Content Gazette - March 2020 - 12

Call for Papers
IEEE Signal Processing Magazine
Special Issue: Innovation Starts with Education
Signal processing (SP) is at the very heart of our digital lives, owing to its role as the pivotal development technology
across multiple disciplines. Its prominence in modern data science has created a necessity to supply industry,
government labs, and academia with graduates who possess relevant crucial signal processing expertise and are
well equipped to deal with the manifold challenges in current and future applications. To this end, both the ways to
deliver the educational content and the core Signal Processing curriculum need to be revisited and integrated into
Engineering and Computer Science degrees, to provide hands-on skills, experience, and inspiration for students.
Signal processing education in today's universities is largely influenced by three modern trends: 1) the availability of
competing and complementary online and multimedia resources; 2) the fact that we live in a world in which the
amount and diversity of information we generate, process and analyse is growing ever faster; 3) the explosive growth
of computing power, and the rapid development of new technologies for implementing both analog and digital signal
processing. These trends offer both opportunities and challenges, which we can, and must, exploit in charting
dynamically adjustable courses that attract a high level of student engagement while offering a mix of essential
background physics, intuition, mathematical rigor, and practical applicability of the taught material.
With such initiatives underway at many universities world-wide, this special issue aims to facilitate both keeping
abreast with SP education and exploring innovative and participatory ways to present the educational materials. In
effect, we cannot assume that students will be able to appreciate the scope and relevance of their courses without
explicitly building a bridge between the material presented in class and cutting-edge research, societal, and practical
impact of their education. This includes the convergence of educational material with other disciplines (machine
learning, data science, big data, bioengineering, artificial intelligence, finance and many others).
This special issue will revolve around three general and most pressing aspects of modern SP education:
o How to educate differently (better). This includes the use of available technology, bringing research into the
classroom, web resources, experiential learning, and massive open online courses (MOOC).
o Student engagement, such as ways to enhance student creativity and curiosity, student satisfaction issues,
various forms of assessment and metrics, engagement of under-represented population, and outreach drives.
o Promotion of the societal impact of SP, including privacy, ethical and security concerns, wearable devices
and eHealth, global interconnections through IoT, and impact on climate change, global economy and finance.
Topics of interest include but are not limited to:
* Mitigation of issues related to the perceived difficulty of traditional SP courses, such as strategies on how to
teach SP with less maths and how to attract attendees from non-engineering departments.
* The use of emerging technologies and technologically orientated classroom, such as MOOC and web resources.
* Metrics for success of education delivery in the After Online Technology (AOT) era.
* Using the principles of signal processing to improve teaching and research in related areas, such as machine
learning, bioengineering, artificial intelligence and optimization, and vice versa.
* Curricular changes to meet contemporary demands from industry, such as using practically relevant problems,
exploring feasible extensions and new applications of the taught material, and curiosity driven learning.
* Preparing students for life-long learning, teaching life-long fundamentals of SP, and relevance of SP with respect
to technological advance.
* Challenges and solutions in industry-run courses; design of short courses offered by academia for industry,
Government Agencies and National Defence.
* Role of mentorship and initiatives to encourage and motivate students in research experiences.
* Promoting creativity in learning, especially when applying the concepts with "opportunity windows" to explore
entrepreneurship and possible product developments, and cross-disciplinary aspects of our work.
Submission Process. Original submissions will be reviewed according to the guidelines as set out in the IEEE
Signal Processing Magazine, and should be submitted online at
http://mc.manuscriptcentral.com/sps-ieee.
Prospective authors should initially submit short White Papers, as indicated below, which will be reviewed by Guest
Editors. Authors of successful White Papers will be invited to submit full-length manuscripts, which will undergo the
usual reviewing process in accordance with the schedule outlined below.
White Papers (up to 4 pages) due: March 1, 2020
Full length manuscripts due: June 1, 2020
Revised manuscripts due: September 15, 2020
Final manuscripts due: December 1, 2020

Decision on White Papers: April 1, 2020
Review results and decision: August 1, 2020
Acceptance notification: November 1, 2020
Publication date: March 1, 2021

Guest Editors
* Mónica Bugallo, SUNY at Stony Brook, USA, monica.bugallo@stonybrook.edu
* Anthony Constantinides, Imperial College London, a.constantinides@imperial.ac.uk
* Danilo Mandic, Imperial College London, UK, d.mandic@imperial.ac.uk
* Alan Oppenheim, MIT, USA, avo@mit.edu
* Roberto Togneri, University of Western Australia, roberto.togneri@uwa.edu.au
Please contact Danilo Mandic for any initial questions concerning this Special Issue.	
  

www.signalprocessingsociety.org

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MARCH 2020
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Content Gazette - March 2020

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