Information
arpaterso@att.net
github.com/abster042
Education
University of California San Diego
Cognitive Science Machine Learning BS
Visual Arts and Computer Science minors
Sept 2016 - Dec 2020
GPA 3.39
Universidad Carlos III de Madrid
Sept 2019 - Dec 2019
UCEAP Study Abraod
Relevant Coursework
Supervised Machine Learning 1
Software Engineering
Applied Linear Algebra
Data Science in Practice
Adv. Statistics and Probability
Neural Signal Processing
Technical Skills
Programming in Python
Adobe Photoshop
User Research
Programming in JAVA
Programming in C++
Spanish Language
Using html
The Sorenson Impact Center performs policy and economic analysis for programs helping to create a more equitable world, with focuses on higher education and early childhood outcomes. In my position, I worked collecting, cleaning, analyzing, and presenting data. I also headed a project to analyze the effects of COVID-19 on one of the center’s ongoing projects around prenatal to three-year- old childhood development. This project has allowed me to learn how to manage different aspects of a project from start to finish as well as hone my data science skills.
As an undergraduate researcher at the UCSD ProtoLab, I worked as a user experience designer. I worked with a team of other students, professors, university administrators, and outside stakeholders to design the website and promotional materials for one of the lab's projects. Due to the nature of the of the project as a competition for civic design, I got to see how my field and others worked together. This position showed me how to integrate design research and practice in a real world context and how to manage stakeholders.
I was an instructional assistant for the class "Sensation and Perception", and upperdivision elective in my major. In this position I was responsible for holding lab sections once a week, creating test questions from lecture material, holding office hours, and helping to proctor exams. I learned how to effectively teach students new material and run interactive labs to enforce it. I strengthened my leadership skills as a leader and my networking skills as an employee.
LabSmith is a microfluidics company that makes research products. For three consecutive summers, I worked as an "all-purpose" intern. I maintained their Facebook page, updated the products listings on their website, and assembled certain products. This position taught me new skills in business administration, and industry website management. Lastly, through coming back for 3 summers, I learned how to work and develop with a business over time.
From Neural Signal Processing, UCSD winter 2020. Our team sought to see if machine learning can be accurately used to predict emotion based on EEG data. We went through a comprehensive research process, starting with a review of the existing literature, then we had to iterate and adapt to our circumstances. Finally, using open source data, we used python machine learning methods to clean the data and test our hypothesis with various supervised learning methods. We were able to train these accessible classifiers with very decent accuracy, and though we could not collect our own data, we learned invaluable skills for working within your constraints to the best results
From Supervised Machine Learning, UCSD spring 2019 Using python and working from several famous and open source machine learning datasets, I performed an experiment comparing the results Logistic Regression, kNN, and SVM machine learning algorithms. In addition to exploring the different classifers, I tested different data test versus train partitions, and regulariztion parameters in a cross validation process.
From Data Science in Practice, UCSD winter 2019 Tasked with investigating real world data, my team decided to investigate the relationship between racial demographics and public health outcomes in the United States My team gathered, parsed, and cleaned data from US counties on infant mortality rate and racial demographics. Using python, we preformed statistical tests, and data representatoins. We were able to determine there is a positive correlation between a county’s racial demographics and infant mortality rate