Hello, my name is Jose Solano!

About Me:

Hi, I’m Jose Solano — a Computer Science graduate from Florida State University based in Tampa, Florida. As a first-generation college student, earning my degree has been one of my proudest accomplishments. It shaped not only my technical foundation, but also my work ethic, resilience, and drive to continuously grow. During my time at FSU, I developed a strong academic and hands-on foundation in Artificial Intelligence, Machine Learning, Natural Language Processing, and Database Systems. I’ve built and trained machine learning models, developed domain-specific NLP systems, designed relational databases, and created full-stack applications that solve real-world problems. My projects range from training convolutional neural networks for image classification to building Named Entity Recognition models that transform unstructured text into structured, analyzable data. Beyond coursework, I actively invest in my professional growth. I attend networking events, connect with industry professionals, and continuously refine my technical skills through independent projects and hands-on experimentation. I am passionate about turning data into meaningful insights and building intelligent systems that create real impact. Currently, I am pursuing a career in Data Engineering, Machine Learning, and AI development. I am eager, highly motivated, and excited to contribute to a team where I can learn from experienced engineers while delivering value from day one. Technology to me isn’t just code — it’s a tool to solve problems, empower people, and create smarter systems for the future.

Contact Information

• Email: jlsolano06@gmail.com
• Show Resume

Projects: (click a project name for details)

• Retail Clothing Stock Manager

  ×

  Retail Clothing Stock Manager

  Worked on both the backend and frontend for a semester long group project which consisted in creating a stock management application that tracks retail items, sends alerts when items are low on stock, updates items, tracks who made changes to the data stored, and provides analytics like most items sold, revenue and user interactions.

  Link to documentation

• Named Entity Recognition Model

  ×

  Named Entity Recognition Model

  Group project consisting on training a named entity recognition model to recognize entities in text such as people, locations, dates, events, geographical locations, products and currencies. Trained a blank spacy model to function specifically with texts related to travel and tourism. My contributions were developing and training the initial blank NER model. Read through the Spacy documentation to start the development of the project. Also developed a simpler version of the final project as a website.

  Link to web version

• Power Automate Weather Bot Virtual Agent

  ×

  Power Automate Weather Bot Virtual Agent

  Using Microsoft Power Automate tools I created a weather bot with the capabilities of looking up a city and state by providing a zip code. Give you the weather forecast at an specific address and provide random weather facts when asked. The virtual agent was trained with prompts to ensure its user friendly and fun for all ages. The virtual agent uses cloud flows to be able to retrieve information when prompted.

  Link to video demonstration

• Accessibility Finder

  ×

  Accessibility Finder

  Developed a web application that helps users identify accessibility features in public spaces. The project involved creating a user-friendly interface for reporting and locating accessibility amenities such as ramps, elevators, and accessible restrooms. Implemented a database to store location data and integrated mapping features to visualize accessibility points.

  Link to Website

• Machine Learning Cat vs Dog

  ×

  Machine Learning Cat vs Dog

  Created a machine learning model to classify images of cats and dogs using Python and TensorFlow. The project involved training a convolutional neural network (CNN) on a dataset of labeled images, achieving high accuracy in distinguishing between the two classes. Implemented data preprocessing techniques and used transfer learning to improve model performance.

  Link to documentation

• Sentiment Analysis Comparison

  ×

  Sentiment Analysis Comparison

  Developed two sentiment analysis applications to compare different machine learning approaches. The first uses spaCy to train a custom text classification model from scratch with positive and negative labels, while the second leverages Hugging Face Transformers with a pretrained sentiment analysis pipeline. Both implementations feature interactive Tkinter GUIs that allow users to analyze text sentiment in real-time and display confidence scores. This project demonstrates the trade-offs between training custom models versus using transfer learning with pretrained models.

• Audio Translation with Voice Cloning

  ×

  Audio Translation with Voice Cloning

  Built an end-to-end audio translation application that captures spoken input, translates it to target languages, and synthesizes it back with voice cloning. The application records the user's voice via microphone, transcribes it to text using Google Speech Recognition, translates the text to Spanish, French, or English using the GoogleTranslator API, and generates speech output with the user's own voice characteristics using Coqui XTTS-v2 voice cloning technology. The system creates a reference voice sample on first run and maintains acoustic style consistency throughout the translation pipeline.

Skills:

• Languages:

  • Python
  • Java
  • C++
  • SQL
  • JavaScript
  • HTML/CSS/PHP
  • R

• Frameworks:

  • Streamlit
  • Flask
  • Tkinter

• ML / Data:

  • TensorFlow
  • PyTorch
  • Keras
  • PySpark
  • SpaCy
  • pandas
  • NumPy
  • Matplotlib

• Developer Tools:

  • Git
  • GitHub
  • Unix/Linux
  • Power Automate
  • VS Code
  • Eclipse
  • Apache

• Concepts:

  • Data Structures and Algorithms
  • Object-Oriented Programming
  • Machine Learning
  • Natural Language Processing
  • Computer Vision
  • API Integration (REST)
  • Data Preprocessing
  • Model Evaluation