Sylphrena Kleinsasser, a CLASSE-sponsored REU student, is working on a project that will enhance the user experience at CHESS. By developing machine-learning-based models to predict material behavior, Syl explains that users can spend their time more efficiently before coming to the beamline.
Sylphrena Kleinsasser is a student at Lycoming College in Pennsylvania. Syl explains that the particle accelerator on campus is what drew them to accept the REU experience at Cornell.
Syl’s summer project at CLASSE has been to develop machine learning-based models for predicting material behavior with uncertainty quantification, with applications for this research aimed at finding better materials with specific properties for future particle accelerators and SRF cavities.
“There are lots of candidates out there for materials scientists to test and see if their material is a good fit for high-temperature superconductors," says Syl. "A machine learning model can predict their properties so we are not testing materials that we don’t necessarily want.”
Syl, a computational physics major at Lycoming College in Pennsylvania brings their data science skills to this project. By using a library in Python, Syl can extract up to 52 features from their dataset to train their models. Syl explains that they are using a data set with 16,000 different materials to train his data set, while also adding uncertainty measurements to this process.
“I have only a little background in material science, and my experience with machine learning is limited to an introductory course," says Syl. "However, my research project revolves around computer science, not necessarily physics, so gaining an understanding of the applications of particle accelerators has probably been the biggest hurdle.”
“You don’t really get that at many other places,”
Syl says that this experience may not be exactly like graduate school, but it is close. And it has given Syl the experience needed to pursue a future in data science.
"I am working on a lot of code to create our models — working closely with physics researchers has helped me understand the field and decide whether graduate school is right for me."
Coming from a small city that is roughly the same size as Ithaca, Syl is pleased at the amount of activities around town. "Graduate school at a place like Cornell University is really tempting," says Syl. "But I have found that I really enjoy data science, and want to pursue this further."
Syl explains that they were accepted into multiple REU programs, but ultimately chose Cornell because of the opportunity to work with the particle accelerator on campus, and the focus on particle physics. “You don’t really get that at many other places,” says Syl.