Hi,
I'm Deni Bravo

I code things. Sometimes, they work.

About Me

Deni Bravo

Graduated from Moravian University majoring in Computer Science. I'm passionate about technology, learning new skills, and building projects that make a difference.

Over the years, I’ve developed a strong foundation in various programming languages and tools, and I’m always excited to tackle new challenges. Here are some of the technologies I’ve worked with:

  • Python
  • Machine Learning
  • AI
  • Computer Vision
  • Data Analysis
  • SQL
  • AWS
  • HTML & CSS
  • JavaScript
  • Pandas
  • Sci-Kit Learn
  • Numpy


Aside from Computer Science, I love sports such as boxing and soccer! As well as a love for content creation!

Experience

Software Developer @ MIAC Analytics

March 2023 - December 2023

  • As part of my role at MIAC Analytics, I worked on a machine learning project centered around improving data matching accuracy through advanced record linkage techniques. We spent significant time researching various methodologies to understand the best approaches for linking records across disparate data sources, focusing on accuracy and scalability. This research-driven approach allowed us to design and implement a data cleaning and record linkage system that improved the efficiency of the company's software, ultimately enhancing the quality of data analysis and reporting.
  • Transitioned to frontend development after completion of machine learning project as an internship extension.

Web Developer @ BKWeb Productions

October 2022 - May 2023

  • Built a complete company website from scratch, using modern web technologies such as HTML, CSS, and JavaScript.
  • Designed the overall website layout and user experience to meet the company’s branding and usability needs.
  • Managed all aspects of web development with a team that consisted of three people, me included, from design concepts to implementation and deployment.

Repair Clinic Staff @ Northampton Community College

October 2022 - May 2023

  • Diagnosed hardware and software issues for client PCs and provided effective solutions to restore functionality.
  • Repaired and upgraded computer components, including CPUs, RAM, and storage devices, ensuring optimal performance.
  • Assisted customers by explaining technical issues in accessible language and providing recommendations for future maintenance.

Key Skills

  • Machine Learning & Data Analysis
  • Frontend & Backend Development
  • Record Linkage & Data Cleaning
  • Client Collaboration & Project Management

Awards

  • Internship Excellence Award
  • Charles H. Davison Memorial Scholarship Endowment in Electronics & Information Systems

Projects


Flight Delay/Cancellation Multi-Classification


Developed a machine learning model to predict flight delays and cancellations up to 7 days in advance using domestic U.S. flight data from 2023 onward. The model classifies flights into on-time, delayed, or canceled, helping stakeholders proactively manage operational disruptions.

Python Pandas Scikit-learn Neural Networks Seaborn


Mirrulations


Contributed to the development of a cloud-based system that ingests, processes, and exposes U.S. federal regulatory data (from Regulations.gov) to support transparency and journalistic analysis. The goal was to enable data journalists and researchers to efficiently search, filter, and analyze public comments and regulatory dockets related to topics such as marijuana, psychedelics, and other emerging policy areas.

Python SQL Amazon Aurora Excel OpenSearch S3 Secrets Manager Docker Agile


Lung & Colon Cancer Histopathological Image Classification


Developed a CNN using TensorFlow to classify over 25,000 histopathological images from the LC25000 dataset into five cancer types. Applied image augmentation and tuning techniques to improve accuracy and generalization.

Python Pandas Scikit-learn Neural Networks Seaborn TensorFlow Keras Matplotlib


Credit Card Fraud Detection


Developed a machine learning solution to identify potentially fraudulent credit card transactions. Given the significant class imbalance in the dataset, the project emphasized techniques to improve fraud detection accuracy while minimizing false positives. The workflow included data cleaning, exploratory analysis, feature scaling, model training, and performance evaluation using metrics suited for imbalanced data.

Python Pandas Scikit-learn Matplotlib Seaborn


AI Hedge Fund Strategy Simulation (In Progress)


Designing an AI-powered system to simulate hedge fund trading strategies using open-source financial data and large language models. The project explores automated investment decisions, sentiment analysis, and market trend forecasting. Focus is on building a cost-efficient, local-first prototype to test real-world financial insights.

Python Pandas Numpy OpenAI API Docker AI Semantic Kernel AI Agents LLM Financial Data


Early Spring Prediction


A data science project aimed at predicting early spring for farmers in Western Pennsylvania. Used soil temperature and weather data to make predictions to assist in purchasing seeds that can grow two crops in a year.

Python Pandas Scikit-learn Random Forest Gradient Boosting


Reading Tracker App


An AWS-powered web application that allows users to log books and track reading progress. Integrated with the Google Books API, the app allows users to search for book details and create a personal library for tracking purposes.

S3 EC2 DynamoDB Flask Python API Gateway Google Books API


Recipes Application


A web application that helps you look for recipes based on your interests using keywords.

Flask mySQL AWS Python HTML & CSS Javascript


Portfolio Website


A website that showcases all my experience and skills gained through my lifetime. Getting to know about me and my achievements.

HTML & CSS Javascript


Squirrel Disease Predictions


A data science project that predicts whether or not a squirrel is sick using the Central Park, NY squirrel census from October 2018.

Python Pandas Random Forests Pandas Scikit-learn Matplotlib Seaborn