10 IEEE SIgnal ProcESSIng MagazInE | July 2017 |

Community VoiCesAndres Kwasinski and Min Wu

elcome to the first article in a newly launched column, “Community Voices,” in IEEE Signal Processing

Magazine. The motivation behind this column is to strengthen ties with read-ers and members in the signal process-ing community. In doing so, we set out to collect reflections from diverse members of our community on questions that are of interest to many. A readily available form on the Internet as well as e-mail exchanges were used to gather respons-es. This first article of the “Community Voices” column focuses on the question “For a person with signal processing training, what do you consider as a suc-cessful career?”

We begin with input from Charles Casimiro Cavalacante from Brazil, who was the first to respond to the web form. We welcome your feedback on this new initiative and your ideas in suggesting future topic questions. The second topic on the future of signal processing is open for input. Please refer to “The Fu-ture of Signal Processing” for the topic and web links. We hope that you enjoy this new column and look forward to hearing from you.

Charles Casimiro CavalacanteSignal processing is broad, and career prospects for signal processing prac-titioners are just as diverse. There are practitioners in biomedical engineering, industrial automation, electronic design,

acoustics and audio applications, image and video process-ing; robotics, navi-gation systems, data and financial analyt-ics, communication

systems, and many others. There are growing research areas in data analyt-ics, perceptual computing, smart energy technologies, and sensor systems for enterprise and industrial applications. There is a wealth of signal processing expertise in research institutions pushing signal processing reach into many fields through research projects and training of the next cadre of practitioners.

While judging career success is a subjective exercise, there are good indi-cators common to most people’s ideal of a successful career. These include drawing satisfaction from day to day job activities, progressive growth in project

responsibilities and influence, and doing recognized and rewarding work that has measurable impact.

Given the breadth of signal pro-cessing career opportunities and un-derstanding what constitutes career success, what does a successful signal processing career look like? I am a midcareer practitioner with experience in both academia and in industry. I consider myself a work in progress to-ward career success. Signal processing has enabled me to contribute to model-ing high-speed computer interconnects and gain insight into channel equaliza-tion challenges, train students on filter design, and witness the excitement of translating design-rule steps to circuit im-plementation for a rudimentary working guitar pickup. These are some rungs on a ladder toward a satisfying career.

Listening to senior engineers dis-cuss their most impactful work and the

What Do You consider a “Successful” career? Perspectives from signal processing-trained professionals

Digital Object Identifier 10.1109/MSP.2017.2698118Date of publication: 11 July 2017

After half a century of development, some say signal processing is already matured in terms of theories and techniques and perhaps would not have a new research breakthrough. Others have observed the problem of “signal processing inside.”

What are your thoughts about the future of signal processing? Please pro-vide your input by filling out this web form: https://www.surveymonkey .com/r/SPSCommunityVoices2.

A selection of the responses will be published in an upcoming issue of IEEE Signal Processing Magazine or Inside Signal Processing eNewsletter, subject to editing for language and length.

the Future of signal ProcessingW

11IEEE SIgnal ProcESSIng MagazInE | July 2017 |

process that took them from ideation to re-sults shows that careers are a journey indeed. In short, a successful career is a hodgepodge of experiences, growth through overcoming challenges, project successes, and willingness to embrace new ways of using signal processing train-ing in different engineering problems.

AuthorCharles Casimiro Cavalcante (charles@ gtel.ufc.br) received a Ph.D. degree from the University of Campinas. He is an associate professor at the Univer-sidade Federal do Ceará, Brazil, and holds the Statistical Signal Processing Chair. He has been a visiting assistant professor in the Department of Com-puter Science and Electrical Engi-neering at the University of Maryland, Baltimore County. He is a Senior Mem-ber of the IEEE and of the Brazilian Telecommunications Society.

Khaled El-MalehI have witnessed the great impact of sig-nal processing in our lives! With signal pro-cessing training span-ning three degrees (my B.Eng., M.Eng.,

and Ph.D. degrees) followed by more than 17 years of industry experience, I have been fortunate to have a successful and rich signal processing career. I think the main reasons for this success have been realizing the great value of continu-ing my relationship with academic insti-tutions (both students and professors), with the IEEE Signal Processing Soci-ety, as well as working on developing multimedia consumer products using signal processing algorithms. Examples of such products are smartphones with wide-band telephony, advanced camera and video telephony, and streaming. In addition, I have recently expanded my signal processing knowledge in emerging areas like the Internet of Things, automotive, mobile health care, and smart cities.

AuthorKhaled El-Maleh (kelmaleh@qualcomm .com) received his Ph.D. degree in

electrical and computer engineering from McGill University, Canada. He is a senior director of technology in the Intellectual Property (IP) Department of Qualcomm leading the Sensor and Display IP Portfolio Team, Multime-dia Technology Team, and related IP Strategy areas. He is a technologist and strategist with focus on entrepre-neurship and innovation, as well as an accomplished inventor with more than 200 U.S. and international patents. He was awarded the Qualcomm Career Thought Leadership Award in 2009 and the IP Department 2013 Distin-guished Contributor Award.

Gene A. FrantzI first will start with an equation, which is the basis for my answer: DSP + Divide = Math.

When we began the drive into digital

signal proessing (DSP), both in theory and hardware, we avoided the divide operator, as hardware didn’t do the divide operation well. In spite of that, DSP technology advanced in both theo-ry and hardware, finding new uses and new users. These new uses demanded high-performance math engines. Late-ly, new terms such as cloud comput-ing, the Internet of Things, big data, smart sensors, etc. are driving us even harder than those initial drivers of DSP (speech, modems, hard disk drives, and three-dimensional graphics). Now, with this as a background, I can answer the question of what does a successful career look like? It is a career where the technology I helped to create became a societal necessity within the span of my career. For many of us, this has happened multiple times. It will con-tinue to happen. All we need to do is to continue to look for those new uses and new users and then make it happen.

AuthorGene A. Frantz (Gene.Frantz@octa vosystems.com) is an engineering man-ager/professor in practice at Rice Uni-versity, Houston, Texas. He took this position after 39 years at Texas In-

struments (TI), where he retired as TI’s Principal Fellow. He is a recog-nized leader in DSP technology both within TI and throughout the indus-try. He holds 48 patents in the area of memories, speech, consumer products, and DSP. He has written more than 100 papers and articles and continually presents at universities and conferences worldwide. He is an IEEE Fellow.

Shan HeA successful career with signal process-ing training is one where you can utilize your analytical skill obtained during the t ra in ing to either

directly solve a technical problem, such as working as an engineer, or assist oth-ers to clarify their solution and to obtain rights associated with solution, for example, working in the patent law area. I am currently practicing patent law, and I found my signal processing back-ground bring me tremendous advantage over other patent practitioners. This is because my strong technical back-ground enables me to understand the invention quicker and deeper, which allows me to assist inventors to achieve the broadest possible legal protection for their invention.

AuthorShan He (shanhe@gmail.com) received her Ph.D. degree in 2007 from the Uni-versity of Maryland, majoring in com-munications and signal processing. She worked as a research scientist in the research lab of Thomson Multimedia for three years. She then switched her career path in 2010 to become a patent agent with Lee & Hayes, PLLC, serving clients including the world’s most valu-able technology companies. She expects to obtain her law degree in Decem-ber 2017.

Hing Cheung SoFrom my point of view, a successful engineer is an excellent problem solver. To solve a problem, the first step is to identify it and investigate if it is worth tackling. The second step is to formulate

12 IEEE SIgnal ProcESSIng MagazInE | July 2017 |

the problem—de-scribe it clearly with unambiguous require-ments. Next, we ap-ply our knowledge as well as creativity to devise solutions and

then choose the best among the pro-posed alternatives according to the pre-set criteria or via balancing all the pros and cons. Finally, the solution is put into practice.

In fact, the problem-solving skill set is well trained through fundamental sig-nal processing courses including Sig-nals and Systems and Digital Signal Processing. For example, we learn that problems in linear time-invariant sys-tems can be solved by either a time- or transform-domain approach, and a digi-tal system can be designed using differ-ent finite impulse-response or infinite impulse-response filters that meet the same specifications. In the former, we also experience that the time-domain solver is easier in certain scenarios and vice versa, while one filter can be implemented with minimum complex-ity in the latter, stimulating us to think about the optimum choice. In addition, to be successful, I believe we should only focus on the most investable prob-lems (i.e., think big) and realize the best solution in an efficient and persistent manner. A spirit of humility, open-mindedness, and willingness to learn is important, too.

AuthorHing Cheung So (h.c.so@cityu.edu.hk) received his Ph.D. degree in electronic engineering from The Chinese Univer-sity of Hong Kong. He is a professor in the Department of Electronic Engi-neering, City University of Hong Kong. From 1990 to 1991, he was an electronic engineer with the Research and Devel-opment Division, Everex Systems Engi-neering Ltd., Hong Kong. He has been on the editorial boards of IEEE Signal Processing Magazine, IEEE Transac-tions on Signal Processing, Signal Pro-cessing, and Digital Signal Processing. He is a Fellow of the IEEE.

Pramod K. VarshneySignal processing is involved in a very wide variety of sys-tems and applications, and a person trained in this field can have a broad impact. Pos-

sibilities include hardware, software, and algorithmic developments in the areas of defense, security, health, educa-tion, quality of life, and even social good. Since signal processing training prepares one to tackle a broad range of problems, a successful career will include agility and the ability to learn quickly so as to con-tribute to ever-changing technological trends and needs. The key is to be able to adapt and move to new areas. When I look back at my career, with my training

in statistical signal processing, I have been able to contribute to wide-ranging applications such as intelligent radars deployed on several U.S. Air Force platforms, fault detection for health management of air and space vehicles, mammography automation, and secur-ing wireless sensor networks. In my opinion, a successful career would be one in which signal processing training is applied to solve diverse problems so as to impact societal needs and improve quality of life.

AuthorPramod K. Varshney (varshney@syr .edu) received his Ph.D. degree in elec-trical engineering from the University of Illinois at Urbana-Champaign. He is with Syracuse University, New York, where he is currently a distinguished professor of electrical engineering and computer science and the Director of the Center for Advanced Systems and Engineering. He is also an adjunct pro-fessor of radiology at Upstate Medical University, Syracuse. He received the IEEE 2012 Judith A. Resnik Award, Doctor of Engineering Honoris causa from Drexel University in 2014, and the ECE Distinguished Alumni Award from the University of Illinois in 2015. He was the president of the International Society of Information Fusion during 2001 and is a Fellow of the IEEE.

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