Associate Software Engineer in the Tech Development Program working on IVR (Interactive Voice Response) systems under Claims.

As part of a team, our project was to engineer an AI chatbot application for the Travel & Hospitality Industry, specifically designed for WhatsApp. The application was built using Google VertexAI's PaLM LLM, LangChain, MongoDB, and APIs, with the aim of enhancing tourists' experiences by providing engaging conversations, accurate and up-to-date answers, live data, and recommendations for Atlanta's attractions (World of Coca-Cola, Zoo Atlanta, Georgia Aquarium), hotels (like Marriott®), and restaurants.

To bridge the gap between our frontend team and backend resources, such as our MongoDB databases and AI chatbot program, I architected RESTful APIs using Flask and Python. This architecture enabled the team to generate and retrieve responses effectively. In addition, I automated the CI/CD (DevOps) pipeline through GitLab and Docker, and deployed our frontend applications on Google Firebase Hosting and backend applications on Google App Engine. This not only streamlined the development process but also ensured seamless deployment of our applications. I was able to improve the accuracy of the bot's responses up to 91% through rigorous testing and validation.

As a final touch, I assembled an interactive map website to serve chatbot options and venue information to users, providing them with a comprehensive and interactive tool to enhance their travel experience.

Our efforts were met with great satisfaction from our client and coaches. We even outperformed the team in Boston, as well as all the other teams in the Atlanta office. This experience was a testament to the power of my leadership, teamwork, rapid learning, and innovative thinking and their potential to create impactful solutions.

I served as a Connected Autonomous Vehicles (CAVs) Software Engineer for the Georgia Tech EcoCAR EV Challenge at the Georgia Institute of Technology. As part of the Vehicle-to-Everything (V2X) subteam, I utilized multiple data streams from cameras and sensors to develop a state machine. This machine was designed to enable the car to make intelligent decisions in various traffic light scenarios, with a focus on efficiency and user experience. For example, based on the distance to the traffic light, the state machine would determine whether the car should stop or continue driving, which in turn would improve the car's fuel efficiency and the user's experience.

The EcoCAR Mobility Challenge is a prestigious 4-year Collegiate Competition and a $1 million research program. It is sponsored by esteemed organizations such as Argonne National Labs, the U.S. Department of Energy, General Motors, MathWorks, Intel, and more.

I am proud to have contributed to the Georgia Institute of Technology team's victory in the 2022 EcoCAR Mobility Challenge, where we secured 1st place. This experience not only honed my technical skills but also reinforced my passion for software engineering and its potential to create impactful and innovate solutions in the field of autonomous vehicles.

My primary task was to develop a machine learning program using MATLAB, a language and environment that was completely new to me. The project involved training and fine-tuning a neural network using an architecture like AlexNet on a dataset of images where each image was associated with a person's name. The goal was to use live footage from a computer webcam to correctly identify people's faces. This task was essentially a classification problem, and it involved elements of facial recognition.

Despite the complexity of the task and my unfamiliarity with MATLAB, I was able to learn the basics of the language in just a week. I heavily relied on documentation to aid in the development of the program. My efforts paid off when my supervisor expressed great admiration for the work I had accomplished in such a short period of time and even offered me position at the company. However, as I was still in high school and wanted to prioritize my studies, I had to respectfully decline the offer. This experience was a testament to my ability to quickly adapt to new technologies and deliver impressive results.