Dr. Jernej Hribar
- Role: MSCA Fellow
- Joined: October, 2022
- Affiliations: Jožef Stefan Institute
- Research Interests: age of information, reinforcement learning, deep learning, smart grids, and embedded systems.
Jernej Hribar is a Marie Skłodowska-Curie Action Fellow in the Department of Communication Systems since October 2022. His MSCA action - TimeSmart - investigates the applicability of the novel Age of Information metric in smart grids. From 2019-2022, he was a postdoctoral researcher in the CONNECT Centre for Future Networks and Communications at Trinity College Dublin, Ireland. He was involved in an international collaborative project between Trinity College Dublin and Tsinghua University using machine learning techniques to assist future networks with decision-making problems in smart cities. He received an undergraduate degree in electrical engineering from the University of Ljubljana, Slovenia, in 2014 and a Ph.D. from Trinity College Dublin, Ireland, in 2020. His PhD focused on improving the sustainability of large-scale sensor deployments using reinforcement learning and leveraging the freshness of correlated information measured by the Age of Information metric.
Patents:
- Method and System for Energy Aware Scheduling for Sensors: Patent US11762446B2, 2023-09-192023
Publications:
- Metrika Starosti Informacije in Njena Vloga v Vzdržnih Omrežjih PrihodnostiElektrotehniški vestnik online, 2024
- Balancing Energy Preservation and Performance in Energy-Harvesting Sensor NetworksIEEE sensors journal, 2024
- Trajnostni Razvoj Interneta Stvari: Analiza Ogljičnega Odtisa LoRaWAN Omrežij Na Področju SlovenijeŠTeKam: Študentska tehniška konferenca, 2024
- Smart Homes, Smarter Savings: Energy Trading With Deep Reinforcement Learning2024 IEEE 22nd Mediterranean electrotechnical conference (MELECON): 25-27 June 2024, Porto, 2024
- Visibility Graph-Based Wireless Anomaly Detection for Digital Twin Edge NetworksIEEE open journal of the Communications Society, 2024
- Building Zero-Touch Service Management Framework for Automotive Services Using the Smart Highway Testbed2024 7th International Balkan Conference on Communications and Networking (BalkanCom): 3-6 June 2024, Ljubljana, 2024
- Digital Transformation With a Lightweight On-Premise PaaSFuture generation computer systems, 2024
- FedSBS: Federated-Learning Participant-Selection Method for Intrusion Detection SystemsComputer networks: the international journal of computer and telecommunications networking, 2024
- The Energy Cost of Artificial Intelligence of Things Lifecycle2024
- Smart Home Energy Cost Minimisation Using Energy Trading With Deep Reinforcement LearningBuildSys'23: proceedings of the 10th ACM Conference on International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation, 2023
- Electrical Energy Cost Minimization in a Smart Home Using Deep Reinforcement LearningZbornik dvaintridesete mednarodne Elektrotehniške in računalniške konference ERK 2023: Portorož, Slovenija, 28. - 29. september 2023, 2023
- A Survey on Securing Federated Learning: Analysis of Applications, Attacks, Challenges, and TrendsIEEE access, 2023
- Machine Learning Operations Model Store: Optimizing Model Selection for AI as a ServiceBalkanCom 2023, 2023 International Balkan Conference on Communications and Networking (BalkanCom) took place 5-8 June 2023 in İstanbul, Turkey, 2023
- Deep W-Networks: Solving Multi-Objective Optimisation Problems With Deep Reinforcement LearningICAART 2023: proceedings of the 15th International Conference on Agents and Artificial Intelligence, 2023
- Federated Spatial Reuse Optimization in Next-Generation Decentralized IEEE 802.11 WLANSITU journal: future and evolving technologies, 2022
- Timely and Sustainable: Utilising Correlation in Status Updates of Battery-Powered and Energy-Harvesting Sensors Using Deep Reinforcement LearningComputer communications, 2022
- Enabling Deep Reinforcement Learning on Energy Constrained Devices at the Edge of the NetworkIEEE Conference on Wireless Communications and Networking, 10-13, Austin, Texas, Usa, 2022
- Energy Aware Deep Reinforcement Learning Scheduling for Sensors Correlated in Time and SpaceIEEE internet of things journal, 2022
- Federated Spatial Reuse Optimization in Next-Generation Decentralized IEEE 802.11 WLANs2022
- Analyse or Transmit: Utilising Correlation at the Edge With Deep Reinforcement Learning2021 IEEE Global Communications Conference (GLOBECOM), Madrid, Spain 7 - 11 December 2021: proceedings, 2021
- SMART: Situationally-Aware Multi-Agent Reinforcement Learning-Based TransmissionsIEEE transactions on cognitive communications and networking, 2021
- Resource Reservation Within Sliced 5G Networks: A Cost-Reduction Strategy for Service Providers2020 IEEE International Conference on Communications Workshops (ICC): proceedings, 2020
- Utilising Correlated Information to Improve the Sustainability of Internet of Things DevicesWF-IoT: 2019 IEEE 5th World Forum on Internet of Things, 2019
- Using Deep Q-Learning to Prolong the Lifetime of Correlated Internet of Things Devices2019 IEEE International Conference on Communications Workshops, (ICC Workshops): proceedings, 2019
- Using Correlated Information to Extend Device LifetimeIEEE internet of things journal, 2019
- Using Deep Q-Learning to Prolong the Lifetime of Correlated Internet of Things Devices2019
- Updating Strategies in the Internet of Things by Taking Advantage of Correlated SourcesIEEE Globecom: global hub: connecting East and West, 2017