What I have worked on:
+ Collaborated on a cross-functional team to develop an iOS app to find, log, and review books.
+ Utilized Google Cloud Platform for end-to-end development and Firebase Firestore databases to process user data, accessing book information from the Google Books API.
+ Developed app with Swift and SwiftUI, releasing the app for beta testing on the iPhone app store.+ Completed user research to ensure high customer value and user interface.
+ Worked on a team to create a gamified mental health app aimed at giving users accessible and friendly resources, using artificial intelligence and natural language processing to offer personalized recommendations.
+ Worked on the front end to convert designs to useable interfaces, quickly picking up SwiftUI and app development.
+ Honed communication skills and time management, working on a team of 7 to deliver on a fast-paced software development cycle, earning top spots in various app design competitions.
+ Spearheaded a feature to track users’ mental health data to give users custom plans using machine learning to analyze the large data set and use various psychology sources to give accurate feedback.
+ Java application aimed to connect students in person using hypothetical location data and filtered matches between users based on fields of study and interests.
+ Teamed with fellow students using Figma, starting the project in WINFO Hackathon 2024 and continuing the implementation with help from industry professionals and self-learning.
+ 9-hour initial build with algorithm architecture draft and three-month deliverable design implementation, utilizing Gradle and the JVM to release documentation on the prototype.
+ Excelled in weekly online Python training program, learning machine learning and data modeling techniques.
+ Mastered data cleaning/visualization and statistical representation techniques through over 100 hands-on data analysis projects with large data sets from various international sources.
+ Gained coding experience and deepened knowledge of machine learning models, such as Linear/Logistic Regression, Random Forest Classifier, and Fast Fourier Transformations.
+ Java object-oriented program utilizing Dijkstra's graph algorithm to find the path of pixels with the least energy within an image.
+ 3-week long development stage, building upon CSE 373 curriculum.