In this final year of the grant, the Computational Bootcamp ran online (due to COVID-19) with an enthusiastic group of 16 students, and three students did internships funded and/or arranged by the PI4 program. Other students found internships through the sister program PI4-IMA Internships.
Scott Harman (Wolfram Research).
Over the summer, I was an intern with the Wolfram|Alpha Math Content team, supported by the PI4 grant. I worked to improve the Step-by-Step framework for derivatives in Wolfram|Alpha. The main work was done in the Wolfram Language. The work involved bringing mathematical ideas to the table for proper calculations of derivatives, translating those ideas into a proper algorithm in Wolfram, and some pedagogical techniques in writing the steps and solutions in a coherent fashion. I was able to improve my programming skills and work in an industry setting as opposed to the academic environment that I am used to, which are valuable skills that I hope to bring to my career after graduation.
Shinhae Park (Corteva Agriscience).
I took part in a project on “Spray Atomization Nucleation in Two-Phase Flow”. It was a cool project with clear goals, motivations and deliverables to the company and the industry. Considering that this project was exploring a whole new area to me, I knew I would find it extremely challenging. In the beginning I had small doubts and was questioning whether I would be able to complete the project successfully. But as we advanced towards the objective, the project team helped me become more confident and certain of my capabilities.
Furthermore, the internship at Corteva broadened my career horizons.
During the summer, I observed from recurring seminars at Corteva that scientists with different specialties (such as math, biology, chemistry, statistics) collaborated on interesting tasks. Previously I was pursuing Data Science positions, but now I am seeking quantitative research positions as well. Soon, I will be applying for full-time jobs and this internship was the perfect experience for me. All things considered, I had a greatly productive summer with Corteva.
Dara Zirlin (Ameren Innovation Center).
This summer I worked at Ameren using AMI meter data to find errors in the utility company’s secondary connectivity model. At each home there is a meter that measures electricity consumption and these meters are attached to transformers outside the home. Transformers can be attached to multiple meters. Utility companies keep records of which meter is connected to which transformer. However, these records can be inaccurate, as the meter to transformer connections can be changed while fixing power outages and these changes are sometimes not recorded. It is important to know which transformer a meter is connected to, as homes may be alerted that there is a power outage, when there is not one. Worse, during a power outage, they may be given an inaccurate estimate for when their power will be back on. The goal of our project was to use AMI meter data to develop an algorithm that can predict when a transformer to meter connection record is inaccurate and predict what transformer the meter is connected to. Additionally, this algorithm is being tested on two different computing platforms to discover which is the most cost-effective and which is the fastest.
Additional mathematics graduate student do internships each summer, hosted locally and nationwide. See the full list here (through 2018). The PI4 grant has played a key role in catalyzing these internships.