My students and I devise new algorithms to improve the imaging of active and passive seismic data. Images obtained from seismic data are the main source of information on the structural and stratigraphic complexities in Earth's subsurface and on many subsurface dynamic processes. These images are constructed by processing seismic wavefields recorded at the Earth surface and generated by either active-source experiments, or by natural (ocean waves) and anthropogenic (vehicle traffic) sources. Because our datasets are huge, and wavefield propagation needs to be accurately modeled to achieve high-resolution imaging, we need to harness the power of latest computational hardware to test our methods on field data. Therefore, the mapping of imaging algorithms into high-performance architecture is an essential component of our research. Fiber-optic seismic recording holds the promise of enabling cost-effective continuous seismic monitoring at large scale (e.g. cities, unconventional basins). To achieve first-hand experience with this new technology my research group has been continuously recording data under Stanford campus for more than two years using a 2.5 km long fiber-optic cable and started devising innovative algorithms to process and image these new, but challenging, seismic datasets