  Nuclear reaction data required for astrophysics and applications is
incomplete, as not all nuclear reactions can be measured or reliably predicted.
Neutron-induced reactions involving unstable targets are particularly
challenging, but often critical for simulations. In response to this need,
indirect approaches, such as the surrogate reaction method, have been
developed. Nuclear theory is key to extract reliable cross sections from such
indirect measurements. We describe ongoing efforts to expand the theoretical
capabilities that enable surrogate reaction measurements. We focus on
microscopic predictions for charged-particle inelastic scattering,
uncertainty-quantified optical nucleon-nucleus models, and neural-network
enhanced parameter inference.
