Series to Highlight Women in Signal Processing: Monica Bugallo

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News and Resources for Members of the IEEE Signal Processing Society

June 2021

Series to Highlight Women in Signal Processing: Monica Bugallo

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Enugu State University of Science and Technology SPS Student Chapter
Member Highlights
By: 
Dr. Anubha Gupta

Monica Bugallo

Mónica Bugallo
Professor of Electrical & Computer Engineering
Vice Provost for Faculty Affairs & Diversity, Equity and Inclusion
Faculty Director of the Women In Science & Engineering (WISE) Honors
Stony Brook University 

Mónica F. Bugallo received her Ph.D. in computer science and engineering from University of A Coruña, Spain. She is a Professor of Electrical and Computer Engineering and the Vice Provost for Faculty Affairs, and Diversity, Equity and Inclusion at Stony Brook University, NY, USA. Bugallo is the current Chair of the IEEE SPS Signal Processing Theory and Methods Technical Committee, Senior Associate Editor of the IEEE Signal Processing Letters and Associate Editor of the IEEE Transactions on Signal Processing. Her research is focused on statistical signal processing, with emphasis on the theory of Monte Carlo methods and its application to different disciplines including biomedicine, ecology, sensor networks, and finance. She has also focused on STEM education and has initiated successful programs to engage students at all academic stages in the excitement of engineering and research, with focus on underrepresented groups. She has authored and coauthored two book chapters and more than 185 journal papers and refereed conference articles.

Bugallo is a senior member of the IEEE.

We approached Monica Bugallo with a few questions:

1. What was the most important factor in your success?
 
I do not think that there was a single factor. I think that several factors that have influenced my career and I would probably highlight hard work, humility, and collaboration. I was fortunate to get great opportunities that I accepted at the right time, I also had great mentors and role models who have guided me and helped me in my professional career and most importantly I have been able to follow my professional passions and enjoy what I do all the way. 
 
2. Failures are an inevitable part of everyone’s career journey, what is the most important lesson you learned during your career when dealing with failures?
 
I think that I learned to live with the failures and to be prepared to accept them, but also to not stop trying and continue forward. When I have failed, I have learned and I have achieved new understandings and made new connections.
 
3. Please share your work of societal impact with us.
 
Some of my most recent work is on the development of novel scalable Bayesian inference methods for systems of the highest complexity, with large amounts of unknowns and possibly big data. The developed theory can have a high impact in a vast range of application domains including computational biology and other biological-related areas, earth and environmental sciences, epidemiology, finance, communications, and sensor networks. In particular, I am currently working on the application of the resulting methods to an ecological problem related to the inference of the demographic rates of penguin populations in the Antarctic, which can enable large-scale and non-invasive monitoring of penguin populations to be used for decision-support applications. Another current application of the developed theory is a biological problem involving the estimation of gene regulatory network topologies, which can allow for a better understanding of complex metabolic processes.
 
4. During these COVID times, the teaching and learning has become online for some time as of now. What do you think are some of the challenges being faced in carrying out quality teaching as well as quality research? Do you have any suggestions for students and faculty?
 
I think that the adaptation to the new mode of class delivery for both students and faculty has been hard, especially because we were all adjusting at the same time to a new way of living in extremely stressful and uncertain circumstances. Engagement, learning and assessment in the new virtual academic setting have been challenging as well as finding good and effective supporting systems for both faculty and students. The quality of research has also suffered from this new adjustment and the personal circumstances affecting all of us. However, we have also learned valuable lessons related to processes that can now be more efficient in remote environments and we have also learned to be more flexible. Moving forward and as we see the brighter future ahead we should take the positives and try to pursue hybrid learning and research strategies as the previous year experience has clearly opened the door to an even more digital future. 

To learn more about Monica Bugallo, please visit her webpage. 

Tags: 
Women in Signal Processing
Leaders in Signal Processing

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