This NSF project aims to solve the problem of oscillations faced by power grids with high penetration of renewable energy that are disrupting system operations. The project will bring transformative change in fundamental understanding of such phenomena and propose new control strategies to damp the oscillations by leveraging the cyber layer of the power grid including sensors and communication network. This will be achieved by novel approaches of modeling the cyber physical power grid that can capture such phenomena, and centralized and decentralized controls that can damp such oscillations even in presence of anomalies in sensor measurements including cyber-attacks. The intellectual merits of the project include development of computationally manageable cyber physical models, novel sensor grouping and algorithms for data recovery from corruption, and control methods that do not rely on detailed renewable plant models. The broader impacts of the project include solving a major impediment of renewable energy integration that can help tackle climate change, integrating the proposed research in summer camps with high school students, offering summer internships for underrepresented minorities, informing curricula, and student engagement through Penn State?s Center for Engineering Outreach and Inclusion. The proposed project has three key thrusts addressing the sub- and super-synchronous oscillations (SSOs) in presence of inverter-based resources (IBRs). First, a scalable, computationally manageable, and linearizable dynamic phasor-based modeling framework with unbalance simulation capability for grids with high penetration of IBRs is proposed, which is coupled to a realistic cyber layer model with data packet drops and delays. Second, a centralized remedial action scheme based damping control is proposed that relies on three steps ? (a) offline phasor measurement unit (PMU) placement, online dynamic signal grouping, and signal recovery from sparse and non-sparse corruption, (b) detection and source localization of SSOs using dissipating energy flow (DEF) approach, and (c) determination of generation re-dispatch through a novel DEF sensitivity calculation. Third, decentralized modulation-based corruption-resilient SSO damping is proposed based on model predictive control (MPC) framework that does not require knowledge of IBR models, wherein the computational burden will be reduced by estimating a map by offline training of neural networks.