Experience

Developing an automated tool for detecting and extracting text and tables from documents. Text is extracted using NLP, and tables are detected using YOLO and are then converted into CSV files with Google AI Studio. Gained expertise in integrating machine learning models, cloud services, and scripting workflows in Python.

Currently collaborating on researching alternative methods to improve pattern identification capabilities for Self-Supervised Learning models, aiming to reveal valuable transformable knowledge between datasets.

Explored the machine learning lifecycle, data preparation, and models such as KNN, logistic regression, ensemble methods, and more. Led student team in conducting a case study on implementing a neural network for sentiment analysis in chatbots. Provided recommendations for streamlining intent classification, improving accuracy, and enhancing the user experience. Engaged in a Kaggle competition with the New York Botanical Garden, training a model for precise classification of plant and animal specimen leveraging pre-trained models and computer vision techniques.

Explored diverse Tableau visualizations, skillfully applying them to create comprehensive dashboards. Led the development of dynamic data stories emphasizing student information, contributing to the school system’s equity initiative, offering actionable insights to enhance student success.