| 2026 | SEAMS | Balancing Multiple Objectives in Urban Traffic Control with Reinforcement Learning from AI Feedback. | Chenyang Zhao, Vinny Cahill, Ivana Dusparic |
| 2025 | ECAI | Optimistic Exploration for Risk-Averse Constrained Reinforcement Learning. | James McCarthy, Radu Marinescu, Elizabeth Daly, Ivana Dusparic |
| 2025 | ICLR | Drama: Mamba-Enabled Model-Based Reinforcement Learning Is Sample and Parameter Efficient. | Wenlong Wang, Ivana Dusparic, Yucheng Shi, Ke Zhang, Vinny Cahill |
| 2024 | HAI | Semifactual Explanations for Reinforcement Learning. | Jasmina Gajcin, Jovan Jeromela, Ivana Dusparic |
| 2024 | IROS | Applying Neural Monte Carlo Tree Search to Unsignalized Multi-intersection Scheduling for Autonomous Vehicles. | Yucheng Shi, Wenlong Wang, Xiaowen Tao, Ivana Dusparic, Vinny Cahill |
| 2024 | SEAMS | Learning Recovery Strategies for Dynamic Self-healing in Reactive Systems. | Mateo Sanabria, Ivana Dusparic, Nicols Cardozo |
| 2023 | CAIN | Prevalence of Code Smells in Reinforcement Learning Projects. | Nicols Cardozo, Ivana Dusparic, Christian Cabrera |
| 2023 | ECAI | Expert-Free Online Transfer Learning in Multi-Agent Reinforcement Learning. | Alberto Castagna, Ivana Dusparic |
| 2023 | ECAI | Iterative Reward Shaping Using Human Feedback for Correcting Reward Misspecification. | Jasmina Gajcin, James McCarthy, Rahul Nair, Radu Marinescu, Elizabeth Daly, Ivana Dusparic |
| 2023 | ICAART | Deep W-Networks: Solving Multi-Objective Optimisation Problems with Deep Reinforcement Learning. | Jernej Hribar, Luke Hackett, Ivana Dusparic |
| 2023 | WiMob | Density-Aware Reinforcement Learning to Optimise Energy Efficiency in UAV-Assisted Networks. | Babatunji Omoniwa, Boris Galkin, Ivana Dusparic |
| 2022 | ICAART | Multi-agent Transfer Learning in Reinforcement Learning-based Ride-sharing Systems. | Alberto Castagna, Ivana Dusparic |
| 2022 | NetSoft | FedSA: Accelerating Intrusion Detection in Collaborative Environments with Federated Simulated Annealing. | Hlio N. Cunha Neto, Ivana Dusparic, Diogo M. F. Mattos, Natalia Castro Fernandes |
| 2022 | WCNC | Enabling Deep Reinforcement Learning on Energy Constrained Devices at the Edge of the Network. | Jernej Hribar, Ivana Dusparic |
| 2021 | GLOBECOM | Analyse or Transmit: Utilising Correlation at the Edge with Deep Reinforcement Learning. | Jernej Hribar, Ryoichi Shinkuma, George Iosifidis, Ivana Dusparic |
| 2021 | SEAMS | Adaptation to Unknown Situations as the Holy Grail of Learning-Based Self-Adaptive Systems: Research Directions. | Nicols Cardozo, Ivana Dusparic |
| 2020 | ECAI | Demand-Responsive Zone Generation for Real-Time Vehicle Rebalancing in Ride-Sharing Fleets. | Alberto Castagna, Maxime Guriau, Giuseppe Vizzari, Ivana Dusparic |
| 2020 | ECAI | Emerging Micro-Communities for Ride-Sharing Enabled Mobility-on-Demand Systems. | Baudouin Dafflon, Maxime Guriau, Yacine Ouzrout, Ivana Dusparic |
| 2020 | ICSE | Learning run-time compositions of interacting adaptations. | Nicols Cardozo, Ivana Dusparic |
| 2020 | ICSE | Does Neuron Coverage Matter for Deep Reinforcement Learning?: A Preliminary Study. | Miller Trujillo, Mario Linares-Vsquez, Camilo Escobar-Velsquez, Ivana Dusparic, Nicols Cardozo |
| 2019 | IJCNN | Parallel Transfer Learning in Multi-Agent Systems: What, when and how to transfer? | Adam Taylor, Ivana Dusparic, Maxime Guriau, Siobhn Clarke |
| 2019 | ICTAI | Variational Policy Chaining for Lifelong Reinforcement Learning. | Christopher Doyle, Maxime Guriau, Ivana Dusparic |
| 2019 | WiMob | An RL-based Approach to Improve Communication Performance and Energy Utilization in Fog-based IoT. | Babatunji Omoniwa, Maxime Guriau, Ivana Dusparic |
| 2017 | ECOOP | Peace COrP: learning to solve conflicts between contexts. | Nicols Cardozo, Ivana Dusparic, Jorge H. Castro |
| 2014 | IJCNN | A dynamic forecasting method for small scale residential electrical demand. | Andrei Marinescu, Ivana Dusparic, Colin Harris, Vinny Cahill, Siobhn Clarke |
| 2014 | IJCNN | Accelerating Learning in multi-objective systems through Transfer Learning. | Adam Taylor, Ivana Dusparic, Edgar Galvn Lpez, Siobhn Clarke, Vinny Cahill |
| 2013 | ICSE | Residential electrical demand forecasting in very small scale: An evaluation of forecasting methods. | Andrei Marinescu, Colin Harris, Ivana Dusparic, Siobhn Clarke, Vinny Cahill |
| 2009 | ATC | Using Reinforcement Learning for Multi-policy Optimization in Decentralized Autonomic Systems - An Experimental Evaluation. | Ivana Dusparic, Vinny Cahill |
| 2007 | ICSE | Research Issues in Multiple Policy Optimization Using Collaborative Reinforcement Learning. | Ivana Dusparic, Vinny Cahill |