Research Group
Marek Lóderer
Research areas: machine learning, data analysis, time series forecasting, ensemble learning, metaheuristic and nature inspired computation, anomaly detection
Position: AI Specialist
Marek is a researcher and AI Specialist focusing on data analytics for green energy. His core expertise lies in machine learning, ensemble learning, optimization algorithms, and time series forecasting. He applies these methods to solve a variety of microgrid-related problems, with a specific emphasis on prediction, optimization, and anomaly detection in energy consumption. By developing models that simulate power flows incorporating consumers, renewable energy sources, and battery configurations, his work aims to advance sustainable and smart energy management.
Throughout his career, he has prioritized practical, high-impact applied projects and software solutions. He led the creation of the REBUS project, an interactive simulation modeling household energy management. He has also been a key member of several national and international research initiatives, including the V4Grid and NEWTON (H2020) projects. Furthermore, he has practical experience applying ML to real-world problems through industry collaborations, having partnered with ZSE to use machine learning for disaggregating customer consumption profiles, alongside applied R&D projects in cooperation with sféra, ATOS, and Instarea.
Selected activities
- Invited presentation on Metro (ON) AI Line 2023 Conference in Poprad focusing on AI and Smart Cities.
- Attendance at conferences Digitálna Budúcnosť 2025 in a role of eDIH consultant
Selected Projects
Other notable projects
International Centre of Excellence for Research of Intelligent and Secure Information-Communication Technologies and Systems – II. Stage
ITMS 313021W404. Partner: Atos IT Solutions and Services s.r.o. , Rozinajova, V. – principal investigator for FIIT STU until August 2020
International Centre of Excellence for Research of Intelligent and Secure Information-Communication Technologies and Systems
ITMS 26240120039. 2014-2015. Partner: Atos IT Solutions and Services s.r.o., Rozinajova, V. – principal investigator for FIIT STU
Knowledge-Based Approaches for Intelligent Analysis of Big Data
APVV-16-0213. 2017-2021. Partner: Technical University of Kosice (prof. Jan Paralic), Rozinajova, V. – principal investigator for FIIT STU until August 2020
NEWTON – Networked Labs for Training in Sciences and Technologies for Information and Communication
H2020 688503. 2016-2019. Coordinator: Dublin City University, Rozinajova, V. – principal investigator for FIIT STU
Optimization in Microgrid
Slovak University of Technology in Bratislava – Grant scheme to support excellent teams of young researchers. 2019-2021. Loderer, M. – principal investigator
Selected Publications
Selected Student Supervising
Master
- Gemeľa Juraj – Detection of non-standard customer behavior in the power grid. Defended 2021
- Kubík Dávid – Optimization of power load consumption in microgrids. Defended 2020
- Vidiečanová Dominika – Optimization of power load consumption using high-capacity batteries. Defended 2020
- Cuper Matúš – Identification of abnormal behavior of customers in the power grid. Defended 2019
- Matula Marek – Prediction of electricity consumption by ensemble learning. Defended 2018
- Halaš Peter – Prediction of electricity consumption using biologically inspired algorithms. Defended 2017
Bachelor
- Bubán Michal – Biologically inspired algorithm in R language. Defended 2020
- Fano Adam – Biologically inspired algorithm in R programming language. Defended 2020
- Šoltés Pavol – Biologically inspired algorithm in R language. Defended 2019
- Cuper Matúš – Optimizing configuration parameters of prediction methods. Defended 2017
- Cvíčela Martin – Electric load forecast including external factors. Defended 2016