Member Highlight: Mário Figueiredo

Member Highlight: Mário Figueiredo 
Professor, Instituto Superior Técnico - Universidade de Lisboa,
and Instituto de Telecomunicações

Mário Figueiredo received his MSc (1990), PhD (1994), and habilitation (agregação) degrees, all in Electrical and  Computer Engineering from Instituto Superior Técnico (IST), the school of engineering of the University of Lisbon, where he has been a professor since 1994. He is currently an IST Distinguished Professor with the Department of Electrical and Computer Engineering and holds the Feedzai Chair of Machine Learning. He is also area coordinator and group leader at Instituto de Telecomunicações, a non-profit research institute associated with IST.

His research areas include signal processing, machine learning, and optimization. He is a Fellow of the IEEE, a Fellow of the International Association for Pattern Recognition (IAPR), a Fellow of the European Association for Signal Processing (EURASIP), and a Fellow of the European Laboratory for Learning and Intelligent Systems (ELLIS). He is also a member of the Lisbon Academy of Sciences and the Portuguese Academy of Engineering. Mário Figueiredo has received several national and international awards and prizes, namely, the IBM Portugal Scientific Prize (1995), the IEEE Signal Processing Society Best Paper Award (2011), the IEEE W. R. G. Baker Award (2014), the IAPR Pierre Devijver Award (2016), the EURASIP Technical Achievement Award (2017).

Mário Figueiredo has served the IEEE Signal Processing Society (SPS) as an Associate Editor of the IEEE Transactions on Image Processing (2000-2008), a member of the Image, Video, and Multidimensional Signal Processing Technical Committee (2005-2010), a member of the Machine Learning for Signal Processing Technical Committee (2013-2018), Senior Area Editor of the IEEE Transactions on Signal Processing (2015-2019), a Senior Editor of the IEEE Transactions on Computational Imaging (2019-2022), a Senior Editor of the IEEE Signal Processing Magazine (2022-2023).

We approached Mário Figueiredo to learn more:

Q: Why did you choose to become a faculty in the field of signal processing?

Maybe “choose” is not the most adequate word here. As in so many other aspects of life, a career turns out to result from a sequence of interactions, circumstances, contingencies, and local decisions by oneself and others around us. I was always very interested in mathematics, physics, and science in general, but also electronics as a hobbyist. As an undergraduate student at IST, the courses that I found most captivating were those at the intersection of mathematics, statistics, and its applications, namely signal analysis and processing, systems and control theory, and machine learning (called pattern recognition at that time). At the same time, I also had a strong interest in medical imaging, so I ended up doing my MSc thesis on a medical imaging topic (specifically, segmentation and analysis of angiographic images) and my PhD thesis on image restoration and segmentation (with some medical imaging applications). During that time, I was lucky enough that my supervisor (José Leitão) had established a collaboration with the cardiac imaging group at a hospital, thus I worked in close contact with clinical applications, which gave me the feeling that what I was doing could have a real impact in people’s lives. After that, in 1994, I became a faculty member in the Electrical and Computer Engineering Department of Instituto Superior Técnico, University of Lisbon, where I am currently a professor. During my career, I have taught courses in telecommunications, information theory, machine learning, image processing, and have done research mostly in signal processing and machine learning topics.

Q: How does your work affect society?

It is tough, if at all possible, to assess how my work directly affects society. I have made a few small contributions to some signal processing and machine learning areas (namely, image restoration and segmentation, optimization methods for inverse problems, sparsity, and model selection), which are now part of the large modern toolbox of concepts and methods in these areas or that served as stepping stones for further advances. Consequently, maybe I can immodestly think that I have made a little contribution to modern signal processing and machine learning, as countless others have. Given the impact that signal processing has in modern society (from telecommunications to remote sensing, from medical imaging to digital photograph, video, and multimedia communications), contributing, even just a little, to signal processing is contributing to the technological backbone of modern society.  

On the educational side of my career as a professor, I have taught thousands of students in these areas and have supervised more than 20 PhD students and roughly 100 MSc students. I believe that through all these students, whom I think I have helped to know a little more about signal processing and machine learning and who have had a huge variety of different career paths, my teaching and supervision also had some positive indirect effects on society.

Q: What challenges have you had to face to get to where you are today?

I don’t think I have faced any important challenges in my career and I prefer to take the opportunity to mention the positive influences that allowed me to be where I am today. Throughout my career, I feel that I have had the privilege of interacting and being supported by many generous, hard-working, intelligent, kind people, without whom I would not be where I am today..

The several amazing high school teachers who stimulated my curiosity and desire to learn and the many great professors at IST from whom I took courses as an undergraduate and MSc student sparked my desire to pursue an academic research career. My MSc and PhD advisor, José Leitão, taught me how to be an independent thinker and so many other important things. I also had the privilege of interacting and collaborating with several outstanding colleagues and friends at IST (among whom I would like to highlight the late José Bioucas-Dias, 1960-2020) and in other countries (namely, Anil K. Jain, from Michigan State University, and Robert Nowak, from the University of Wisconsin in Madison), without whom I would certainly not be where I am today. Finally, I was also lucky enough to have served as supervisor for many excellent students from whom I have learned so much; without them, I would also not be where I am today. Throughout the 30 years of my career, I have met many interesting people and made many friends, and this is probably one of the most positive aspects of an academic research career.

Q: What advice would you give to scientists/engineers in signal processing?

I have only very general advice to young scientists or engineers in signal processing or any other technical field: curiosity and passion are fundamental to doing excellent work, thus pursue topics and problems that stimulate those feelings in you; build a very strong background on the foundations of your field (in the case of signal processing and machine learning, this is mostly mathematics and statistics), it will pay off; seek supervisors, mentors, collaborators, and students with whom you believe the product of your work together will be more than the sum of the parts, i.e., with whom you can pursue synergistic interactions, and with whom you can establish a good human relationship.