Implementation and relevant scripts for HW QED Research Project.
Under Professor Leana Golubchik at the Quantatitive Evalualuation and Design Research Group at the University of Southern California
Developed a stochastic multi-agent continiuous network-based simulation of Covid-19 on a variety of different random graph generation models. Generated time-series infection datasets in order to train various machine learning algorithms (LSTM, MLP, auto-encoder, and CNNs) that could analyze real-world infection data for different countries and determine the best hyperparameters and graph model to represent the spread of Covid-19, which might inform future patterns of Coronavirus spread.