  Nuclear astrophysics is a multi-disciplinary field with a huge demand for
nuclear data. Among its various fields, stellar evolution and nucleosynthesis
are clearly the most closely related to nuclear physics. The need for nuclear
data for astrophysics applications challenges experimental techniques as well
as the robustness and predictive power of present nuclear models. Despite
impressive progress for the last years, major problems and puzzles remain. In
the present contribution, only a few nuclear astrophysics specific aspects are
discussed. These concern some experimental progress related to the measurement
of key reactions of relevance for the so-called s-and p-processes of
nucleosynthesis, the theoretical effort in predicting nuclear properties of
exotic neutron-rich nuclei of interest for the r-process nucleosynthesis, and
the recent introduction of machine learning techniques in nuclear astrophysics
applications.
