Java Backend Developer and Machine Learning Enthusiast, with knowledge in Java, Python, React, and Node.js. Welcome to my Portfolio!
I’m passionate about creating reliable systems, solving tough problems, and making sure everything runs smoothly behind the scenes. I also love to leetcode!
Hi! I am a backend developer that loves to solve complex problems and challenges! I have worked with lots of companies in the past such as Boeing and Google! My main language is Java, but I love to try out new and different languages!
I possess 2+ years of experience in program and product management. This came from my courseworks, unpaid internships, and certifications from google! My expertise includes coordinating cross-functional teams, optimizing project resources, and ensuring the successful delivery of complex projects on time and within budget.
I am a UI/web developer with expertise in React, Node.js, and Electron. I love creating designs and making things work on Figma and Canva. I also own a streetwear brand that helps my designing skills everyday.
Crea8folio was my final Capstone project in University and one of my most difficult projects so far. Crea8folio is a no-code portfolio builder designed to make creating professional portfolios accessible to everyone—especially business students who often lack tools tailored to their needs. The platform bridges the gap between functionality and ease of use, enabling users to showcase their projects, skills, and achievements in a sleek, interactive format without writing a single line of code. Built with React and powered by Electron for a cross-platform desktop experience, Crea8folio incorporates cutting-edge technologies like Grape.js to deliver an intuitive drag-and-drop interface. Users can customize pre-designed templates, add dynamic sections like project showcases or testimonials, and even export their portfolios as zip files for easy sharing and deployment. The app also features advanced options like full-screen previews, spectate mode, and a built-in editor to view and tweak the underlying HTML/CSS if desired. The inspiration for Crea8folio came from observing how many resources exist for tech and creative students, while business students often rely on static resumes or LinkedIn profiles. This project is about leveling the playing field and giving everyone, regardless of their technical background, the power to control their professional narrative in a visually compelling way.
A cutting-edge weather application built with HTML, CSS, and JavaScript that empowers you to access real-time weather information for any city across the globe. This sleek and user-friendly weather app goes beyond just providing forecasts; it offers an immersive and interactive experience to keep you informed and prepared for any weather conditions. Key Features: Global Coverage: This weather app offers worldwide coverage, allowing you to check the current weather in any city, town, or village across the planet. User-Friendly Interface: With a clean and intuitive design, this app ensures that accessing weather information is a breeze. Simply enter the city name, and the app will do the rest. Real-Time Updates: Stay up to date with the latest weather conditions as the app provides real-time updates, including temperature, humidity, wind speed, and more. Cross-Platform Compatibility: Access the app on various devices and browsers, ensuring you can check the weather no matter where you are.
a minimalist, aesthetically pleasing clock created with HTML, CSS, and JavaScript. This elegant clock combines simplicity and style to offer you a delightful and functional time-telling experience. Key Features: Clean and Elegant Design: Our clock features a beautifully crafted interface with a focus on simplicity. The sleek design ensures that it complements any setting, whether it's on your desktop or as part of a web page. Accurate Timekeeping: The clock provides precise, real-time updates to keep you in sync with the current time, ensuring you never miss a beat. Lightweight and Fast: The clock is designed for efficiency, ensuring it doesn't slow down your website or consume excessive system resources.
A mockup clothing website created by experimenting with layout using the power of Bootstrap, HTML, and CSS. Please note that this website is for practice and layout experimentation only, and no actual orders can be placed. Key Features: Bootstrap-Powered Responsiveness: Our website is built on Bootstrap, ensuring a fully responsive experience. Whether you're on a desktop, tablet, or smartphone, the website adapts seamlessly to your screen size. Fashion Gallery: Explore the Fashion Gallery, where you can find stunning images of models/cars showcasing style and culture. This gallery was built on bootstrap.
This program utilizes JavaScript libraries and machine learning to create a web-based face identification and emotion recognition tool. It sets up a webpage with a video element for live webcam feed. The JavaScript code likely handles initializing the webcam, detecting faces, and analyzing emotions using machine learning models. CSS styling ensures a visually appealing layout, possibly with overlays to highlight detected faces. Overall, it offers an interactive platform for real-time face analysis, with potential applications ranging from entertainment to practical use cases like mood tracking or user engagement analysis.
The project involved creating an image dataset by capturing screenshots from a specific window using Python libraries like numpy, win32gui, and PIL, then labeling the dataset using Make Sense AI for manual annotations. After organizing and labeling the images, the dataset was used to train a YOLOv4-tiny object detection model on Google Colab, leveraging pre-trained weights and a custom configuration. Post-training, the model was tested in real-time on a live window of the "Rocket League" game, detecting objects like the ball and boost. While the model showed reasonable accuracy, particularly with static or slow-moving objects, it struggled with fast-moving scenes and varied lighting conditions. The project demonstrated the practical implementation of object detection, including dataset preparation, model training, and real-time application, highlighting challenges in dynamic environments and emphasizing the iterative nature of machine learning development.
This program predicts whether a patient has diabetes using an SVM classifier based on medical attributes such as pregnancies, glucose levels, and BMI. It involves loading and analyzing a CSV dataset, standardizing the data, splitting it into training and test sets, and training the model. The model's accuracy is evaluated, and a predictive system is demonstrated by inputting patient data to predict diabetes status.
This project is all about visualizing the comparison between actual and predicted prices using a scatter plot to evaluate the performance of my predictive model. I created a scatter plot that includes actual prices on the x-axis and predicted prices on the y-axis, with each point representing a data instance from the training set. By examining this scatter plot, I can assess the model's accuracy by observing how closely the points align with the ideal line 𝑦 = 𝑥. Deviations from this line highlight discrepancies in predictions, providing insights into areas where the model may need improvement. This visualization helps me identify systematic errors and guides further refinements in the model, ensuring continuous improvement in prediction accuracy. To make this process easier, I've included a detailed code example using Python and Matplotlib to create the scatter plot. This example demonstrates how to implement the visualization and understand the model's performance effectively. By using this scatter plot, I aim to provide a clear and intuitive understanding of how well the predictive model works and where it can be improved.
The Java GUI Personality Quiz Game is an interactive application designed to engage users in exploring various personality types through a fun and educational quiz format. Developed using Java's Swing framework, the program presents users with a series of questions, each accompanied by multiple-choice answers. Based on their responses, the application calculates and reveals the user's personality type from six predefined categories. Each personality type comes with a descriptive text highlighting its unique traits, an associated image for visual representation, and background music that enhances the experience. Users can enjoy discovering different personality types in a visually appealing and intuitive interface, making it both entertaining and insightful. I honestly had a lot of fun making this application!
This machine learning program employs the XGBoost algorithm to predict calorie expenditure during exercise using a dataset that includes physiological and exercise-related metrics such as age, gender, height, weight, exercise duration, heart rate, and body temperature. By leveraging these features, the model learns patterns that relate these variables to the calories burned, offering insights into how different factors influence energy expenditure during physical activities. This predictive capability can be instrumental in tailoring personalized fitness plans, optimizing workout routines, and supporting health professionals in advising on exercise intensity and duration for effective calorie management and fitness goals.
Feel free to reach out and send me a message anytime.
