect on cross-countries comparisons. Measurement invariance will be assumed for the observed indicators conditional on the latent variables across countries. Various model extensions are proposed here to model the missing data mechanism together with the measurement and structural model. The model for the missing data mechanism will serve two purposes: first to characterize the item non-response as ignorable or non-ignorable and consequently to study the patterns of missingness and characteristics of non-respondents across countries but also to study the effect that a misspecified model for the missing data mechanism might have on the structural part of the model.

Short Bio

Irini Moustaki is a professor of Social Statistics at the London School of Economics and Political Science. Her research interests are in the areas of latent variable models and structural equation models that are widely used in Social Sciences and Educational Testing for measuring unobserved constructs such as attitudes, health status, behaviours, intelligence, performance, etc. Her methodological work includes treatment of missing data, longitudinal data, detection of outliers, goodness-of-fit tests and advanced estimation methods. Furthermore, she has made methodological and applied contributions in the areas of comparative cross-national studies and epidemiological studies on rare diseases.

Date

Wednesday, 11 June 2014, 12.00-13.00.

Room

Room 102, 1-19 Torrington Place.

Title

Mathematics for solving real problems

Abstract

This talk will describe the research developments associated with two projects that I am involved in via my collaborations with both industry and academics from different disciplines. They are two completely different problems, requiring very different approaches and working with very different people, but both rely on the development of new methodology. The first is associated with the development of software to allow for the breakdown of intra-day volatility into daily, monthly and longer term volatility for commodity prices. The second is the development of statistical techniques which allow us to quantify the effect of area deprivation on child pedestrian casualties. Through these two case studies, I will attempt to give a flavour of the issues, both good and bad, that I have found in my experience of collaborative work on real problems.

Short Bio

Emma McCoy is the Deputy Head of the Mathematics Department and a member of the Statistics Section at Imperial College London. She holds an MSc in Computational Statistics from the University of Bath and a PhD from the Department of Mathematics at Imperial. Emma has been a mathematics subject expert for the Department for Education and teaches statistics at the undergraduate and postgraduate level. She regularly participates in mathematics dissemination activities including delivering Royal Institution Mathematics Masterclasses and has given the London Mathematical Society Popular Lecture. Her published research includes work on the development of statistical methodology for time series, with applications in signal processing and financial time series analysis, incorporating methods for prediction and inference. Her most recent research involves the development of novel causal methods for statistical inference.

Date

Wednesday, 12 March 2014, 12.00-13.00.

Room

Pearson Lecture Theatre, G22 Pearson (North East Entrance).

PhD Students, Postdoctoral Fellows and Staff from CoMPLEX, Mathematics Department, Statistical Science Department.

Come and meet other female researchers of the departments in an informal environment. Lunch will be provided.

Date

Wednesday, 30 October 2013, 12.00-14.00.

Room

Pearson Room (Room 116), 1-19 Torrington Place.