I-NERGY aims to support and develop novel AI-based energy services as part of the enrichment of European AI-on demand platform. This webinar will present the objectives and scope of the project, its requirements in terms of resources and the successful utilisation of EGI infrastructure. The webinar will conclude with a demo of I-NERGY services.
Domain scientists and researchers
I-NERGY project and AIOD overview (scope, objectives, services / assets, pilots) – 15′ minutes
I-NERGY needs (related to resources) and….. – I-NERGY architecture and how EGI infrastructure was used and supported us – benefits from this collaboration / impact for the project – 5-10 minutes / slides
Demo presentation of one or more of I-NERGY services (15 mins)
Q&A 15 mins
Researcher and holds a Master in Electrical and Computer Engineerιng and a Master in Data Science and Machine Learning at the National Technical University of Athens. He has been involved and assumed responsibilities and technical task coordination in several ICT and cross-cutting applied research projects including ones under the Horizon 2020 programme. He is experienced in the cybersecurity domain where he has worked on penetration testing as well as cyber-risk assessment and network behaviour simulation using machine learning and deep learning methods, in the context of the project “SPHINX A Universal Cyber Security Toolkit for Health-Care Industry”. He is also experienced in the energy sector as he has conducted extensive research on sustainability and climate change issues at Datagrid company and has performed numerous energy audits. He has also contributed to the development and maintenance of easykenak web application for energy audits (www.easykenak.gr). Currently he is working on artificial intelligence, time series analysis and software engineering concepts in the context of the project “I-NERGY: Artificial Intelligence for Next Generation Energy”. During his career he has mainly focused on the conceptualization and coordination of pilot use cases alongside the development of statistical models, machine learning and deep learning models, and the deployment of relevant applications. He is fluent at programming languages such as Python, R, C and SQL and frameworks such as Docker, Spark and MLflow, constantly enriching his knowledge and skills with modern practices and frameworks. Several results of his work have been published in book chapters and international conference papers.
Master’s degree from the Faculty of Mathematics, University of Belgrade, department: Computer Science. She is enrolled in PhD studies, from 2020 – present, at the Faculty of Technical Sciences, University of Novi Sad, Computing and Control Engineering. She has been working in ENG for more than five years. She has worked on several EU H2020 projects, such as WiseGRID, Waste4Think, Matrycs, FoodRUS, I-NERGY. She has experience working in the energy sector and field of sustainable economies, developing solutions in various technologies.