Swetha P
- Research Program Mentor

MS candidate at University of California Los Angeles (UCLA)

Expertise

computer science (Python, C++, Java), data science and machine learning (Scikit-Learn, numpy, Keras, Pandas, TensorFlow)

Bio

I completed my Bachelors and Masters in Computer Engineering as a part of the 5-Year BS/MS Program at the University of California, Santa Barbara. One summer, I did an internship at a tech company in the Bay Area in California as a Machine Learning Performance Engineer Intern. Through these opportunities, I found that I really enjoy data science and machine learning so I decided to pursue a second Masters in Data Science Engineering at the University of California, Los Angeles while starting full-time employment as a Data Scientist. During my graduate education, I was the teaching assistant for two courses -- I found that this was an especially rewarding experience because in explaining to other students, I was able to help them develop the intuition from the ground up on their own, as well as solidify my own understanding of the concepts. In essence, it was a win-win for everyone involved! In my free time, I like to take some time away from the screen and pursue an active and adventurous lifestyle. I enjoy hitting the gym, biking, and trying new things! I love hanging out with my friends, or my family and my dog Rocky! Fun fact -- I have a freckle in my eye!

Project ideas

Project ideas are meant to help inspire student thinking about their own project. Students are in the driver seat of their research and are free to use any or none of the ideas shared by their mentors.

Heart Attack Analysis and Prediction

Given a dataset consisting of different measurements of the human body such as age, resting blood pressure, maximum heart rate, etc., we can predict if a patient is likely to suffer a heart attack. This is very applicable and useful in healthcare today because if we could catch something like this early on, patients and medical professionals can take steps towards preventative measures early on to combat the onset of such a diagnosis. These would improve the overall well-being and quality of life of the individual. Data science and machine learning in the Python programming language would be used to study this classification task. It includes a complete end-to-end pipeline consisting of data cleaning, data transformation, Exploratory Data Analysis (EDA), model construction, model testing, and hyperparameter tuning. We would evaluate the performance of these models with multiple metrics and see how the model fares.

Python Maze Game

Build a fun maze game in Python! This would use the library Pygame to program the game using loops, conditionals, and more!

Coding skills

Python, C/C++, Arduino, Java, Android Studio, R

Languages I know

Malayalam - elementary

Teaching experience

As a graduate student, I was the teaching assistant for two courses during the year. I received the award of Outstanding TA of the Year for the Class of 2021-2022. Prior to that, in high school, I also taught at Kumon to K-12 students.