We are stepping to a new territory of applied mathematics.   We are
developing computational multilinear algebraic methods for
higher-order tensors, which are parallel to the matrix theory. We
are studying mathematical properties of tensors, such as eigenvalues
and characteristic polynomials of tensors, tensor decomposition and
tensor approximation, etc. The new subject has found applications
and links from data analysis, automatic control, magnetic resonance
imaging, optimization, solid mechanics, quantum physics, higher
order Markov chains, spectral hypergraph theory, Finsler geometry
and relativity theory, etc.   Recently, linear convergence has been
established for algorithms for finding the largest eigenvalue of a
nonnegative tensor. Further serious exploration on these aspects is
needed.    I hope that more researchers will join us to explore this
new field.