◦ Achieved a 20% reduction in downtime by deploying a company-wide telecommunications infrastructure upgrade,
ensuring seamless communication across over 5000+ devices while optimizing network performance.
◦ Implemented a database management system in Python for Android device identification codes and streamlined
application installations using Samsung Knox, improving scalability across 35+ regional offices.
◦ Analyzed and maintained telecommunications data systems to ensure compliance with industry standards and
internal policies, ensuring secure and efficient operations.
◦ Collaborated with IT teams to develop and implement scalable communication solutions that supported the company’s logistics and transport operations, enabling efficient handling of 10,000+ daily logistics requests.

- Developed a full-stack fintech education platform with 15 interactive modules using React.js and Flask, helping Gen Z investors understand ETF portfolios and risk analysis.
- Won a $400 award as 1 of 2 Sun Life case winners out of 300+ participants for creating an intuitive and educational investment tool.
- Integrated stock data dynamically and built 2 interactive candlestick and histogram charts using yfinance and Plotly to simulate portfolio returns and allow users to explore the performance and risk of 100,000+ stocks.

- Built an AI-Powered Webscraper that dynamically pulls data from a website, using a Meta's AI (Llama ver. 3.2).
- Created an NLP-powered solution that dynamically extracted relevant content from website URLs based on user prompts, achieving accurate data retrieval across 100+ test cases, enhancing web-scraping efficiency.
- Designed front-end in React.js Framework and the Selenium Python Package and connected using a Flask server.

- Developed a custom predictive analytics tool to forecast stock price movements based on historical financial data over the past 10 years
- Programmed a Random Forest Classifier in Python using Scikit-Learn, trained on 10,000+ data points of stock prices and trading volumes, combined with technical indicators to achieve a 15% improvement in predictive accuracy for market trends.
- Data is taken from Yahoo Finance using the yfinance library in Python and recommends a stock that has a greater than 55% chance of rising in value.

- Engineered the front-end and AI model using React, Python, HTML, and CSS for an Alzheimer’s detection tool aimed at physicians, which won a $1,000 prize at YIC (Youth Impact Challenge).
- Aided in developing a convolutional neural network (CNN) to classify 2000+ images and qualitative clinical data to determine the likelihood of a patient having Alzheimer's Disease with 85.3% accuracy.
- Collaborated in a team of 3 to integrate machine learning models (Random Forest, Meta Classifier) for analyzing MRI scans providing invaluable support in early diagnosis and patient care management.