Senior Scientific Advisor — Data Science, Machine Learning & Applied AI
Data Science · Machine Learning · Applied AI
Dr Mireille Esther Gettler Summa is a mathematician and Data Science researcher whose scientific trajectory spans more than four decades, from the emergence of data analysis and expert systems to contemporary Machine Learning, Deep Learning and interdisciplinary data-driven research.
Dr Mireille Esther Gettler Summa’s scientific career is rooted in mathematics, probability and Data Analysis. Her work developed towards textometry, statistical methods and the analysis of complex real-world datasets across disciplinary boundaries.
Her long-standing academic activity in mathematics and computer science includes work at Université Paris Dauphine and within CEREMADE, at the intersection of statistics, computer science, econometrics and Data Analysis.
Her research interests developed through automated classification, recognition and algorithmic learning, connecting mathematical methods with practical analytical problems.
Over subsequent decades, she applied statistical and computational approaches across environmental and biological observations, astronomy, electoral analysis, health-related data, signal recognition and textual data.
Dr Gettler Summa has contributed to European collaborative research and has experience connecting fundamental Data Science research with industrial applications.
Across her career, she has worked across academic and industrial environments, applying statistical, computational and data-driven approaches to real-world analytical challenges.
Her work contributes to the dialogue between mathematical foundations, statistical learning, Machine Learning and practical Data Science.
Her scientific interests have continuously evolved alongside the field: from multivariate Data Analysis and expert systems to statistical learning, Machine Learning, Deep Learning and contemporary data-driven research.
Beyond academic research, Dr Gettler Summa has experience connecting scientific work with innovation and entrepreneurship. Her career includes participation in university innovation environments, applied research with industry and the translation of Data Science methodologies into operational contexts.
This combination of mathematical foundations, scientific research, industrial applications and innovation aligns with BECOME’s science-to-technology and DeepTech Venture Building model.
At BECOME, Dr Gettler Summa contributes expertise in Data Science, statistical learning, Machine Learning, Deep Learning, scientific modelling, AI applied to IoT and sensor data, research methodology, European collaborative R&I, doctoral research and interdisciplinary data-driven research.
Her recent work includes Deep Learning applied to IoT sensor data for energy optimisation and thermal comfort management in buildings.
Her contribution supports BECOME’s wider objective of connecting scientific research, Artificial Intelligence, IoT, energy systems and real-world technology development.
Her current research interests also extend to General Linguistics, applying data-driven methodologies to French textual data and written language.
This work continues a scientific trajectory across mathematical and statistical Data Analysis, Machine Learning, Deep Learning and interdisciplinary Data Science.
5 records
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 detailsDr Gettler Summa brings long-standing experience in Data Science, statistical learning and interdisciplinary applied research to BECOME’s European Research & Innovation activities.
Her expertise is particularly relevant to projects combining scientific data, Machine Learning, modelling, IoT, energy systems and multidisciplinary research.