A) We have developed machine learning and deep learning models that can predict prevalence, and forecast outbreaks based on self-reported population-level aggregated symptoms data. Furthermore, we have also developed multi-agent reinforcement learning models for prescribing non-pharmaceutical interventions, given the current state of the disease, economic impact, and more (Glorioso et al., 2021; Patwa et al., 2021; Sukumaran et al., 2021). Our DeepABM system makes use of Graph Neural Networks (GNNs) to scale agent-based models to run simulations with 100,000s agents in less than a few seconds (Chopra et al., 2021). Our outbreak predictions and NPI prescription models were ranked among the top models globally in renowned competitions organized by Facebook and XPRIZE. Members of our team have also been at the forefront of creating privacy-preserved machine learning models. We have published these works as numerous research papers in top-tier AI/ML venues (NeurIPS, ICLR, CVPR, and more).