Joliet, Illinois, United States
I am a computer sciences student at the University of Illinois at Chicago (UIC) and I am eager to apply my skills to working on projects in internships. During the summer after my freshman year, I've completed an internship through Breakthrough Tech at Google to learn about the user research and product design process. I was delighted to apply my creativity into brainstorming ideas and creating prototypes to illustrate how to utilize existing software to enhance current products. Currently, I'm also serving as a TA for a CS course at UIC. I am passionate about helping other students learn and succeed. In this role, I am challenged to utilize my problem-solving skills to help my students with variety of coding problems and practice my communication skills. Through my studies, I have gained experience with developing and testing applications and programs. I am familiar with several coding languages including Java, C/C++, and python. I am interested in app development and software engineering.
Built and deployed a Java Spring Boot application to validate AWS Simple Email Service (SES) integrations using Terraform and Kubernetes, enabling internal teams to simulate real-world usage and better troubleshoot issues across environments Designed Figma wireframes to propose an improved developer experience for an internal product, synthesizing cross-team feedback and technical constraints to deliver both a streamlined MVP and a more comprehensive future-state design
Assisted in teaching Mathematical Foundations of Computing (propositional logic, proofs, sets, relations, and probability) and Programming Practicum (dynamic memory allocation, pointers, linked lists, objects/classes, debugging, testing; taught in C). Hosted 4+ hours of office hours per week helping students with lab, homework, and debugging coding projects. Dedicated 6 hours per week to guiding 80+ students with completing review worksheets and labs.
Implemented Design Thinking process to conduct primary research with 100+ participants to determine user demand for AI centric features in partially autonomous vehicles. Proposed hypotheses regarding features that would increase users' likelihood to purchase a car and created data visualizations to deduce the most valued features. Gave 2-hour presentation to leadership with prototypes of features and user scenarios to showcase feature utility.