Signal Processing - May 2017 - 79

Some prototype apps will be provided,
and each group will decide to either add
innovative elements to the existing prototypes or create a completely new one. At
the end of the activity, each group will
give a brief presentation.

Concluding remarks
Engineering education is at a crossroads
with recent efforts to create inspiring
engineering experiences for K-12 students. There is a persistent need to attract
and retain students in engineering postsecondary study and careers, and educators and policy makers have responded
with widespread adoption of the NGSS
to incorporate engineering knowledge
and skills in science instruction. We aim
to advance engineering education by
creating and refining programs that
improve STEM teaching and learning
by building passion, preparation, and
confidence for engineering study among
secondary students.
Our programs involve several stakeholders-students, teachers, and counselors-in a multifaceted effort to address
weaknesses in precollege engineering
accessibility. More students will be
exposed to engineering as a means to
solve problems by applying scientific
knowledge, and their teachers and counselors will have the skills to communicate these processes and advise students
on academic trajectories that lead to engineering careers. We will continue leveraging the expertise of engineering and
science education faculty to designing
innovative experiences that ultimately
diversify the engineering talent pool.
Although our previous and current student offerings focus on electrical and
computer engineering with signal and
information processing, we plan to
expand to other engineering disciplines
to offer students a broader vision of engineering careers. In doing so, we hope to
contribute to the knowledge base in engineering education so effective outreach
strategies might be incorporated in classroom teaching and advisement.

Acknowledgments
We would like to thank the National
Science Foundation for its support
through awards EEC-1647405 and

CCF-1617986. We would also like to
thank Dr. Keith Sheppard, director of
the Institute for STEM education, for
his support of our initiatives.

Authors
Mónica F. Bugallo (monica.bugallo@
stonybrook.edu) is an associate professor of electrical and computer engineering and the faculty director of the
Women in Science and Engineering program at Stony Brook University, New
York. She received her B.S., M.S., and
Ph.D. degrees in computer science and
engineering from the University of A
Coruña, Spain. Her research interests are
in the field of statistical signal processing, with emphasis on the theory of
Monte Carlo methods and its application
to different disciplines including biomedicine, sensor networks, and finance. She is
also committed to STEM education and
has initiated several successful programs
with the purpose of engaging students at
all academic stages in the excitement
of engineering and research, with a
particular focus on underrepresented
groups. She has authored and coauthored two book chapters and more
than 150 journal papers and refereed
conference articles.
Angela M. Kelly (angela.kelly@
stonybrook.edu) is an associate professor
of physics and astronomy and the associate director of the Science Education
Program at Stony Brook University,
New York. She attended La Salle
University, Philadelphia, Pennsylvania,
where she received her B.A. degree in
chemistry, and completed her M.A. and
Ph.D. degrees in science education
(2000 and 2006, respectively) and her
Ed.M. degree in curriculum and teaching (2007) at Teachers College,
Columbia University. She is the recipient of the SUNY Chancellor's Award for
Excellence in Teaching (2016); the
Provost's Faculty Recognition Award for
Excellence in Scholarship and Research
from Lehman College, City Uni versity of New York (2010); and the Outstanding Teaching Award from Teachers
College, Columbia University (2006).
Her research has been rooted in a commitment to equity in precollege science
and engineering.
IEEE Signal Processing Magazine

May 2017

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Table of Contents for the Digital Edition of Signal Processing - May 2017