BECOME / DATA & AI
Start with the decision or task that needs to improve. Then establish whether data and AI can make a useful contribution.
Discuss a Data & AI challengeAI projects depend on more than a model. They need relevant data, a meaningful baseline, clear evaluation criteria and people who can use the result. BECOME’s Data & AI focus connects these questions with applied research and project development.
Describe the current process, the people affected and the outcome you want to assess. Together, these provide a basis for comparing an AI approach with existing practice and deciding what a first experiment should test.
Examples for scoping include research-data analysis, decision support, document workflows and interpretation of sensor or Earth-observation data. The appropriate application depends on data access, specialist expertise and a clearly bounded use case.
A project can begin with a feasibility study or a limited prototype. The output should explain what was tested, how it performed and whether further development is justified. Any operational deployment requires its own delivery scope and responsibilities.
Use Executive Builder to develop a decision-ready business case, Corporate Builder to frame an organisational challenge, or Venture Building to assess a technology opportunity.
3 records
Senior Scientific Advisor — Data Science, Machine Learning & Applied AI
Mathematician and Data Science researcher with more than four decades of experience spanning statistical learning, Machine Learning, European R&I and applied AI.
View Scientific ProfilePhD in Electrical Engineering
Chedia Jarray holds a PhD in Electrical Engineering.
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PhD in Electrical Engineering
Mohamed Khayri Rahmani holds a PhD in Electrical Engineering and researches AI-driven energy efficiency and intelligent control.
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This journal article presents the Twin-Federated-Loop architecture, focusing on privacy preservation and personalization in thermal comfort management.
View detailsThis journal article examines a novel data-balancing approach for thermal comfort prediction through numerical and experimental study.
View detailsThis conference paper examines predictive trajectory-based control of thermal comfort in smart buildings.
View detailsThis conference paper examines the role of gender in thermal comfort prediction in industrial environments using an XGBoost approach.
View detailsThis conference paper explores transfer learning with deep GRU-BiGRU models to address data scarcity in thermal comfort prediction for office environments with climates similar to Tunisia.
View detailsBrand hate is a complex feeling that is not easy for companies to recognize. Mednini and Turki (2022) have confirmed that hate can originate from genuine brand haters or an employee who works with competitors, to…
View detailsThe use of unmanned aerial vehicles (UAVs) for data gathering in wireless sensor networks (WSNs) and Internet of Things (IoT) applications has significantly gained interest in recent years. This shift is mainly attributed to the fast…
View detailsDue to the limitations of sensor devices, including short transmission distance and constrained energy, unmanned aerial vehicles (UAVs) have been recently deployed to assist these nodes in transmitting their data. The sensor nodes (SNs) in wireless…
View detailsUnmanned aerial vehicles (UAVs) and Terahertz (THz) communication are promising technologies envisioned to support the race towards enhanced performance with respect to data rate, reliability, coverage, etc. Research on the merger of these two technologies for…
View detailsBring a challenge, a contribution or an opportunity.