Senior Projects - AI Research & Development
Welcome to my senior project research on text embedded AI models. These represent my exploration into teaching machines to understand not just what people say, but how they say it and what it means.
Featured Articles
Emotionally Adaptive Chatbots
Building Empathy with AI Through VAD Emotion Detection
This project uses AI to detect and respond to human emotions in text. Using Valence-Arousal-Dominance (VAD) scoring, I achieved variance scores above 0.70 with over 300,000 labeled entries, enabling chatbots to interpret emotional context alongside meaning.
Key Achievements: - Variance scores > 0.70 across all VAD dimensions - Over 300,000 emotion-labeled text entries - Real-time emotional tone adaptation - Customer service empathy modeling
Technologies: Python, NLP, Sentence Transformers, spaCy, VAD Modeling
AI-Powered Resume Scoring System
From Reading Emotions to Reading Resumes
Leveraging the breakthroughs from the VAD emotion project, this system uses semantic similarity and pretrained text embeddings to match resumes to job descriptions, not by counting keywords, but by understanding meaning.
Key Features: - Semantic matching (not just keyword scanning) - Intelligent keyword extraction with NLP - Weighted scoring (65% meaning + 35% keywords) - Real-time resume analysis
Technologies: Python, Sentence Transformers, spaCy, Flask, NLP
VAD Final Presentation
Complete Results & Live Demo
This project builds a machine learning model that predicts emotional meaning in text using the Valence–Arousal–Dominance (VAD) framework. A dataset of more than 300,000 labeled text samples was created using EmoBank, synthetic data generation, and game server logs. The text was transformed into embeddings with a SentenceTransformer model, and a multi-output Ridge Regression model was trained to estimate the three VAD dimensions. The final model achieved strong performance in predicting emotional tone and demonstrates an efficient, interpretable approach for emotion analysis in real-time text applications.
Technologies: Python, NLP, Sentence Transformers, spaCy, VAD Modeling