Problem Solving

Learning how to be a good problem solver was at the heart of my training as a mathematician and it is one of my strongest skills today. I love the challenge of a new problem and the feeling of accomplishment after I find the solution.

During my time at EPFL, I had just taken over a finite element model simulation of ankle implants from a colleague who had left the lab and we discovered a problem with inconsistent simulation results. The simulations were complex and the cause could be any number of things. I was able to look through all of our data and simulations to discover the problem was in our density definition. After correcting the error, I was able to re-run the study and still deliver the results on-time to our project sponsor.

While I worked at MIT Lincoln Laboratory, I relished the opportunity to work as part of a multi-disciplinary team to solve challenging real-world problems. One of our biggest challenges was to design a self-separation software for unmanned aircraft (drones), something that had never been done before. The biggest obstacle was that the term “self separation” appeared in the international regulations, but was never defined. As part of a small team, I worked with my colleagues using Monte-Carlo methods to find a risk-based quantitative definition of self-separation, which was eventually published and used by the regulatory committees.

Data Analysis

Data analysis is a foundational skill for any applied mathematician and its the aspect of my current job that I enjoy the most. I can’t wait until my simulations are finished so that I can get my hands on the data and play with it. I love digging into results and data to find out what they really say and to discover hidden relationships.

At EPFL, while working on ankle implant research, I was able to use data analysis to draw many conclusions about which type of implant design was better, what underlying factors were correlated to increased bone damage, and what impact implant bone support had on bone damage. These conclusions were invaluable to the project sponsor, a medical device company, in marketing their product, in improving their product design, and in giving recommendations to the surgeons.

At MIT Lincoln Laboratory, I also had ample opportunity to use my love of data analysis to benefit our projects. While working to develop our collision avoidance and self-separation algorithm, our team was faced with tuning a wide variety of algorithm parameters in order to get the best algorithm. I was able to use my data analysis skills to evaluate which combinations of parameters produced the best performing algorithm. These efforts helped to speed up parameter selection and get the algorithm ready for demonstrations and testing using real aircraft.


Leadership has been a part of my life since before university and I first discovered my love of taking on leadership roles in high school. I enjoy the sense of accomplishment I get from seeing my team do well and achieve something.

After relocating to Switzerland, I volunteered at the American International Women’s Club of Geneva. This was a great opportunity for me to network and learn about my new home. However, I recognised that the club was missing out on a great opportunity: they weren’t making use of social media. I pointed this out to the leadership and was soon made the Social Media Coordinator. I formed a team to help generate ideas and manage the new social media accounts. As a result, the team was able to post relevant and interesting information about the club on a regular basis. Due to our efforts, we increased awareness of the club in our community and with other area organisations. The social media campaign also brought in new, younger members and helped to spread the word about club events to existing members.

During my time at MIT Lincoln Laboratory, many programs used an internal simulation framework to perform studies for various project sponsors. I noticed that as our number of programs grew, so too did our number of users and requirements. Many programs would develop a “make do solution” to alter the framework for their particular study. Eventually, everyone was doing this and the simulation framework became clunky to use and unable to adapt to changing needs. I organized a meeting of all stakeholders to gather requirements for the simulation framework and the timeline they had for each of their deliverables. As a result of my initiative, I was chosen to lead the upgrade process. I was able to put together a plan from the requirements and timelines my colleagues had shared and get the upgrade on track to meet everyone’s deadlines.