MathematicalStatistics

Jyoti U. Devkota

Jyoti U. Devkota

Born in Nepal Studied Mathematical Statistics at Lady Shri Ram College, New Delhi, India • Highest Degree PhD in Mathematical Statistics at the University of Osnabrück, Germany • Lives in Kathmandu, Nepal • Occupation Professor of Statistics and Mathematics

I had a great interest in mathematics right from my childhood. The beauty of mathematical problems and its solutions always captivated me. The logical approach followed towards solving a mathematical problem, the exactness and preciseness of its solutions, was always a source of great fascination. As a school student, I was always in the quest of a solution to the mathematical problems given by my mathematics teacher, in the classroom. During my student life in school and college, I was always ready to tackle that mathematical problem for a solution. 

While growing up, my mathematics teachers in my school and my college were my role models. But I didn’t always have a good mathematics teacher in the school. Some teachers, although quite knowledgeable, could not explain mathematics in a simple language. In the pre-Internet and Communication Technology (ICT) era, those were the times of great struggle, as a student. Access to good quality study materials in mathematics was limited to teachers, in those times. Despite having very limited good quality educational resources in mathematics, I have tried to persevere as a student, professional and a researcher. Mathematics has always been a labor of love for me.

Despite having very limited good quality educational resources in mathematics, I have tried to persevere as a student, professional and a researcher. Mathematics has always been a labor of love for me.

After studying Mathematical Statistics in India and completing my PhD in Germany, I returned to Nepal, where I have worked now in the Department of Mathematics at Kathmandu University for more than 25 years.  In this university, I have delivered lectures on several courses of Statistics and Mathematics at the undergraduate, graduate and postgraduate levels. My main objective has been to popularize these courses among my students. To achieve this, I have always tried to simplify formulas and make them engaging for the students. I have also offered crash courses in advanced levels of Statistics and Data Analysis to interested students and researchers. I have also focused on the interdisciplinary applications of the subject. I have taught students from many disciplines including medicine, engineering, environmental sciences and social sciences. My main aim has always been to promote data-based interdisciplinary studies. This was done by making mathematics interesting and popular among my students.

My main aim has always been to promote data-based interdisciplinary studies. This was done by making mathematics interesting and popular among my students.

I faced some challenges while starting my career as a professional like all my male counterparts. This was due to the switch over from student life to the life of a professional. I experienced at that time that the atmosphere in the classroom as a student was completely different from the atmosphere in the university as a lecturer. In due course of time, I married and had two children. In the initial years of my marriage and motherhood, balancing my married life and my motherhood with my professional life was the source of a great challenge. At that time, due to a Gender Gap in the professional fields of Nepal, I had to figure out how to balance my life. There were no female peers in this field, who could guide me through this part of my life journey. At that time, female professionals were much less in number than male counterparts. My family supported me during this time. I left my daughter with my parents, during my PhD study. 

In the initial years of my marriage and motherhood, balancing my married life and my motherhood with my professional life was the source of a great challenge. [..] There were no female peers in this field, who could guide me through this part of my life journey.

I have to state that there is a Gender Gap in STEM education. STEM subjects seem to be less popular among girls. I feel that girls can break the glass ceiling through their hard work and perseverance in Mathematics and its allied subjects. A sound training in mathematics and its allied subjects prepares them to look at a problem from a different perspective. Girls with enhanced skills in mathematical problem solving are more evidence based and thorough. Mathematics is said to be the language of nature. Thus, these skills have immense scope of interdisciplinary applications. 

With Internet and communication technology, girls of Nepal can be as good as their counterparts in the developed country. By using this technology, girls of Nepal can enhance their skills of problem solving, using mathematics. They should be encouraged to participate in Mathematical events, as this will expose them to the importance of mathematics and the role of ICT in enhancing their skills in mathematics.

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Amanda Minter

Amanda Minter

Born in UK • Studied Mathematics at Lancaster University in Lancaster, UK • Highest Degree PhD in Infectious Disease Modelling • Lives in UK • Occupation Director of Equations of Disease C.I.C.

Growing up, universities were always a bit of a mystery to me, my parents didn’t go to university. But I was encouraged by my parents and schoolteachers that going to university would be the path for me. I thought that going to university and studying would help me change the world for the better. I enjoyed maths from a young age, it was a subject which came naturally to me. I found the lessons easy, but then at university, studying maths, I struggled.

Whether it was the format of lectures or the more abstract topics, the subject I loved didn’t come naturally anymore. I worried that I had reached my limit in my understanding of mathematics. After a few disappointing grades, I knew something would have to change if I was going to get a good degree. I had to do something different – I had to learn differently. 

I knew with enough time I could figure out most things – or know when it was taking me too long and I should ask for help!

I wasn’t used to having to put effort into learning maths, but now I would attend classes, then practice, read several books, find examples online, until I understood the concept. In those years at university, I learnt how to learn. And it paid off, not just at university, but further down the line as well.

I stayed at my university to do an MSc in Statistics. Although I loved group theory, I wanted to work on something more applied.  Following my MSc, I started a PhD in infectious disease modelling. Studying for a PhD was all about learning new things, and now I had learned how to learn. I knew with enough time I could figure out most things – or know when it was taking me too long and I should ask for help!

In universities I had been aware of being a first-generation university goer and of not having been to private school, and also of being White.

After my PhD, I stayed at university to do research applying mathematics to the problems of global health, but I found myself becoming disillusioned with academia. As a postdoctoral researcher I worked on some amazing mathematical problems and with some great scientists modelling infectious diseases. But I found myself reflecting on my place in global health research. In universities I had been aware of being a first-generation university goer and of not having been to private school, and also of being White. But I never really thought about what it meant to be White, British, and working in global health. 

My definition of success has changed a lot from starting at university and wanting to change the world with maths.

I was motivated to work in infectious disease modelling to use maths for good, but in my role as a postdoctoral researcher I felt I was not helping to support the decolonisation of global health. I decided to leave academia to set up the social enterprise I run now. I aim to create accessible training opportunities for learners in the Global South.

My definition of success has changed a lot from starting at university and wanting to change the world with maths. And to the aspiring mathematicians, the struggling ‘not a mathematicians’: know that the path to success is not linear, or even constant, but something which keeps changing the more you learn.

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Karem Guzmán Elgueta

Karem Guzmán Elgueta

Born in Los Vilos, Chile • Birth year 1990 • Studied B. Sc. in Mathematics and ​ B. Sc. in Mathematical Engineering at Universidad de Santiago in Santiago, Chile • Highest degree Master in Statistics • Lives in Santiago, Chile • Occupation Financial Advisory Consultant

My relationship with mathematics began when one day in high school a classmate asked me: “Karem, you are very good at mathematics, have you thought about studying it at university?” I will never forget this question because it was this one that made me aware of my love for mathematics. Since I was little, I had a knack for numbers and the subject always entertained me, so I decided to formally continue studying Mathematical Engineering at University.

During college, mathematics opened a new world, a lot of theory and logic work. It was not easy, including many hours of study and frustrations, and not always achieving good exam results. It was a long and hard road, but with resilience I managed to finish successfully.

I liked the time flexibility these jobs gave me, but they didn’t make me happy, as I felt a sense of intellectual emptiness. This is why I decided to go back to university to pursue a Master’s degree in statistics and you can’t imagine how much I liked it!

After graduating, I worked for two years as a high school teacher and as an assistant professor at the university. I liked the time flexibility these jobs gave me, but they didn’t make me happy, as I felt a sense of intellectual emptiness. This is why I decided to go back to university to pursue a Master’s degree in statistics and you can’t imagine how much I liked it! I was fascinated by the subjects associated with models and their theories (data mining, predictive modeling, supervised and unsupervised learning as well as time series, among other models), so today I am a lover of statistics.

Could you imagine what would happen if one day you make a withdrawal from your card and the bank denies it for not having funds? A systemic shock would surely occur, so these models are essential.

I am currently working for a professional services firm and I have experience in credit risk modeling projects, e.g. provision models under local regulations and International Financial Reporting Standards, countercyclical provision models, forward looking models, management models such as admission, behavior and collection, as well as in liquidity risk projects, e.g. construction of flow projection models/methodologies. Credit risk models, in general, aim to mitigate the risk of non-compliance with contracted payments, so provision models estimate an amount of money that a financial institution could eventually lose if all its customers decide not to pay. Management models, such as admission models, aim to estimate a client’s ability to meet their payment obligations, and thus help the financial institution to select its clients. On the other hand, liquidity risk models seek to ensure sufficient cash flow to comply with all normal operations associated with a financial institution: deposits, drafts, transfers, withdrawals of investment funds, etc. Could you imagine what would happen if one day you make a withdrawal from your card and the bank denies it for not having funds? A systemic shock would surely occur, so these models are essential.

My work is dynamic and very demanding, but I love it because I never do the same thing. There are always new projects and clients to care for, so I enjoy my work every day. I invite all women who like mathematics to dare and study it without fear, and if you also have an inclination for finance, then the world is yours!

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Dr Beate Ehrhardt

Dr Beate Ehrhardt

Born in Walsrode, Germany • Birth year 1987 • Studied Mathematics in Bremen, Germany • Highest Degree PhD in Mathematical Statistics • Lives in Bath, UK • Occupation Mathematical Innovation Research Associate at Institute for Mathematical Innovation, University of Bath

I am a 33-year-old applied mathematician and data analysis expert with a PhD in Mathematical Statistics from University College London. I hold a permanent, research-only position at the Institute for Mathematical Innovation (IMI) at the University of Bath. Before joining the IMI, I worked as a Senior Research Statistician at the global pharmaceutical company AstraZeneca. I have a 2-year-old daughter and am expecting my second child any day.

Growing up with two sisters and a brother, my father never told us there was a difference between boys and girls. Instead, he instilled in us an understanding that we can achieve what we want with hard work. As a result, whenever people tell me I cannot do something I take it as a challenge rather than a dead-end.

I love mathematics. I love learning. I love people. And I love science. But most of all I love when all of these four things come together. 

Ask for advice but know how to interpret it

Any kind of advice you receive from others says much more about them than about you. When I was deciding what to study after my A-levels, a teacher for advanced maths advised against “studying mathematics because it is too hard”. He was wrong. I loved every second of my undergraduate programme in mathematics. All of a sudden I was surrounded by like-minded people and could solve riddles day in and day out. Studying mathematics was the best choice for me. It was intense – and yes – it was hard work, but it was so rewarding. I learned to describe the world in equations, see the world in trends, identify patterns, and extract information from all the noise. I found a way to explain the world and found out I was really good at it! Looking back on it now, I understand that my teacher was not judging whether I would be good enough to study mathematics but rather was projecting his own experiences and difficulties studying maths. That is why I would suggest: Ask for advice but know how to interpret it.

I particularly enjoyed the statistics part of my undergraduate degree but wanted to understand further the maths behind it. So, I decided to pursue a PhD in mathematical statistics. Having been abroad to Cardiff, UK for an ERASMUS exchange during my undergraduate, I knew I wanted to be in an international environment surrounded by people from many different backgrounds and cultures for my PhD. When I heard about a PhD position at University College London on the mathematics of networks I was immediately intrigued. Before signing up, I met twice with my future supervisor, which was an incredibly good opportunity to get to know him and his team a little bit. I believe the PhD experience is strongly influenced by the research group you are joining and thus, I would very much recommend trying to find out about them as much as you can. In contrary to the common stereotype that a PhD in mathematics is lonely, I experienced quite the opposite. I joined a small research group of brilliant colleagues – some of whom I still call up nowadays to discuss research ideas, and I also was part of a cohort of PhD students that formed a support network for each other. There was always someone to discuss Maths with, or to join me for a pint when a break was needed.

(…) the very best you can do for you and your career is to discover what gets you out of bed in the morning with a smile

During my PhD, I discovered my talent for proving theorems, and there were multiple opportunities to do a Postdoc on related topics. However, being good at something does not always mean it is what you enjoy doing most. At UCL, I was fortunate to be exposed to many different types of research, which enabled me to understand that what really fascinates me are the insights one can draw from data and the corresponding impact rather than the actual tools used. So, after four years of carefully building a network and investing time and effort to build a strong foundation for a research career, I made (what felt like) a radical decision to leave academia and to join the research-end of industry where I can apply my knowledge to add insights to science with an immediate impact to the real world. Many colleagues and friends were shocked by my move including the research group I was part of, which made the decision even harder.      

Now, five years after finishing my PhD, I know it was undoubtedly the right move for me for two main reasons. First, the line between industry and academia is not as rigid as I thought. The move from a research-in-industry position back to academia is increasingly common, and the work I do now at the Institute for Mathematical Innovation is from a mathematical point-of-view very similar to my work at the pharmaceutical company. Second, and most importantly, the move enabled me to experience research in a very applied setting. Most of the work I have done post-PhD has involved engaging with multi-disciplinary teams working together towards an overarching goal. Each new project comes with its own data analytical challenges while at the same time allowing me to learn about research in a variety of disciplines. Whether it is tiny scissors that allow us to edit DNA (called Crispr Cas9) or contributing to our knowledge about the growth of black holes, the work is always fascinating. Everybody’s motivations are different and the very best you can do for you and your career is to discover what gets you out of bed in the morning with a smile.

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