Ml Researcher - Computational Neurobiology
Swarthmore, Pennsylvania, United States
• Lead the computational analysis of a significant Neuro‑toxicology study using Machine learning and Computer vision techniques. Our study employs various supervised, unsupervised, and semi‑supervised models to analyze and classify the neurological behaviour of flatworms afterexposure to certain toxic chemicals.• Developed Python scripts independently from scratch to extract useful features from video data ‑ these extracted features are used to trainclassification models that help us map specific chemicals to specific worm behavior.• Employed Computer vision and statistical techniques to crop videos, isolate foreground objects(the worm), and extract informative featuresfrom a large dataset of noisy videos with varying lighting conditions and quality.• Utilize a diverse range of models such as LSTMs, CNNs (for classification tasks), Random Forests, XGBoost, T‑SNE, PCA, UMAP, and other unsupervised and semi‑supervised learning methods for in‑depth image analysis.• Applied computer vision techniques extensively