Driely Celestino Da Costa

Today, media companies are more concerned about their customers. They have become the main focus since they choose what to watch at any time and any place. Moreover, mental well-being is currently one of the main concerns of users and, consequently, media companies. Therefore, all these data and procedures can be useful for companies that care about the well-being of users and want to offer them the most suitable content.

The main purpose of the data collected at this research project will be to generate recommendation insights to end user’s customers, in a more personalized way. It is hoped that those insights can even be able to help the end user’s well-being. And covering these main topics: AI-based conceptual content modeling and advanced user profiling for an emotionally safe TV experience; and Contribution to mental well-being at home via smart and hyper personalized content-based recommendations.

The data planned to be collected and worked at this research project is metadata from Video on Demand (VoD) resources. These metadata will be processed by using Natural Language Processing (NLP) techniques to provide useful and meaningful inputs to a content recommender.

EDUCATION

Universidad Politécnica de Madrid – PhD’s student in in Communication Technologies and Systems at the Superior Technical School of Telecommunication Engineers

LAST WORK EXPERIENCE

International Business Machines (IBM) – Data&AI Partner Technical Specialist

PAST RESEARCH PROJECTS

Iberdrola Group: Circular Economy in the Electric Sector Project.

Universidade Federal de Juiz de Fora: Pollution Dispersion in the Paraibuna Watershed by Toxic Substances from Road Transportation Project.

University of Georgia: Heat Stroke and vehicle-related hyperthermia in children (CURO) Project http://noheatstroke.org/Brazil/ & National Weather Service’s Heat Advisory Project.

Illinois Institute of Technology: Finite Element Methods for Environmental Transport Process Project.

PORTE Jr. Company: RECICLE Project.

SKILLS

Technology: Microsoft365, Python, Jupyter, C++, RStudio, MSProject, ArcGIS, AutoCAD, ModFlow.

Languages: Native Portuguese, Fluent English, Fluent Spanish, Advanced Italian.