- What made you choose to do a PhD?
Since I can remember, I always loved to study. I am the first person in my family to have a Bachelor’s degree. So, I think that always motivated me to become a PhD one day. Moreover, technology is constantly evolving, so to deeply understand and work with specific topics in its entire process and lifetime; time, focus, and a lot of research are needed.
- How did you hear about SDGine and Marie Curie’s actions and sponsorship?
I did my master’s degree at Universidad Politécnica de Madrid too, so I got a UPM email about a different topic that made it through the UPM webpage. Once there, I started looking around the webpage and found myself in the SDGine and MSCA PhD call for applications.
- Why have you chosen this particular field?
I would say that my career path brought me here. I have always been involved in research related to Data, but after my master’s degree, I started to work in positions more related to Innovation Data & Artificial Intelligence. Working with it made me realise how important it is for our present and future as human beings, and made me passionate about the topic. So, I started to look for Data & AI PhD opportunities and found this project on the UPM webpage, with a topic focused on Artificial Intelligence, and where I could also positively impact people’s life.
- What difficulties do you expect to encounter during this project?
There are some difficulties, mainly related to bureaucracy, and communication among all the people involved in the action. From a technical perspective, the improvement of my Artificial Intelligence skills, and the psychology inputs that we need to take into account during this project, for a better and safer content recommendation. For this last one, we are planning to collaborate with specialists in the field during the Doctorate Secondment at institutions with expertise in the field.
- What do you plan to do after you complete your PhD?
I want to continue working with Data & Artificial Intelligence projects and companies that positively impact people’s lives.
Optiva Media is a leading company in the audiovisual industry with more than 15 years of experience, validated by key players in the market. To maintain this privileged position in the current paradigm-changing context of the TV market, with increasingly demanding consumers that require total control of what/when/how they consume content, Optiva Media needs to offer differentiating solutions based on data science and machine learning.
Participating in the SDGine project gives us the perfect opportunity to successfully achieve this objective, allowing Optiva Media to work closely with a forefront research group at the university to train a high-skilled researcher that will boost our developments with the application of state-of-the-art solutions endorsed by both scientific and academic criteria.
Making Driely feel part of the team at Optiva Media is my main objective as co-supervisor, as I believe it is key for aligning her research with the company’s interests and, most importantly, supporting and facilitating her daily work with our knowledge and expertise in both the TV domain and the underlying technology. All this along with the establishment of a permanent communication channel with José Manuel, her supervisor at university, to assure a perfect synchronization between academic and industry objectives and correct assistance for Driely during the whole PhD.
As the supervisor, I hope to be able to help Driely by relying on our knowledge of data analysis and processing, and its application in machine learning solutions. Our long experience in the research of services linked to audiovisual content will surely contribute, as we can combine aspects of audiovisual signal characterization and communications, as well as analysis for applications of recommendation, accessibility and usability.
I believe that the SDGine programme offers an excellent opportunity to train PhDs who will then project their experience in the company. The fact of having the full involvement of the company forces the thesis topic to be linked to lines of research that are of their interest, and to facilitate the transfer of knowledge from the university to the industry.