Hello world! I’m Kimberly Herrera. I was born and raised in LA county but I’m currently in the Bay Area where I’m a senior at UC Berkeley. I study pure math and math education. I applied to SGI because I had previously gotten a taste of topological data analysis this previous summer and I guess I wanted to see other ways in which math and coding ‘mesh.’😎
Tutorial week
I’m in California so that meant waking up before 8 am which kinda sucked but I got used to it. I’m also someone who has a hard time learning remotely so I was worried, but thankfully the lecturers were great. I was able to follow along (mostly) while growing interested in the material. I think my favorite lesson was on 2D and 3D shape representations. This wasn’t particularly new to me, having worked with point clouds and cubic splines before, but Silvia was a very engaging speaker. She presented the material in a way that was so digestible. By the end of the week, I hadn’t nearly finished all of the exercises but I made sure to do a few from each lesson so I could be prepared for the coming weeks.
When ranking projects, a lot of the descriptions were just buzzwords for me. I just decided to choose whichever ones had prerequisites I satisfied. I actually got my first choice for my first project, which I chose because it involved tda.
Project 1:
In our first meeting, we introduced ourselves and our background in topology and machine learning. Our mentor then told us the goals of the project, which I made sure to write down. We then immediately went to work. I started by investigating the neural network CLIP we would be using for image classification. I also researched what feature spaces were. This project went on for 2 weeks and we only met as a team like 4 times, although we did consistently communicate through Slack. However, it did feel like “here’s what you need to do, now go do it,” which was fine with me. I was proud of my work on this project, I completed everything I needed to do and was able to communicate my findings in our meetings.
Project 2:
This project is so different from the last. This mentor started by presenting slides on the background and goals for the project. I also noticed that the TA was more active, I think because they are a graduate student of the mentor. We also meet every day in the morning and have a follow-up meeting to discuss our work for the day. That being said, I don’t think I’ve completed as much work on this project thanks to errors with running the code. Hopefully, more progress will be made in the coming days.
In comparison to previous research:
SGI has been a bit different from the REU I did last summer. Having a tutorial week and guest lectures is the same, but here we do multiple mini projects instead of deep diving into one sole project. This of course leads to engaging with different kinds of people and different work ethics. Last summer I was working 9-5 while this time it depends on the project and the mentor. Another big difference of course is how coding/cs heavy this project is compared to my previous project. Previously, we did a deeper dive into the mathematical background (since it was a math REU) and the coding was done to inform the math. Now it feels like the math is learned in order to inform the CS/Machine learning.
Overall, I am having a good time and am excited for the next two weeks 🙂
