Connor has also been co-mentored by Dr. Eric Miller at Tufts University, who connected him with CHESS for a one-of-a-kind, machine-learning and data science project opportunity. Shanks and Miller have worked together for 2 years on a project funded by the Office of Naval Research, focused on augmenting CHESS capabilities via machine learning and data science tools.
Using data collected at FAST, Connor has been developing a diffraction-spot characterization code, for which he has received a number of accolades at science and math fairs including:
- Received a gold medal at the Long Island Al Kalfus Math Fair.
- Qualifying for the second round of the New York State Science and Engineering Fair on 3/25/24
- Submitted his project as part of a successful application to the competitive summer program: Boston University RISE (~7% acceptance rate)
- Honorable Mention in the WAC Lightning Research Invitational
After attending the CHESS 2024 User Meeting, and presenting during the poster session, we sat down with Connor for an interview of his experience as a high school student engaging in a research project at FAST:
Q: How did you first get involved with CHESS and the FAST beamline project?
A: I was looking to do a computational study for my school's research class, and when browsing journal articles, I came across a study on signal processing in X-ray diffraction by Daniel Banco. After reading through the paper, I emailed the researchers involved expressing my interest in contributing to future research. Dr. Eric Miller responded, and we discussed ways for me to contribute to the FAST beamline project.
Q: Can you describe a typical day working at the FAST beamline?
A: For me, my work with the FAST beamline was done virtually. Whenever I had free time, whether during a school lunch period or in the evening after finishing homework, I would take out my laptop and work on writing and troubleshooting the code for my model. The independence I had in completing the project was much different from my experience in typical school courses, and I definitely appreciated this freedom.
Q: What were some of the challenges you faced while working on this project, and how did you overcome them?
A: A few challenges arose from a lack of experience. I jumped into this with only the knowledge from a high school coding class and thus had to self-learn how to handle the many foreign datasets and image processing concepts. Through many google searches and guidance from Eric L Miller and Kate Shanks, I was able to learn a lot from these challenges.
Q: What specific data science and machine learning techniques did you apply in your research?
A: I applied various image-processing techniques, working with image data obtained from FAST beamtimes. I applied blob-detection to precisely locate spots and Gaussian peak fitting in order to extract numerical parameters. I also spent a lot of time on data sorting, relating spot reconstruction files to the raw datasets.
Q: How did your work contribute to the overall goals of the grant from the Office of Naval Research?
A: My project was able to contribute to the line of work of SPOT-FETCH within the grant, providing a framework for analyzing individual diffraction peaks in real-time.
Q: What did receiving a gold medal at the Long Island Al Kalfus Math Fair mean to you?
A: Receiving gold at the Long Island Math Fair was a very important award, as it was the result of both my work in the CHESS project and my preparation for the fair in the Math Research 11 class. Being recognized by others in the field of math and data science created a great sense of validation.
Q: What insights or feedback did you gain from participating in the WAC Lightning Research Invitational and receiving an Honorable Mention?
A: The WAC Lighting Research Invitational was a great way to present to local judges with experience in similar fields. I was able to interact with researchers in chemistry and materials science at local universities and labs, particularly one judge from the Brookhaven National Laboratory, who suggested that I visit their synchrotron NSLS-II.
Q: How has working with Dr. Eric Miller and other mentors influenced your research and career aspirations?
A: Working with Dr. Miller and getting involved with CHESS has deepened my interest in physics, which I now intend to pursue in future studies. Having more experience with data science will be helpful throughout my career, and I am quite interested in future computational studies. Also, my positive experience working with CHESS and visiting campus during the User Meeting has made me take a liking to Cornell University, where I will definitely be applying to in the fall.
Q: What advice would you give to other high school students interested in pursuing research in data science or machine learning?
A: Find work with interesting real-world applications, as I believe the use of computation as a tool is where it really shines. I would also recommend having a strong understanding of math and programming concepts, as being able to think of and develop algorithms is vital. Specific programming languages and data science methods can be learned more quickly if you have a good background.
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