  This paper develops an interpolatory framework for weighted-$\mathcal{H}_2$
model reduction of MIMO dynamical systems. A new representation of the
weighted-$\mathcal{H}_2$ inner products in MIMO settings is introduced and used
to derive associated first-order necessary conditions satisfied by optimal
weighted-$\mathcal{H}_2$ reduced-order models. Equivalence of these new
interpolatory conditions with earlier Riccati-based conditions given by Halevi
is also shown. An examination of realizations for equivalent
weighted-$\mathcal{H}_2$ systems leads then to an algorithm that remains
tractable for large state-space dimension. Several numerical examples
illustrate the effectiveness of this approach and its competitiveness with
Frequency Weighted Balanced Truncation and an earlier interpolatory approach,
the Weighted Iterative Rational Krylov Algorithm.
