Personal Portfolio

Web Development
Description:
A responsive portfolio website using HTML, CSS, and JavaScript, showcasing my skills, projects, and experiences as a developer. Implemented a visually appealing design with interactive elements and ensured compatibility across different devices.
Technologies used:
  1. Bulma framework
  2. HTML, CSS, Javascript, & jQuery
  3. GitHub Pages

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Our Help

SWE Web Development
Description:
A web application using Java, JavaScript, HTML, CSS, and Bootstrap, incorporating Google Cloud Platform APIs (App Engine, Datastore, and Maps) for enhanced functionality and user experience to enable seamless access to local resources and services.
Technologies used:
  1. Google Cloud Platform
  2. Java, HTML, CSS, Javascript, Bootstrap framework
  3. App Engine, Datastore, & Maps APIs

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CPP Hub

SWE Web Development
Description:
A simple and easy-to-navigate Chrome extension that caters to students who attend Cal Poly Pomona. CPP Hub grants students quick access to relevant links to campus resources.
Technologies used:
  1. Chrome Developer Dashboard
  2. HTML, CSS, Javascript, & Bulma framework
  3. jQuery, JSON, & Font Awesome

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CALSys Lab

Data Science SWE
Description:
Cyber Adaptive Learning System Laboratory is a research lab at Cal Poly Pomona that focuses on advancing cyber-defense strategies through machine learning and social network analysis. I help develop cyber-threat intelligence systems and gather data from hacker communities to proactively identify emerging cyber threats.
Technologies used:
  1. Tor Browser on Tails OS
  2. Python and libraries
  3. Web Crawler and Parser

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Rock Paper Scissors

SWE
Description:
In this rock-paper-scissors game, implementated using the Qiskit library, you have the opportunity to make your choice, while the program generates the computer's choice randomly. Once the winner is determined, the outcome and the choices made are displayed.
Technologies used:
  1. IBM Quantum Computing
  2. Python & Qiskit Library
  3. Superposition

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Spam Email Classifier

Machine Learning
Description:
This project implements a machine learning model to classify emails as spam or non-spam. It utilizes the Naive Bayes algorithm for text classification and demonstrates the process of training the model, evaluating its performance, and making predictions.
Technologies used:
  1. Multinomial Naive Bayes
  2. Python & scikit-learn
  3. pandas, matplotlib, seaborn

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Data Analyzer

Data Science
Description:
This project is a data preprocessing and analysis tool that provides features to drop missing values, remove outliers, clean string data, perform optional operations, calculate basic statistics, and generate visualizations (scatter, histogram, boxplot).
Technologies used:
  1. Data Preprocessing, Statistics, & Visualizations
  2. Python, pandas, matplotlib, & seaborn
  3. Modularity & Error Handling

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Stock Price Predictor

Machine Learning
Description:
This project uses historical stock price data to create a predictive model based on LSTM neural networks, which aims to forecast future stock prices for a predefined list of stocks.
Technologies used:
  1. keras (with TensorFlow backend)
  2. Python, pandas, numpy, & scikit-learn
  3. yfinance for stock information

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Search Engine

Machine Learning SWE
Description:
Developed a web scraping search engine for Cal Poly Pomona's Civil Engineering professors. Utilized Beautiful Soup for scraping, stored data in MongoDB, and applied natural language processing with TF-IDF and cosine similarity using sklearn and nltk. The user-friendly interface was built with Django, HTML, CSS, and Bulma UI for seamless searching and exploration.
Technologies used:
  1. Python, HTML, CSS, Bulma UI
  2. Scikit-learn, NLTK, Pymongo
  3. MongoDB

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Huddle

SWE Web Development
Description:
Huddle is a collaborative task management web application that allows users to create huddle groups, add members, and manage tasks within these groups. Users can seamlessly coordinate and track progress on shared tasks, fostering efficient teamwork.
Technologies used:
  1. Python, HTML, CSS, JavaScript, Bulma UI
  2. Django, PostgreSQL
  3. Amazon Web Services (AWS)

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ChatGPT Bias Research

Data Science
Description:
This research project aims to uncover and address potential gender bias that may exist within Large Language Models, such as ChatGPT. Identifying these potential biases helps address ethical concerns in AI. This project involves generating prompts, utilizing ChatGPT's API, storing responses, and evaluating the bias in responses.
Technologies used:
  1. ChatGPT API
  2. Python, csv, pandas, & matplotlib
  3. Creating & managing datasets