DataScience

16
Oct
2024
Michelle Snider

Michelle Snider

Studied Physics & Mathematics at Smith College, Northampton MA, and Mathematics at the University of California San Diego, CA USA and at Cornell University, Ithaca, NY USA • Highest Degree: PhD in Mathematics • Lives in United States • Occupation: Senior Data Analyst at SRT Labs and Adjunct Research Staff Member at Center for Computing Sciences, Institute for Defense Analyses

I was always interested in math and science, maybe because I was just good at it. I chose to go to a women’s college because even at the high school level, I had been the only girl in the class, and experienced some unhealthy dynamics that can occur in a gender-imbalanced environment. Finishing my double major in Math and Physics in an enthusiastic and supportive environment, I decided I was happy to keep learning for the sake of learning, so I started applying to graduate school. 

I went to the University of California, San Diego because they had big math and applied math departments, and since I didn’t have a specific area of focus yet, this would give me lots of options. Two years in, I realized I had not narrowed down the list of mathematical topics I was interested in so much as the list of professors I was not interested in working with. I set up meetings with potential advisors across the departments, who did work in numerical analysis, representation theory, combinatorics, and even math education research. Rather than giving me an impromptu lecture, one professor spent 5 minutes setting up a problem, then handed me the chalk and said “Go up to the board and work out an example.” I thought to myself, I guess I’m an algebraic combinatorialist now!

My specific expertise seemed to be less relevant than my willingness and ability to jump into new research areas and tackle hard problems.

Six years and a cross-country move later, I finished my PhD. I had determined that I didn’t want to pursue an academic track, but with such a pure math background, I wasn’t sure what other options I would even have. That is, in academia, it is quite common that you have no idea what else to do except be an academic because no pure math professor I have met has ever done anything other than be a pure math professor. While I had a wonderful opportunity learning how to think mathematically, I had no guidance about how to transition my research to real life. After sending my resume to companies and national labs across the spectrum of options, I landed an interview at the Center for Computing Sciences in Maryland, a federally-funded research and development center, where the organizational ethos seemed to be to hire a bunch of smart people and remove all the administrative distractions so they can just focus on solving hard problems for the US government. The people I met at my interview were excited about their work, but also had interesting hobbies and work-life balance. My specific expertise seemed to be less relevant than my willingness and ability to jump into new research areas and tackle hard problems.

The AWM is a community of mathematicians from around the world who care about building up a network to help us all succeed and I love being a part of it.

Along the way, I had an opportunity to join the Association for Women in Mathematics (AWM) on a day trip to the US Capitol in Washington, DC, to meet with the offices of elected officials and advocate for supporting underrepresented minorities in STEM.  The AWM is a community of mathematicians from around the world who care about building up a network to help us all succeed and I love being a part of it.  These visits give us a chance to let our voices be heard, and to bring awareness to the importance of STEM across society—many politicians have never met a mathematician before, and we had the chance to try to counter some of the stereotyped images in the media. I met an amazing group of mathematicians, and before I knew it, I was the one organizing these Capitol Hill visits, then serving on several committees. 

A few years ago, an opportunity came up to work with a small technology company with a great company culture. My job title is Senior Data Analyst, but again I was hired not for specific expertise but for my flexibility in taking on new challenges. I get to work across a broad swath of the company, talking to clients, designing solutions, and yes, analyzing some data along the way. I love being able to apply mathematical thinking to problems perhaps not thought of as classical mathematical problems, like how to help universities save energy by connecting their air conditioning system to their class scheduling system.

I could not have predicted the path that I’ve been on, and certainly would never say that I had a plan all along. I am happy to do lots of different things, but it matters a lot to me who I spend my time with. Picking each step based on the people I enjoy spending time with seems to be working just fine so far. 

Posted by HMS in Stories, 0 comments
01
Mar
2023
Anna Konstorum

Anna Konstorum

Studied Biology/Bioinformatics at McGill University, Canada, and University of California, Los Angeles, USA, and Mathematics at University of California, Irvine, USA • Highest Degree PhD in Mathematics • Lives in United States • Occupation Research Staff Member at Center for Computing Sciences, Institute for Defense Analyses

I came to applied mathematics slowly, and circuitously – but sometimes that makes for the best stories. When I was young, I fell in love with the complexity of biological processes, and thus I chose to study biology for my BSc. My grandmother was a math teacher and I have fond memories of us playing all sorts of educational math games growing up, which instilled in me a joyful, non-competitive view of math. But I never saw myself as a mathematician, it was just something I enjoyed ‘on the side’.

I sat there in complete astonishment of the beauty and power of math to describe a world that I had realized I had always wanted to see in a mathematical light.

It was only when doing my Master’s, when I took a course focused on using dynamical systems to study the life sciences, that I came to see that mathematics needed to be more than a hobby for me. I sat there in complete astonishment of the beauty and power of math to describe a world that I had realized I had always wanted to see in a mathematical light. And, I felt then, everything clicked. That my love for math and complex systems such as biology were not separate, but actually completely intertwined. It was this realization that led me to do my PhD in mathematics. I performed research modeling interactions of growing tumors with their microenvironment and took classes in a wide range of mathematical subdisciplines. It was very difficult as I knew I had less experience with mathematics than many of my peers, but I also had complementary skills in working on real-world scientific problems, which gave me a unique vantage point to think about the methods I was studying. When I kept my focus on the subject matter, I knew I was where I needed to be. It was one of the hardest, but most rewarding experiences in my life.

I work at the interface of data science and applied mathematics to help address challenging problem sets in national security, and more generally in the computational and data science realms.

Something you come to understand by taking a strong pivot, is that both you and the world have the capacity to honor a new stage in your life and career, especially if you approach the challenge thoughtfully and creatively. I had come to understand that for me, the next stage that I wanted to reach was to expand my applied mathematics capabilities to new domains in addition to the life sciences. And, really, I was ready! Studying the life sciences from a mathematical perspective prepares you to handle a variety of complex data problems. The field is full of extremely noisy data – but data that has, if you chip at it long enough, fascinating patterns and meaning underneath the noise. I now get to do just that as a Research Staff Member at the Center for Computing Sciences, Institute for Defense Analyses (CCS/IDA). I work at the interface of data science and applied mathematics to help address challenging problem sets in national security, and more generally in the computational and data science realms. I’ve used approaches ranging from applied dynamical systems (PDEs and ODEs) to, more recently, unsupervised learning methods employing matrix- and tensor-decomposition frameworks. I also hold an adjunct faculty role in the Laboratory for Systems Medicine at the University of Florida, which allows me to continue to collaborate on projects in mathematical and systems biology.

I wish I had known to take advantage of all [professional societies] have to offer earlier in my career.

What I’ve come to realize is that your unique interests and capabilities, even when they may not fit easily into a clear label, do have a place in this world where they will be valued. My background in mathematical biology has given me a unique perspective on the challenges I face in my current role, both from a mathematical and applied sense. And it makes for some fun intersectional research.

Finally, I’d like to make a quick shout-out to the power of professional societies. I wish I had known to take advantage of all they have to offer earlier in my career. Societies like the American Mathematical Society (AMS), Society for Industrial and Applied Mathematics (SIAM), Association for Women in Mathematics (AWM), and Society for Mathematical Biology (SMB) all provide opportunities to network via conferences and meetings, and to learn more about opportunities in and outside of academia utilizing the skills you learn. You don’t need a minimum degree to join – just an interest to connect with like-minded researchers.

Posted by HMS in Stories
22
Jun
2022
Karrie Liu

Karrie Liu

Born in Hong Kong • Studied Mathematics at University of York, UK • Highest Degree MSc in Applied Mathematics • Lives in London, UK • Occupation Freelance Mathematician / Founder of an analytical advisory company

Growing up in two distinct family cultures (Chinese parents in Hong Kong and “adoptive” English parents in the UK), I noticed that girls weren’t often encouraged in the same way that boys were. Many Asian parents would prefer that their daughters marry and focus on family rather than pursuing studies in higher education. Due to this, I wish to be a role model to younger generations, especially girls, so that they may be inspired and have the courage to follow their dreams. My ultimate goal is to improve the world through maths, data science and technology. Hence, that is why I set up an analytical consultancy company called the analytical advisory company Hypatia Analytics Ltd in 2019, which allowed me to spend more time on different types of charity work.

My ultimate goal is to improve the world through maths, data science and technology.

Since graduating from university, I have been applying my skills to continuously show people how they can use mathematics in healthcare and life sciences. During my tenure at the National Health Service (NHS), I participated in several diversity and equality projects. The NHS lacks information on ethnicity and I noticed that researchers had to use the general label “South Asian Name programme” to gather more details. I headlined a project discovering whether extra details can improve the name-test accuracy and to carry out diagnostics tests using patients’ self-reported ethnicity as the standard compared to test results. The outcome has been widely adopted in the Bradford/Leicester council area, improving NHS data and enabling valuable insights for local health economics planning.

Since data science is a relatively new type of career, many people haven’t yet fully understood why it is needed and how to apply it in the real world. Education is the key for people who want to be specialized professionals, but they also need to make the field accessible to the general population. My role as a trustee at The Institute of Mathematics and its Applications (IMA) allowed me to chair three national conferences to showcase how mathematics can be used with data science and helping others to get more help from the industry. 

My company [..] acts as an analytical advisor for charities providing statistical support for clean water programmes, using data science and technology to improve design and optimise resources needed to implement systems.

Skill-based volunteering is also very close to my heart; with my company Hypatia Analytics Ltd I have had the opportunity to voluntarily lead tech and maths projects engaging with the public and different charity organisations. Hypatia Analytics Ltd acts as an analytical advisor for charities providing statistical support for clean water programmes, using data science and technology to improve design and optimise resources needed to implement systems. The charity’s aim is for people’s lives to improve from having clean water close to their home. Hence, more children have time to attend school and the prevalence of illnesses is decreased.

In the summer of 2021, Hypatia Analytics Ltd in partnership with a charity promoting mathematics set up a Math & Data Summer programme called “Discover Data”. This program is a series of introductory workshops on how applied mathematics with real-world evidence can be used to address the world’s problems to students aged 14-17. However, the program  did not stop there, it had set up a monthly meeting to teach more, and we are now planning Summer 2022 face-to-face workshop.

I believe data and mathematics are at the heart of better decision-making and hope that people can benefit from it.

Posted by HMS in Stories
15
Sep
2021
Maylin Wartenberg

Maylin Wartenberg

Born in Braunschweig, Germany • Studied Math (diploma) at the Technical University in Braunschweig, Germany • Highest Degree Doctorate in Math (Dr. rer. nat.) • Lives in Meine, Germany • Occupation Professor at the Hochschule Hannover – University of Applied Sciences and Arts, Department of Business Information Systems, Field of Data Science

Analytical thinking has always been easy for me. Therefore, I enjoyed the rules and patterns that occur in math from early on. Luckily, I recovered quickly after the German high school greeted me with the minimum pass mark “adequate” in the first two math exams in 7th grade. In 9th and 10th grade, we had a very strict “old school” teacher who left a lasting impression. We always had to stand up to greet him, and if you used a swear word in class, you had to wash the glasses in the chemistry room during the next break. He was strict, but he liked me and I learned a lot. In 11th grade I spent a high school year in the US and after this year I wanted to take math as one of my advanced courses. That was a tough decision because all I did at the American high school was statistics whereas in Germany everyone had started with curve sketching. After my return to Germany, the first exam in 12th grade was about this topic. I didn’t know anything about it and I had 6 weeks of summer break to study. A former very kind teacher helped me with the material and I studied by myself and achieved a good mark. That was a major milestone to my decision to study math, since I was able to teach myself the topics of almost a whole school year. But I still wasn’t sure. Math or psychology?

After all the ups and downs you typically encounter during this phase – 3 years for me – I finished my doctoral thesis in math (graph theory) two weeks before my first daughter was born.

Both sounded very attractive to my 19-year-old self. The plans to move to Braunschweig with two of my friends were already settled and I finally chose math because it was giving me a wider range of options on what future opportunities to follow – because I had no clue what to do after my studies at that point. In the beginning we were quite a few students, but in the end only 4 of us were left in pure math – 25% women 😉. I chose most of my courses in abstract math – algebra, combinatorics – and did as little applied math as possible. I really enjoyed the study of group and ring structures and the book Algebra by Serge Lang was always by my side. I already dreamed of becoming a professor myself.

Yet, in the end, the question what to do with all the knowledge I gained crept more and more into my consciousness. That is why I didn’t pursue a strictly academic career, nevertheless I still wanted to secure the option, and chose a PHD position in business at Bosch (formerly Blaupunkt) in Hildesheim. No more group and ring theory, suddenly I had to write code in C++ for algorithms in navigation systems. I had avoided any computer science so far, thus, I was thrown in at the deep end. But I never regretted this step because I discovered that coding is not all at all as difficult as I thought – after all it’s logical – and I learned a lot about working in a bigger company. After all the ups and downs you typically encounter during this phase – 3 years for me – I finished my doctoral thesis in math (graph theory) two weeks before my first daughter was born.

I found the fitting position where I can combine my passion for analytical thinking, my academic background, and my work experience (…).

I stayed home with her and somehow managed the defence of my doctoral thesies with a 5-month-old baby and still deprived of decent sleep. After 8 or 9 months at home, my brain started asking to be challenged again, and I began to apply for jobs in industry. As a young mother I wanted to start part time, but as a woman holding a doctorate in mathematics that was not as easy to get as I hoped. After a long search, including several offers with 40 hours and more, I was finally rewarded by starting a job at VW Financial Services. My one-year-old daughter was able to stay at the company’s own childcare facility and I started with 27 hours a week as a systems analyst in the business intelligence department in IT. In almost 10 years I made my way from analyst, to project lead, to team lead all the way to head of two sub-departments and got enrolled in the management trainee program – most of this in part time including a maternity leave when I had my second daughter in between. Then, suddenly, another option which had gotten a little out of sight but was still a silent dream popped back in.

And that is my way to my current position as a professor in business computing, especially data science. I found the fitting position where I can combine my passion for analytical thinking, my academic background, and my work experience – all of that with the advantage of being my own boss, still doing interesting projects with different companies, giving talks about AI for lay audiences (schools, senior clubs, …), and guiding young people on part of their own story.

Posted by HMS in Stories