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.

Publications:

• A Survey on Securing Federated Learning: Analysis of Applications, Attacks, Challenges, and Trends
  Helio N. Cunha Neto, Jernej Hribar, Ivana Dusparič, Diogo Menezes Ferrazani Mattos, and Natalia C. Fernandes
  IEEE access, 2023
  • COBISS: 159983619
  • DOI: 10.1109/ACCESS.2023.3269980
• Machine Learning Operations Model Store: Optimizing Model Selection for AI as a Service
  Gregor Cerar, and Jernej Hribar
  BalkanCom 2023, 2023 International Balkan Conference on Communications and Networking (BalkanCom) took place 5-8 June 2023 in İstanbul, Turkey, 2023
  • COBISS: 158333187
  • DOI: 10.1109/BalkanCom58402.2023.10167931
• Deep W-Networks: Solving Multi-Objective Optimisation Problems With Deep Reinforcement Learning
  Jernej Hribar, Luke Hackett, and Ivana Dusparič
  ICAART 2023: proceedings of the 15th International Conference on Agents and Artificial Intelligence, 2023
  • COBISS: 145125123
  • DOI: 10.5220/0011610300003393
  • arXiv:2211.04813v2
• Federated Spatial Reuse Optimization in Next-Generation Decentralized IEEE 802.11 WLANS
  Francesc Wilhelmi, and Jernej Hribar
  ITU journal: future and evolving technologies, 2022
  • COBISS: 127025155
  • DOI: 10.52953/TNYT6291
• Timely and Sustainable: Utilising Correlation in Status Updates of Battery-Powered and Energy-Harvesting Sensors Using Deep Reinforcement Learning
  Jernej Hribar, Luiz A. DaSilva, Sheng Zhou, Jiang Zhiyuan, and Ivana Dusparič
  Computer communications, 2022
  • COBISS: 126791683
  • DOI: 10.1016/j.comcom.2022.05.030
• Enabling Deep Reinforcement Learning on Energy Constrained Devices at the Edge of the Network
  Jernej Hribar, and Ivana Dusparič
  IEEE Conference on Wireless Communications and Networking, 10-13, Austin, Texas, Usa, 2022
  • COBISS: 126776835
  • DOI: 10.1109/WCNC51071.2022.9771901
  • arXiv:2201.07308v1
• Energy Aware Deep Reinforcement Learning Scheduling for Sensors Correlated in Time and Space
  Jernej Hribar, Andrei Marinescu, Alessandro Chiumento, and Luiz A. DaSilva
  IEEE internet of things journal, 2022
  • COBISS: 97757187
  • DOI: 10.1109/JIOT.2021.3114102
  • arXiv:2011.09747v2
• Federated Spatial Reuse Optimization in Next-Generation Decentralized IEEE 802.11 WLANs
  Francesc Wilhelmi, Jernej Hribar, Selim F. Yilmaz, Emre Ozfatura, Kerem Ozfatura, Ozlem Yildiz, Deniz Gündüz, Hao Chen, Xiaoying Ye, Lizhao You, Yulin Shao, Paolo Dini, and Boris Bellalta
  • arXiv:2203.10472v2
• Analyse or Transmit: Utilising Correlation at the Edge With Deep Reinforcement Learning
  Jernej Hribar, Ryoichi Shinkuma, Geogre Iosifidis, and Ivana Dusparič
  2021 IEEE Global Communications Conference (GLOBECOM), Madrid, Spain 7 - 11 December 2021: proceedings, 2021
  • COBISS: 98959875
• SMART: Situationally-Aware Multi-Agent Reinforcement Learning-Based Transmissions
  Jiang Zhiyuan, Yan Liu, Jernej Hribar, Luiz A. DaSilva, Sheng Zhou, and Zhisheng Niu
  IEEE transactions on cognitive communications and networking, 2021
  • COBISS: 97766915
  • DOI: 10.1109/TCCN.2021.3068740
• Resource Reservation Within Sliced 5G Networks: A Cost-Reduction Strategy for Service Providers
  Jean-Baptiste Monteil, Jernej Hribar, Pieter Barnard, Yong Li, and Luiz A. DaSilva
  2020 IEEE International Conference on Communications Workshops (ICC): proceedings, 2020
  • COBISS: 97818627
  • DOI: 10.1109/ICCWorkshops49005.2020.9145374
• Utilising Correlated Information to Improve the Sustainability of Internet of Things Devices
  Jernej Hribar, and Luiz A. DaSilva
  WF-IoT: 2019 IEEE 5th World Forum on Internet of Things, 2019
  • COBISS: 97896963
• Using Deep Q-Learning to Prolong the Lifetime of Correlated Internet of Things Devices
  Jernej Hribar, Andrei Marinescu, George A. Ropokis, and Luiz A. DaSilva
  2019 IEEE International Conference on Communications Workshops, (ICC Workshops): proceedings, 2019
  • COBISS: 97883139
  • DOI: 10.1109/ICCW.2019.8756759
• Using Correlated Information to Extend Device Lifetime
  Jernej Hribar, Maice Costa, Nicholas Kaminski, and Luiz A. DaSilva
  IEEE internet of things journal, 2019
  • COBISS: 97766659
  • DOI: 10.1109/JIOT.2018.2869986
• Using Deep Q-Learning to Prolong the Lifetime of Correlated Internet of Things Devices
  Jernej Hribar, Andrei Marinescu, George A. Ropokis, and Luiz A. DaSilva
  • arXiv:1902.02850v1
• Updating Strategies in the Internet of Things by Taking Advantage of Correlated Sources
  Jernej Hribar, Maice Costa, Nicholas Kaminski, and Luiz A. DaSilva
  IEEE Globecom: global hub: connecting East and West, 2017
  • COBISS: 97898499