Computer Vision · Machine Learning Research · Cognitive AI
🔬 Research Data Scientist @ Cognitive Development Lab, Indiana University Bloomington
🎓 MS Data Science, Indiana University Bloomington (2025)
I build computer vision pipelines to study how infants perceive and learn from their visual environment — analyzing 500,000+ egocentric head-camera images and videos collected from infants aged 4–30 months.
My work sits at the intersection of deep learning, quantitative image analysis, and developmental psychology. I translate SOTA CV/ML research into reproducible scientific tools that support academic publications and conference presentations.
Infant Egocentric Vision Analysis · IU Cognitive Development Lab, 2024–Present
End-to-end CV pipeline measuring visual complexity in infant environments using feature-congestion models, semantic segmentation, and multimodal video analysis. Dataset: 500K+ head-camera frames across 30 infants.
EvacSim — Multi-Agent Evacuation Simulation · GitHub · Demo
🥈 2nd Place, Luddy Hackathon 2025. Real-time evacuation tool with 9 autonomous agents (8 drones + 1 ground vehicle) built in Unity with AI NavMesh pathfinding, integrated with a React frontend via WebSocket.
Algae Classification — City of Bloomington Partnership · Report · Poster
Applied ResNet and U-Net to classify 12 algae species from microscopy images for Lake Monroe water quality monitoring. 1,287 images preprocessed and augmented to address class imbalance.
Heart Disease Risk Assessment · GitHub
ML classification models (Logistic Regression, Random Forest, XGBoost) across full, female-only, and male-only cohorts. EDA, feature engineering, and model evaluation in Python + scikit-learn.
Languages
ML / Deep Learning
Data & Visualization
Databases & Tools
Always open to discussing research, collaboration, or interesting problems.