Member in the spotlight: Ercan E. Kuruoglu

In this series we aim to introduce society members and other experts of the signal processing field by means of interviews. This month, we are happy to present the Dr. Ercan E. Kuruoglu, Senior Researcher from ISTI-CNR Pisa, Italy.

You were involved in editorial and conference organizer roles in various signal processing societies, including IEEE SPS, EURASIP and the Elsevier Digital Signal Processing journal. Could you briefly compare the scopes of the different organizations, and the categories of scientific content they expect from contributing authors?

They are all top quality organizations, which deliver the highest level of quality, in conferences, in publications and other professional services. I was involved in the organization of both ICASSP of IEEE SPS and EUSIPCO of EURASIP, which are the top two signal processing conferences in the world. ICASSP has more global vision while EUSIPCO has emphasis in Europe despite attracting attendance also from the USA and the Far East. Both provide frontier research talks and require top-level contributions to attend as speakers. EUSIPCO also provides a venue for the European project partners to meet. IEEE SPS publications are the highest impact factor journals, which are difficult to publish in and therefore promise a higher quality; however, in this process some work with novel ideas are eliminated due to over critical reviewers. Digital Signal Processing Journal of Elsevier aims to provide a just and fast review process and be flexible to accommodate research papers, which challenge existing conceptions. The topic areas cover all fields of signal processing including image processing and speech processing but also extend to emerging applications such as computational biology, environmental signal processing and financial time series analysis. In addition to regular research papers, it publishes also tutorial papers. The acceptance ratio of DSP is 26% and the mean time to first decision is 74 days.

What do you expect from the recent announcement on the SPS-EURASIP Partnership?

I expect this partnership to end the illogical divide between European and US research communities and help establish more collaborations between the two sides of the ocean as well as a more direct exchange of information.

When did you first come into touch with signal processing? What was your motivation of following a career in this domain?

During undergraduate courses. It was the course, which I studied with almost no effort, and I felt comfortable working with signal processing methodology. My career choice is motivated by the flexibility signal processing provides one to work on vastly different applications. In the beginning of my career, I was working on document image processing, then SAR imaging, and now on genomics. I have worked also with seismologists, astrophysicist. The field provides me continuous excitements with new problems.

What was the first signal processing algorithm you ever implemented? In which context was it used?

As far as I can remember, the first algorithm I developed was the Viterbi algorithm for trellis waveform coder design. I had combined it with Simulated Annealing and obtained trellis coders with the highest performance up to date. I was a final year undergraduate student then and managed publishing it a respected journal and later as a book chapter.

What are your current research interests in the signal processing field?

I work on several problems related to genomics. I also continue to work on alpha stable processes which was the topic of my PhD thesis and have collaborations on fields such as seismology and climatology. I frequently use information theory concepts as well in my work.

Could you introduce an important state-of-the-art research issue (or technology) in this field?

Gene interaction network modelling. We are getting increasingly aware that genes work in orchestra rather than in isolation. It is vital to understand the interactions between genes to be able to understand basic cell processes as well cancer. Our knowledge on probabilistic graph theory, especially Bayesian networks helps us to develop methodology for building gene interaction networks.

In your opinion, what was the most impressive result published in IEEE SPS journals and conferences within the last 10 years?

Particle filtering or sequential Monte Carlo, which provides a solution for the problem of estimation of non-stationary signals under non-Gaussian noise through observations nonlinearly related to unobservables, has been one of the most important developments. The following paper provides a very good presentation of the topic for distributed sensing:
O. Hlinka, F. Hlawatsch, and P. M. Djurić, “Distributed particle filtering in agent networks,” IEEE Signal Processing Magazine, vol. 30(1), pp. 61-81, 2013.

In your opinion, what was the most impressive result published in IEEE SPS journals and conferences within the last 12 months?

I consider the new emphasis on big data very interesting. The following paper provides a good introduction.
Slavakis, K.; Giannakis, G.B.; Mateos, G., "Modeling and Optimization for Big Data Analytics: (Statistical) learning tools for our era of data deluge," IEEE Signal Processing Magazine, vol.31, no.5, pp.18,31, Sept. 2014.

From your experience, is there something the signal processing society can learn from other societies?

The computer science society (especially ACM) is far more successful in achieving visibility in the wider public. We should be more open and communicative with the general public. We should aim to publish also papers, which are more accessible to other disciplines. Most things we had invented 20 years ago are being reinvented by Computer Science people who sell it better and more quickly to other fields.

From your point of view, what are the biggest challenges signal processing should solve in the next years?

Methods to deal with bigger, nonstationary data and nonlinear systems. Stationarity is no longer a valid assumption. Big is getting even bigger. Systems are no longer conveniently defined by input and output relations.

What would be your advice to a new PhD student who wants to start a career in signal processing?

Firstly, be a free thinker. Instead of running after what is the hype, follow your own interests and intuition. One day you may find out that you are the pioneer of a new field. Second, try to learn more mathematics than the engineering curriculum provides you. It will be very useful to make a difference in your career. Lastly, keep in mind that life is also short and precious and the world is unjust with billions living in poverty. Try to work on subjects that would improve life of human kind and reduce the imbalance on this world rather than entering projects that make military or financial companies richer.

Do you have any comments about the development of signal processing research?

We should drop some dogmas and be more flexible about the methodologies and application areas.

Which application fields should be more focused in IEEE SPS publication?

IEEE SPS should adopt a more liberal definition of signal processing and consider applications in a wider scale ranging from financial data analysis to environmental engineering.

Do you have any suggestions about our e-NewsLetter?

Should be more communicative with the readers.

Brief biography

Ercan E. Kuruoglu was born in Turkey in 1969. He obtained his PhD degree in Information Engineering at the Cambridge University, in 1998. He joined the Xerox Research Center in Cambridge in 1998. In 2000, he was in INRIA-Sophia Antipolis as an ERCIM fellow. In 2002, he joined ISTI-CNR, Pisa where he is currently a Senior Researcher. He was a visiting professor in Georgia Institute of Technology-Shanghai in 2007 and 2011. He is a recipient of Alexander von Humboldt Experienced Research Fellowship and worked at Max Planck Institute for Molecular Genetics during his fellowship period. He was an Associate Editor for IEEE Trans. Signal Processing and IEEE Trans. Image Processing. He is the Editor in Chief of Digital Signal Processing. He was the Technical co-Chair of EUSIPCO 2006 and the Tutorials co-Chair of ICASSP 2014. He was a member of the IEEE Technical Committee on Signal Processing Theory and Methods. His research interests are in statistical signal and image processing and information theory with applications in genomics, telecommunications, computer vision and astronomy.