ResearchScientist

Elena Tartaglia

Elena Tartaglia

Born in Melbourne, Australia • Studied Applied Mathematics at the University of Melbourne in Australia • Highest Degree Doctor of Philosophy in Mathematical Physics • Lives in Melbourne, Australia • Occupation Research Scientist

I discovered my love of maths in high school when we started learning algebra. I had never been particularly adept at arithmetic or memorising times tables, but algebra was fun. It was about learning logical rules and applying them, step by step, to solve a problem that seemed impossible from the outset. My maths career so far has taken me from applied maths to mathematical physics to statistics and data science. Though the technical areas have been different, the pattern of understanding fundamental rules to break down big problems has remained.

I followed my heart all the way to a PhD in mathematical physics where I discovered the beauty of diagrammatic algebras: equations made out of squiggly diagrams.

My decision to pursue a career in maths came during my second year of university. I had been studying engineering, which I believed to be a more stable career choice, but after a year and a half I couldn’t get excited about any of the engineering specialisations. My Mum encouraged me to follow my heart and study mathematics: study what you love and you’ll figure out the work later, she advised. I followed my heart all the way to a PhD in mathematical physics where I discovered the beauty of diagrammatic algebras: equations made out of squiggly diagrams.

After a two-year postdoc in Italy, I decided to make the switch from academia to follow a career in data science. I had avoided any statistics and probability in my university studies, because they were not topics I enjoyed in high school, but I soon learned how interesting randomness is and how useful it is for understanding the world. I was lucky enough to land a dream job at Data61, the data analytics unit of CSIRO, Australia’s national science agency. Since then I have been working on industry projects, solving applied problems in the areas of manufacturing, wildfires and public policy with statistics and machine learning. I love that even after this career change, I can still use my mathematical thinking to break problems down into their essential ingredients and solve them step by step.

Reflecting on my path from education to employment, I have learnt that careers don’t have to follow a clear and straight path.

Reflecting on my path from education to employment, I have learnt that careers don’t have to follow a clear and straight path. I have learnt that following your dreams can be a good option, but it isn’t the only one, and that trying out adjacent areas of work that are in-demand can lead to a fulfilling occupation. I have also learnt that an important output of your studies is the ability to teach yourself new skills, because flexibility is a valuable skill in the workforce – plus learning new skills keeps your work interesting.

Posted by HMS in Stories
Jamie Prezioso

Jamie Prezioso

Born in Warren, Ohio, United State Birth year 1989 Studied Applied Mathematics at Case Western Reserve University, Cleveland, Ohio, United States Lives in Washington, D.C. United States currently a Research Scientist

Growing up, I genuinely enjoyed math from an early age. I have fond memories of solving equations and homemade arithmetic flash cards with my grandfather. He consistently and lovingly encouraged me to pursue math. And so, I did.

I had an inclination that studying mathematics would open an array of opportunities, however, I had no tangible examples of this. Nevertheless, I was drawn to pursue math.

I happily studied and excelled in mathematics throughout middle and high school. When choosing a major in college, I did not even consider math. Having never seen or learned about modern-day mathematicians in school or media, I was unaware of this entire profession. Since I was also interested in medicine, I considered studying biology. I knew of clear academic and career paths in the medical field. Ultimately, my first year in college I was undecided. I had an inclination that studying mathematics would open an array of opportunities, however, I had no tangible examples of this. Nevertheless, I was drawn to pursue math. And so, I did.

I began to discover the ways you could use mathematics to solve problems I found interesting and important, like quantifying the effects of climate change or modeling predator-prey dynamics in fragile ecosystems. I graduated from Walsh University with a Bachelor’s of Science in Mathematics. When applying for graduate programs, I had every intention of obtaining a Master’s degree in a few years and leaving the program for industry. The thought of being in school for nearly all of my twenties seemed unbearable, if not impossible. I did not want to wait for my professional career, and in some sense my “adult” personal life, to begin. Still, I was excited to pursue math. And so, I did.

Through coursework and research, I found I was truly passionate about math. I developed strong quantitative modeling and coding skills. I even got to study areas of biology and medicine.

In the Fall of 2012, I began graduate school at Case Western Reserve University. I studied applied mathematics, taught Calculus to bright undergraduates and conducted research in mathematics and computational neuroscience. It was in graduate school where I grew both personally and professionally. I had many wonderful experiences with brilliant mathematicians from all over the world, many of whom I am still close with today. Through coursework and research, I found I was truly passionate about math. I developed strong quantitative modeling and coding skills. I even got to study areas of biology and medicine. I gained confidence in myself and a deeper understanding of mathematics. And so, I obtained a PhD in Applied Mathematics.

I use my background in mathematics to research machine learning (ML) and artificial intelligence (AI) models […]

Now, I am an Applied Mathematician. I am a Research Scientist at a consulting firm in the Washington, D.C. area. I use my background in mathematics to research machine learning (ML) and artificial intelligence (AI) models, focusing on interpretability and explainability. While AI/ML models have proven extremely useful on a variety of tasks, their inherent black-box nature and lack of interpretability limits their use in critical applications, like medicine or autonomous driving. Specifically, I research and develop neural networks, mathematical models which are typically highly over-parameterized but have exhibited superior performance on high dimensional data (e.g. images), trying to better understand how these models make predictions, assess their confidence and incorporate prior expert knowledge.

I feel very fortunate to have a career which aligns with my field of study and allows me to work on problems I am passionate and excited about. I hope that my story, and the stories of the other women here, highlight the vast number of exciting opportunities and careers in mathematics, the careers that I was unaware of for so long.

Posted by HMS in Stories