Maria Arostegi, received her degree in mathematics (Number Theory) in 1995 from the EHU-UPV (Basque country University), after studying her last year in Milano (Italy) in L’Universtità degli Studi di Milano.

In 1996 she attended the Course on Pedagogical Aptitude, and the next two years she obtained some grants to work in the mechanics department of LABEIN where she focused on Virtual Reality. Later on she received another grant from the “Bizkaiko Foru Aldundia” to follow her training on Virtual Reality tools in VRAC (Virtual Reality Applications Center, Ames-IA), working with the Carolina Cruz-Neira research team. Specifically in this period, she worked on geometric modelling, software navigation and photo-realistic treatment.

From then to 2017, she worked on some projects related with 3D-modelling tools, graphic interaction, or computation and simulation on several scenarios., getting specialized on developing Software predictive tools to rolling mills, continuous casting and reheating furnace. More specifically developing the heating module in 1D, 2D and 3D and the software interfaces for those steel processes, that is to say:

• Mathematical development of the three-dimensional equations of the heat transfer in the steel processes.
• Mathematical development of the (2D and 3D) View factor’s related with the geometrical shapes involved in the reheating furnace process, in order to calculate the radiation of the heat transfer.

On 2017, she focused on study of mathematic algorithms of data analytics, machine learning and big data technologies (such as Hadoop, Spark, etc.…), getting a training action on “Big data, Business Intelligence, and Data Science” attending an online Master’s degree issued by INESEM.

From then on, she has participated in several AI projects by using Artificial Intelligence techniques; Machine Learning; clustering schemes, dimensional reduction, unbalanced strategies, regressive schemes, linear, lasso, elastic-net, SVMs, CART, RF, assembly methods (bagging, and boosting).  She is currently developing her thesis on "Explainable continual learning over data streams", within the framework of the PhD program of the UPV/EHV, part-time, in the field of Information and Communication Technologies in Mobile Networks.