I am a recent grad who is interested in Data Science and wants to use technology and data to make the world a better place. While I love physics, I have also learned that solving puzzles in data science is an incredibly rewarding, powerful, and fun tool that can be applied to almost any field. I hope to continue working in the data science and continue to solve puzzles every day while exploring the world and meeting new people!
I have a bachelor's degree in physics from the University of California - Davis and have been doing research in astrophysics for the past couple years. Currently I am conducting research in cosmology by studying galaxy clusters to understand the properties of dark matter. The work I do is a lot of fun and has helped me develop skills in researching, data analysis, and writing professional documents. My group just submitted a paper for publishing that I am second author on and did the vast majority of the data analysis for. Drop me a line if you have any questions about it. I'm always happy to talk about my work!
I taught myself Python during my first year of college in preparation for a C language programming course that I had to take later. Since then I have used Python almost daily to conduct research in the physics department and do a few side projects along the way. In doing so, I have learned to use multiple Python packages, such as scikit-learn, pandas, numpy, and matplotlib. I also have a little experience with C/C++, SQL, HTML/CSS, and the Google Cloud Vision API. I am currently focusing on machine learning techniques and trying out a few smaller projects to get comfortable with the ins and outs of the relevant packages. I'm also working on my second large data science project in astronomy where I'm hoping to get a second paper to publication within the year.
I financed my degree with many part-time jobs dating back to my high school years. I've worked at a ski resort as a ski instructor, a grocery store as a stocker, a cafeteria as a server, a library as a desk supervisor, and physics laboratory as a research assistant in the past few years. From these places I've learned how to work in a team, lead projects, create a positive work environment, and be determined enough to finish multi-year projects. My experiences have molded me into a more responsible, hard-working, passionate person. I'm glad I experienced working at each of these positions, but I am now looking for a new adventure and a more permanent career position in data science.
I love hiking, running, and anything that involves being outside with people. I hope to travel all around the world and meet new, exciting people.
My research mentor for the past couple years recently published the textbook The Elements of Relativity, which teaches the concepts of relativity without going into enough detail to require calculus. He asked me to help write the solutions manual for the book, which involves me writing explanations for each problem as well as developing the required figures to explain the concepts behind each problem, all of which is later edited by him. Doing this project has allowed me to work on my technical writing skills, as I need to be able to write solutions to conceptually complex problems in ways that someone without a math or physics background can understand. This has been a fun challenge so far and I am glad I have been able to have this opportunity.
I recently started this project to determine how long it has been since dark matter halos in the BigMDPL simulation have been involved in a major merger event. By constraining the cool down time of galaxy cluster mergers, we can better understand the BCG wobbling effect that occurs. Similar to the last project I finished, I am using a mix of SQL and Python to grab relevant data and filter through it to find the specific pieces I need. The new challenge presented here though is that the data sets are much larger for the entire project. This is forcing me to use new algorithms while scanning data and to be smarter in how I code. Instead of just figuring out ways to solve problems and using the first one I come up with, I save time and computing power by refining my ideas to be more efficient. For example, instead of looping through entire data sets, I am using binary searches on sorted lists to piece together parts of the data set so that I can go back through them later much quicker. You can follow my progress through my Github repository.
This has been the largest project I've worked on by far. This project was motivated to study the dynamics of merging galaxy clusters by constraining the viewing angle of a few well known clusters. From studying this we hope to learn about the properties of dark matter on a large scale. My responsibilities included retrieving data, researching relevant cosmological phenomena, giving input on project direction, cleaning/processing data, creating visualizations to show our results, and explaining our process and conclusions in our paper. You can view our paper or check out my Github repository for this project. This was my first long-time project and I learned a lot from it. From cleaning up plots, learning SQL, and honing my data analysis skills with Python, almost everything I did for this project was unfamiliar territory. This made work both fun and frustrating at times. I've become a much better programmer and solved many fun puzzles along the way.
I participated in the HackDavis 2018 as part of a team of four that created the "High Marks" web applet. In 24 hours, we learned how to used the Google Cloud Vision API, implemented it as a web applet, deployed a semi-useable product, and won a cup stacking competition while having a lot of fun! Our team decided to create a web applet that would use a picture of text, such as notes for a class or an academic article, and organize the text by highlighted color. This would allow the user to highlight key terms, key ideas, and confusing sections in different colors, and take a picture of it that the applet would then organize to make it easy to go back over later. We never were able to finish a final product, but we were able to get the applet running on one of our machines within the last hour of the competition and demoed our product to judges in the end. I consider it a pretty big success since nobody on our team had ever deployed an applet, used the Google Cloud API, or been to a hackathon before. We have the code in our Github repository and our project description on the Devpost website.
Right now I am working on Time Since Collision project in my free time while looking for a job. I'm hoping to have the journal paper for this project ready for publication by the end of the year. I'm also working on writing a solutions manual for a introductory level general relativity textbook and teaching myself some machine learning techniques so that I can use them in future projects.
