  In this article the author reviews Jos\'e Bioucas-Dias' key contributions to
hyperspectral unmixing (HU), in memory of him as an influential scholar and for
his many beautiful ideas introduced to the hyperspectral community. Our story
will start with vertex component analysis (VCA) -- one of the most celebrated
HU algorithms, with more than 2,000 Google Scholar citations. VCA was
pioneering, invented at a time when HU research just began to emerge, and it
shows sharp insights on a then less-understood subject. Then we will turn to
SISAL, another widely-used algorithm. SISAL is not only a highly successful
algorithm, it is also a demonstration of its inventor's ingenuity on applied
optimization and on smart formulation for practical noisy cases. Our tour will
end with dependent component analysis (DECA), perhaps a less well-known
contribution. DECA adopts a statistical inference framework, and the author's
latest research indicates that such framework has great potential for further
development, e.g., there are hidden connections between SISAL and DECA. The
development of DECA shows foresight years ahead, in that regard.
