Interview with Dr. Gabriele Patrizi—Winner of Electronics 2022 Best Ph.D. Thesis Award

We are pleased to announce the winner of the Electronics 2022 Best Ph.D. Thesis Award. This award is for a Ph.D. student or recently qualified researcher who has produced a highly anticipated thesis with impressive academic potential.

The award has been granted to “An Innovative Data-Driven Reliability Life Cycle for Complex Systems” by Dr. Gabriele Patrizi, Department of Information Engineering, University of Florence, Florence, Italy.

The winner will receive CHF 800, a certificate, and a chance to publish a paper free of charge after peer review in Electronics (ISSN: 2079-9292) in 2023.

We congratulate Dr. Gabriele Patrizi on his accomplishments. We would like to take this opportunity to thank all the applicants for submitting their exceptional theses and the Award Committee for voting for and supporting this award.

Dr. Gabriele Patrizi is currently a Post-Doctoral Research Fellow of instrumentation and measurement and an Adjunct Lecturer of electric measurements at the University of Florence. His research interests include life cycle reliability, condition monitoring for the fault diagnosis of electronics, data-driven prognostic and health management, and instrumentation and measurement for reliability analyses.

The following is a short interview with Dr. Gabriele Patrizi:

Could you please give us a brief overview of your research topic and the main objectives of your Ph.D. thesis?
I graduated from a master’s course in electronics engineering, and then I started my Ph.D. in electronics and industrial engineering. The actual name of the course is industrial and reliability engineering. But, of course, I tried to bring my background in electrical and electronics engineering with me. My research topics may mainly relate to electric and electronic measurements and reliability engineering, and my thesis tried to merge these two aspects, trying to include data analysis and a measurement technique to improve the reliability analysis of different kinds of systems for hardware electronics tools. At this time, I tried to first study and search for different alternatives to improve the standard reliability analysis method. After some proposed optimization, I tried to implement this technique in different application areas.

What motivated you to pursue this research topic, and how did you come up with your research questions?
I think the first motivation came from the acknowledgements gathered during my master’s thesis. I went to Spain for a four-month research project on reliability and maintenance, and during that period, I worked on a wind turbine with a professor at Luleå University of Technology in Sweden, and it was also at that time that the knowledge of a researcher at the Spanish Research Institute together with my professor's knowledge in Florence really directed my attention to the topic of reliability and maintainability of complex systems because, most of the time, we do not think about how important they are for lots of devices to be as reliable as possible. So, I think that, during that time, the general topic really caught my attention and basically just after my master’s graduation, my supervisors in Florence said that there could be the possibility of having a Ph.D. fellowship here in Florence. So, I submitted the application, and it went well. When I came to this laboratory, which is a two-topic laboratory on reliability and measurements, we decided: OK, let's try to come up with something that could merge these two aspects so that electric and electronic measurements could actually improve the reliability of all systems.

How did you manage your time and prioritize your tasks during your Ph.D. program, and what strategies did you use to stay focused and motivated?
I was still young, and it was obviously difficult to try and study all these aspects, go to work, and at the same time, try to move on with my personal life, and I think that the most important thing that allowed me to reach these results, and at the same time, to live let's say, a happy life was that I actually enjoyed what I was studying, I liked my research topic, and I liked what I was doing. So, I think this is the secret to achieving it, to manage your time properly during a Ph.D., even if sometimes the task seems enormous with respect to your resources. But if you enjoy it and you like what you are doing, you can find the motivation.

What were some of the biggest challenges you faced during your Ph.D. journey, and how did you overcome them?
I have to say that one big challenge was COVID-19 because I started my Ph.D. in November 2018, so I basically had one full year, one full year and a half in a normal situation, and then COVID-19 caused the university to close in Florence for at least four months completely. I mean, there was a possibility to go to the lab, but only for a very specific reason. This was motivated by supervisors, and not only supervisors, but also by the department. So, it was not easy to come to the lab and do the actual practical research. I have to say that I was also a bit lucky because some parts of my work were modeling and simulation, so I found a way to do them, at least partially, at home. But yes, that was one of the biggest challenges, and it was also one of the biggest regrets because it was not possible to go to conferences and workshops and meetings that usually, during a Ph.D., could bring you news, new ideas and new connections to improve your research and activities. So, I think the biggest challenge was probably that.

When and how did you access Electronics? What prompted you to apply for this award, and would you like to share your experience with the journal Electronics?
I discovered the MDPI award basically at the beginning of my Ph.D., trying to do some research on something others have done in my field, and then after, let's say one year, one year and a half, my supervisor received an invitation for a special session on Electronics about “Reliability and Maintainability of Industrial System and Electronic System”. We decided to reply to this invitation, and we sent a little bit of our work. It wasn't basically what was in my Ph.D. dissertation, it was like a little bit of extra work and work from others and from another Ph.D. student at the time. We had a good experience. We published the paper after a couple of review rounds, but everything was very fast and of a good quality, I believe, including the quality of the reviewers, and so on. When I was looking for the publication of the article, I looked a little bit more at the journal’s website because I have to say that I knew the MDPI website, and I knew that there are a lot of journals. I even already cited some papers published on electronics, but before publishing this paper, I had never actually looked into this. So, after the publication of the article, I looked into the website, and I saw that there was this annual reward for a Ph.D. dissertation, and I said: OK, let's make a note about this prize. Who knows? And then after one year, one year and a half when the thesis was finished, I looked into that and said: OK, let's try it. The research went well, so let's also try for the award. I think it was a good decision.

Finally, how do you plan to continue building on your research in the future, and what are your long-term career aspirations?
That's a very difficult question. After my Ph.D., I started a Post Doc-Fellowship here at the University of Florence, and so, basically, it's now one and a half years later that I'm doing the Post-Doc here and I like it. I also have done some teaching here at the Department of Information Engineering of the University of Florence on electrical measurements and electronic measurements, and the aspiration, I think, is to hopefully remain here doing research and teaching activities in Florence and try to explore a little bit more about the integration between these two worlds. I am starting something right now about integrating artificial intelligence to merge these two aspects of reliability and data analysis and electronic measurements. So, probably, I think in the future, I need to integrate artificial intelligence with my research to find a better way for reliability analysis in different fields.