Pablo A. Estévez, president of the IEEE Computational Intelligence Society (2016-2017), received his professional title in electrical engineering (EE) from Universidad de Chile in 1981, and the M.Sc. and Dr.Eng. degrees from the University of Tokyo, Japan, in 1992 and 1995, respectively. He is a Full Professor with the Electrical Engineering Department, University of Chile, and former Chairman of the EE Department in the period 2006-2010.

Prof. Estévez is one of the founders of the Millennium Institute of Astrophysics (MAS), Chile, which was created in January 2014. He is currently leading the Astroinformatics/Astrostatistics group at MAS. He has been an Invited Researcher with the NTT Communication Science Laboratory, Kyoto, Japan; the Ecole Normale Supérieure, Lyon, France; and a Visiting Professor with the University of Tokyo.

Prof. Estévez is an IEEE Fellow. He served as conference chair of the International Joint Conference on Neural Networks (IJCNN), held in July 2016, in Vancouver, Canada. Currently, he is serving as general co-chair of the 2018 IEEE World Congress on Computational Intelligence (IEEE WCCI 2018) to be held in Rio de Janeiro, Brazil, July 2018.

I had the opportunity to interview Pablo and I’m pleased to share it with you.

DF: How did you get into computational intelligence research?

PE: When I was an undergraduate student at the University of Chile, my senior thesis advisor was doing research on neural networks and fuzzy logic. I should note that this was before the appearance of the PDP book in 1986 – quite early! – and we worked on associative memories and single neuron models.

DF: I enjoy hearing stories from investigators who have been in the field for over 30 years. There are relatively few of us who have been blessed to have this much experience and see and contribute to the changes in computational intelligence over the years. So, what are you working on personally now?

PE: Currently, I’m working on feature selection methods and also on developing tools for understanding convolutional neural networks (deep learning) based on information theory. I’m applying CI techniques to time-domain astronomy, for example developing methods for finding periodic variable stars and detecting supernovae in very large data sets. I also do research on EEG processing. We’re using deconvolutional methods in combination with matching pursuit to find the timing and waveform of certain patterns, for example, sleep spindles.

DF: This is your second year as IEEE Computational Intelligence Society president ( What do you feel are the society’s biggest accomplishments during the last few years?

PE: Well, let’s start with one very recent accomplishment. Last February, we launched a new IEEE Transactions on Emerging Topics in Computational Intelligence (CI). For this new publication, authors are encouraged to submit manuscripts in any new areas, and in particular nature-inspired computing topics that aren’t covered by our other IEEE Computational Intelligence Society journals.

DF: Can you provide examples of what the journal is looking for specifically?

PE: Glial cell networks, computational neuroscience, brain-computer interface, ambient intelligence, non-fuzzy computing with words, cultural learning, computational intelligence for the IoT and Smart-X technologies. That’s just a partial list. We are also looking for novel CI applications.

DF: Okay, and what about the publications that the society has published for years?

PE: Our society publications have very high impact factors and are truly among the best in engineering and computer science. I should note too that this is the 20th year of the IEEE Transactions on Evolutionary Computation that you started back in 1997. We’re in year 24 of the IEEE Transactions on Fuzzy Systems, and year 27 of the IEEE Transactions on Neural Networks, known now as the IEEE Transactions on Neural Networks and Learning Systems.
We have more recent publications too, such as the IEEE Transactions on Games and the IEEE Transactions on Cognitive and Developmental Systems. I should mention we also sponsor a dozen conferences, among them the IEEE World Congress on Computational Intelligence with nearly 2,000 attendees. We also support many educational activities. For example, we have a large collection of videos of plenary and invited talks given at IEEE CIS flagship conferences []. We also support a distinguished lecturer program, summer schools, research grants, travel grants, and so on.

DF: We’re hosting the 2017 IEEE Symposium Series on Computational Intelligence ( in Honolulu later this year, 10 years after the inaugural event in 2007. What are your thoughts on how this symposium series has expanded and brought in new ideas to the society?

PE: First of all I would like to congratulate you, Piero Bonissone, and the other IEEE SCCI organizers on this 10th anniversary. It’s great to see that this innovative concept of having many concurrent CI symposia has become a successful annual event. I’m sure it will be a very successful conference. SSCI provides a unique opportunity to collaborate with communities both within CI and with those that are not usually within CI. I know this personally because the Astroinformatics community is organizing a special session in the computational intelligence and data mining event (IEEE CIDM 2017), one of the many symposia within SSCI. SSCI plays the key role of being an incubator of new ideas and conferences.

DF: Artificial intelligence is receiving a great deal more attention in the news lately. Do think that the news coverage is fair and appropriate?

PE: Artificial intelligence is a source of fantasy and fun for the people through books, TV series and movies. I enjoy that very much too, but it makes difficult for the lay people to distinguish reality from fantasy. On the other hand, we need to clarify and market computational intelligence, which is what we do.

DF: What efforts does the IEEE CIS make to help educate the public about computational intelligence?

PE: A good example is your public lecture at IEEE WCCI 2016 [|56|Selected_Videos&], which last I checked had been viewed almost 200 times already.

DF: [Laughing] Okay, I wasn’t trying to ask a leading question to fish for a compliment there.

PE: Quite all right. Your talk was a big success and you should do more of them! Building on that success, we plan now to continue to produce videos on CI topics that will be of interest to the general public. In addition, we do outreach activities oriented to high-school students and university students. Beyond producing educational material, we run very successful student competitions that bring the fun and excitement of computational intelligence to young people just entering the field.

DF: What do you see as the most likely next significant successes for computational intelligence?

PE: I think that CI will excel, and is already excelling, with big data applications, where we need to gain insight from all the data available, usually in a very short time. We will need scalable algorithms to be successful. I expect that new important discoveries will be made by data-driven science, for example in astronomy and life sciences. Currently, deep learning is one of the most successful methods for computational vision and signal processing. However, a more advanced theory is needed in order to better understand, design, and use this kind of model.

DF: Let’s think about people who are recent graduates in the areas of computational intelligence. Clearly, they have a great opportunity right now. Based on your experience, what advice do you have for them?

PE: I like very much Steve Jobs’ expression: “Stay hungry, stay foolish” — meaning to always keep wanting something more, as well as keep an open mind, never think that you know everything. My personal favorite is: “It takes two to tango,” meaning that in today’s world it’s key to cooperate with other researchers internationally.

To contact Pablo Estevez, email and visit his home page at
To contact David Fogel, email and visit his news page at
© David Fogel, 2017

Links for David’s other interviews:
Prof. Kalyanmoy Deb, Dept. Electrical and Computer Engineering, Michigan State University

Interview with Prof. Kalyanmoy Deb, Dept. Electrical and Computer Engineering, Michigan State University, MI, USA

Dr. Joseph Lizier, Chair 2017 IEEE ALIFE Symposium

Interview with Dr. Joseph Lizier, Chair of the 2017 IEEE ALIFE Symposium

Prof. Dipankar Dasgupta, 2017 IEEE Symp. Computational Intelligence in Cybersecurity

2017 IEEE Symposium Series on Computational Intelligence: Interview with Prof. Dipankar Dasgupta on CI and Cybersecurity

Prof. Xin Yao, Chair, 2017 IEEE Symp. Computational Intelligence and Ensemble Learning

2017 IEEE Symposium Series on Computational Intelligence: Interview with Prof. Xin Yao of University of Birmingham

Prof. Pnnuthurai Suganthan, Chair 2017 IEEE Swarm Intelligence Symposium

2017 IEEE Symposium Series on Computational Intelligence: Interview with Prof. Ponnuthurai Suganthan

Prof. Vincenzo Loia, Chair, 2017 IEEE Symp. Computational Intelligence and Intelligent Agents

2017 IEEE Symposium Series on Computational Intelligence: Interview with Prof. Vincenzo Loia

Prof. Leonid Perlovsky, Chair, 2017 IEEE Symp. Computational Intelligence in Cognitive Algorithms, Mind, and Brain

2017 IEEE Symposium Series on Computational Intelligence: Interview with Prof. Leonid Perlovsky