Dr. Mingming Liu is a tenured Assistant Professor in the School of Electronic Engineering at Dublin City University (DCU).
Mingming was a data scientist, applied researcher, and H2020 project lead (5G-Solutions) at IBM Ireland Lab, where the main focus of his work was to leverage the state-of-the-art machine learning and applied optimisation techniques for practical and challenging problems arising in the industry. Before IBM, he worked at University College Dublin as a (senior) postdoctoral research fellow with the Control Engineering and Decision Science Research Group within the School of Electrical and Electronic Engineering. He spent almost three years working on both EU and SFI funded projects at UCD, including Green Transportation and Networks (SFI) and Enable-S3 (H2020), with strong collaborations with both academia and industrial partners.
He received his B.Eng. degree with first class honours (ranked 1st) from the Department of Electronic Engineering at the National University of Ireland Maynooth in 2011, and then his PhD from the Hamilton Institute at the same university in 2015 (26 years old). His PhD thesis entitled “Topics in Electromobility and Related Applications” was supervised by Prof Robert Shorten (Full Professor at Imperial College London) and Prof Sean McLoone (Full Professor at Queen’s University Belfast).
He is an IEEE Senior Member. He has published over 60 papers to date including top-tier journals such as “IEEE Transactions on Smart Grid”, “IEEE Transactions on Intelligent Transportation System”, “IEEE Transactions on Automation Science and Engineering”, “IEEE System Journal”, “IEEE Transactions on Transportation Electrification”， “IEEE Transactions on Artificial Intelligence”, “Sustainable Cities and Society”, “Pattern Recognition”, “Applied Energy” and “Automatica”. He acts as an academic editor for PLOS ONE and an associate editor for the Journal of Information Systems and Operational Research (INFOR).
Since 2018, he has secured more than 2.5 million euros in research funding from various sources as the independent PI. At present, he is one of the three awardees at DCU of the prestigious SFI Frontiers for the Future Programme in 2021. He has actively participated in many academic activities, including technical committees, organisation committees and management committees at both national and international levels. He is the management committee member for Ireland in the EU COST Action CA19126, CA20138 and CA21131.
Please visit my personal website https://mingmingliu.net for more information about my research works.
Book Chapter
| Year | Publication | |
|---|---|---|
| 2025 | Wu, H., Yan, S. and Liu, M. (2025) 'Recent Advances in Graph-based Machine Learning for Applications in Smart Urban Transportation Systems' In: Next Generation Cities: An Encyclopedia: Volume 4: Pathways to Urban Transformation. Canada : World Scientific Publishing. [DOI] | |
| 2024 | Li, J., Liu, M., Wang, C., Gu, Y., Zhou, Q., Wen, C., Pham, D.T. and Xu, H. (2024) 'Pedestrian-Aware Cyber-Physical Optimisation of Hybrid Propulsion Systems Using a Fuzzy Adaptive Cost Map and Bees Algorithm' In: In Intelligent Engineering Optimisation with the Bees Algorithm (pp. 367-392). Germany : Springer Nature. [DOI] | |
| 2023 | Carlos Muli; Sangyoung Park; Mingming Liu (2023) 'A Comparative Study on Energy Consumption Models for Drones' In: Lecture Notes in Computer Science book series (LNCS,volume 13533). Switzerland : Springer. [DOI] | |
| 2017 | Gu, Y. and Liu, M. (2017) 'Smart procurement of naturally generated energy (SPONGE)' In: Electric and Plug-in Hybrid Vehicle Networks. Boca Raton : CRC Press. [DOI] | |
| 2013 | Liu M.; McLoone S. (2013) 'Investigation of AIMD based charging strategies for EVs connected to a low-voltage distribution network' In: Communications in Computer and Information Science. [DOI] |
Peer Reviewed Journal
| Year | Publication | |
|---|---|---|
| 2025 | Zhu, J., Cai, W., Zhang, M., Lin, Y. and Liu, M. (2025) 'Saliency detection for underwater moving object with sonar based on motion estimation and multi-trajectory analysis'. Pattern Recognition, . [DOI] | |
| 2024 | Yan, S., Fang, H., Li, J., Ward, T., O’Connor, N. and Liu, M. (2024) 'U-Park: A User-Centric Smart Parking Recommendation System for Electric Shared Micromobility Services'. IEEE Transactions on Artificial Intelligence, . [DOI] | |
| 2024 | Gohari, S., Silvia, S.C., Ashrafian, T., Konstantinou, T., Giancola, E., Prebreza, B., Aelenei, L., Murauskaite, L. and Liu, M. (2024) 'Unraveling the Implementation Processes of PEDs: lesson learned from multiple urban contexts'. Sustainable Cities and Society, . [DOI] | |
| 2024 | Zhang, Y., Li, Q., Wen, C., Liu, M., Yang, X., Xu, H. and Li, J., (2024) 'Predictive equivalent consumption minimization strategy based on driving pattern personalized reconstruction'. Applied Energy, . [DOI] | |
| 2023 | Yan, S., Fang, H., Li, J., Ward, T., O’Connor, N. and Liu, M. (2023) 'Privacy-Aware Energy Consumption Modeling of Connected Battery Electric Vehicles using Federated Learning'. IEEE Transactions on Transportation Electrification, . [DOI] | |
| 2023 | Dey-Plissonneau, A., Soler, I.G., Lee, H., Liu, M., Scriney, M. and Smeaton, A. (2023) 'Supporting second language learner reflection in teletandem videoconferencing through the visualisation of conversation metrics'. Journal of Virtual Exchange, . [DOI] | |
| 2022 | Wu, H., O’Connor, N.E., Bruton, J., Hall, A. and Liu, M. (2022) 'Real-Time Anomaly Detection for an ADMM-Based Optimal Transmission Frequency Management System for IoT Devices'. Sensors, . [Link] [DOI] | |
| 2022 | Li, Ji; Gu, Yingqi; Wang, Chongming; Liu, Mingming; Zhou, Quan; Lu, Guoxiang; Pham, Duc Truong; Xu, Hongming (2022) 'Pedestrian-Aware Supervisory Control System Interactive Optimization of Connected Hybrid Electric Vehicles via Fuzzy Adaptive Cost Map and Bees Algorithm'. IEEE Transactions on Transportation Electrification, 8 (2). [DOI] | |
| 2022 | Hoa Xuan Nguyen; Shaoshu Zhu; Mingming Liu (2022) 'A Survey on Graph Neural Networks for Microservice-Based Cloud Applications'. Sensors, . [DOI] | |
| 2022 | Liu, M.; Cheng, L.; Gu, Y.; Wang, Y.; Liu, Q.; O'Connor, N.E. (2022) 'MPC-CSAS: Multi-Party Computation for Real-Time Privacy-Preserving Speed Advisory Systems'. IEEE Transactions on Intelligent Transportation Systems, 23 . [Link] [DOI] | |
| 2022 | Lee, H., Liu, M., Scriney, M. and Smeaton, A.F. (2022) 'Playback-centric visualizations of video usage using weighted interactions to guide where to watch in an educational context'. Frontiers in Education, 7 . [DOI] | |
| 2021 | Gu, Y.; Liu, M. (2021) 'Fair and Privacy-Aware EV Discharging Strategy Using Decentralized Whale Optimization Algorithm for Minimizing Cost of EVs and the EV Aggregator'. IEEE Systems Journal, 15 . [Link] [DOI] | |
| 2021 | Gu, Y.; Zalkikar, A.; Liu, M.; Kelly, L.; Hall, A.; Daly, K.; Ward, T. (2021) 'Predicting medication adherence using ensemble learning and deep learning models with large scale healthcare data'. Scientific Reports, 11 . [Link] [DOI] | |
| 2021 | Krangsås, S.G.; Steemers, K.; Konstantinou, T.; Soutullo, S.; Liu, M.; Giancola, E.; Prebreza, B.; Ashrafian, T.; Murauskaitė, L.; Maas, N. (2021) 'Positive energy districts: Identifying challenges and interdependencies'. Sustainability (Switzerland), 13 . [Link] [DOI] | |
| 2019 | Liu M.; Naoum-Sawaya J.; Gu Y.; Lecue F.; Shorten R. (2019) 'A distributed markovian parking assist system'. IEEE Transactions on Intelligent Transportation Systems, 20 (6):2230-2240. [DOI] | |
| 2018 | Herrmann A.; Liu M.; Pilla F.; Shorten R. (2018) 'A new take on protecting cyclists in smart cities'. IEEE Transactions on Intelligent Transportation Systems, 19 (12):3992-3999. [DOI] | |
| 2018 | Gu Y.; Liu M.; Naoum-Sawaya J.; Crisostomi E.; Russo G.; Shorten R. (2018) 'Pedestrian-Aware Engine Management Strategies for Plug-In Hybrid Electric Vehicles'. IEEE Transactions on Intelligent Transportation Systems, 19 (1):92-101. [DOI] | |
| 2017 | Naoum-Sawaya J.; Crisostomi E.; Liu M.; Gu Y.; Shorten R. (2017) 'Smart Procurement of Naturally Generated Energy (SPONGE) for Plug-In Hybrid Electric Buses'. IEEE Transactions on Automation Science and Engineering, 14 (2):598-607. [DOI] | |
| 2017 | Liu M.; Wirth F.; Corless M.; Shorten R. (2017) 'On the stability and convergence of a class of consensus systems with a nonlinear input'. Automatica, 86 :205-211. [DOI] | |
| 2016 | Liu M.; Ordóñez-Hurtado R.H.; Wirth F.; Gu Y.; Crisostomi E.; Shorten R. (2016) 'A Distributed and Privacy-Aware Speed Advisory System for Optimizing Conventional and Electric Vehicle Networks'. IEEE Transactions on Intelligent Transportation Systems, 17 (5):1308-1318. [DOI] | |
| 2015 | Liu M.; McNamara P.; Shorten R.; McLoone S. (2015) 'Residential electrical vehicle charging strategies: the good, the bad and the ugly'. Journal Of Modern Power Systems And Clean Energy, 3 (2):190-202. [DOI] | |
| 2015 | Liu, M.; McLoone, S. (2015) 'Enhanced AIMD-based decentralized residential charging of EVs'. Transactions of the Institute of Measurement and Control, . [DOI] | |
| 2014 | Crisostomi E.; Liu M.; Raugi M.; Shorten R. (2014) 'Plug-and-play distributed algorithms for optimized power generation in a microgrid'. IEEE Transactions on Smart Grid, 5 (4):2145-2154. [DOI] |
Conference Publication
| Year | Publication | |
|---|---|---|
| 2025 | Yan, S., O'Connor, D.J., Wang, X., O'Connor, N.E., Smeaton, A.F. and Liu, M. (2025) 2025 IEEE Symposium Series on Computational Intelligence Comparative Analysis of Machine Learning-Based Imputation Techniques for Air Quality Datasets with High Missing Data Rates | |
| 2025 | Kaundanya, C., Cesar, P., Cronin, B., Fleury, A., Liu, M. and Little, S. (2025) 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and App Enhancing Small Object Detection in Resource-Constrained ARAS Using Image Cropping and Slicing Techniques | |
| 2025 | Shah, M.H., Li, J. and Liu, M. (2025) 2025 IEEE Symposium Series on Computational Intelligence On Scalable Design for User-Centric Multi-Modal Shared E-Mobility Systems using MILP and Modified Dijkstra | |
| 2025 | Yu, M., O’Shea, K., Li, Y., Yan, S. and Liu, M. (2025) 2025 IEEE International Joint Conference on Neural Networks (IJCNN) A Comparative Study of Graph-Based Learning Methods for Multivariate Time-Series Anomaly Detection in Cloud Microservice Applications | |
| 2024 | Ding, Y., Yan, S., Shah, M.H., Fang, H., Li, J. and Liu, M. (2024) 2024 IEEE Transportation Electrification Conference & Expo Data-driven Energy Consumption Modelling for Electric Micromobility using an Open Dataset [DOI] | |
| 2024 | Allam, M., Boujnah, N., O’Connor, N.E. and Liu, M. (2024) 10th International Conference, LOD 2024 Synthetic Time Series for Anomaly Detection in Cloud Microservices [DOI] | |
| 2024 | Chiumento, F. and Liu, M. (2024) 2024 IEEE International Conference on Big Data (BigData) Leveraging Multimodal Models for Enhanced Neuroimaging Diagnostics in Alzheimer’s Disease [DOI] | |
| 2024 | Shah, M.H., Dang, X. and Liu, M. (2024) 2024 IEEE 12th International Conference on Intelligent Systems (IS) Hierarchical Tree of Deep Networks (HTDN) for Joint Classification of Linear and Non-Linear Modulations [DOI] | |
| 2024 | Kaundanya, C., Cesar, P., Cronin, B., Fleury, A., Liu, M. and Little, S. (2024) VEHITS Using Attention Mechanisms in Compact CNN Models for Improved Micromobility Safety Through Lane Recognition [DOI] | |
| 2023 | Yan, S., Zhu, S., Fernandez, J.B., Sánchez, E.A., Gu, Y., O (2023) 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC) Breathing Green: Maximising Health and Environmental Benefits for Active Transportation Users Leveraging Large Scale Air Quality Data [DOI] | |
| 2023 | Yan, S., Shah, M.H., Li, J., O’Connor, N. and Liu, M. (2023) 2023 7th CAA International Conference on Vehicular Control and Intelligence (CVCI) A Review on AI Algorithms for Energy Management in E-Mobility Services [DOI] | |
| 2022 | Aparajita Dey-Plissonneau; Hyowon Lee; Mingming Liu; Vyoma Patel; Michael Scriney; Alan F Smeaton (2022) 8th International Conference on Higher Education Advances (HEAd'2022) An Analysis of Conversational Volatility During Telecollaboration Sessions for Second Language Learning [DOI] | |
| 2022 | Hoa X. Nguyen; Shaoshu Zhu; Mingming Liu (2022) 2022 IEEE 11th International Conference on Cloud Networking (CloudNet) Graph-PHPA: Graph-based Proactive Horizontal Pod Autoscaling for Microservices using LSTM-GNN [DOI] | |
| 2022 | Koen Steemers; Savis Gohari Krangsås; Touraj Ashrafian; Emanuela Giancola; Thaleia Konstantinou; Mingming Liu; Nienke Maas; Lina Murauskaitė; Bahri Prebreza; Silvia Soutullo (2022) Sustainability in Energy and Buildings: Research Advances Challenges for a Positive Energy District Framework [DOI] | |
| 2022 | Alan F. Smeaton; Aparajita Dey-Plissonneau; Hyowon Lee; Mingming Liu; Michael Scriney (2022) Proceedings of 21st European Conference on e-Learning ECEL. 21(1). Academic Conferences Ltd.. ISBN 9 Analysis of Individual Conversational Volatility in Tandem Telecollaboration for Second Language Learning [DOI] | |
| 2022 | Wu, Hongde; Liu, Mingming (2022) 2022 IEEE 25TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC) Lane-GNN: Integrating GNN for Predicting Drivers' Lane Change Intention [DOI] | |
| 2022 | Sen Yan; Mingming Liu; Noel E O (2022) IEEE 95th Vehicular Technology Conference (IEEE VTC2022-Spring) Parking Behaviour Analysis of Shared E-Bike Users Based on a Real-World Dataset--A Case Study in Dublin, Ireland [DOI] | |
| 2021 | Wu, H.; O'Connor, N.E.; Bruton, J.; Liu, M. (2021) 7th IEEE World Forum on Internet of Things, WF-IoT 2021 An ADMM-based Optimal Transmission Frequency Management System for IoT Edge Intelligence [Link] [DOI] | |
| 2021 | Lee, Hyowon; Liu, Mingming; Scriney, Michael; Smeaton, Alan F. (2021) Usage-Based Summaries of Learning Videos [DOI] | |
| 2021 | H. Lee, M. Liu, H. Riaz, N. Rajasekaren, M. Scriney, A. F Smeaton (2021) AAAI-2021 Workshop on AI Education: Imagining Post-COVID Education with AI (TIPCE-2021) Attention Based Video Summaries of Live Online Zoom Classes [Link] | |
| 2021 | Chen, Z.; Wu, H.; O'Connor, N.E.; Liu, M. (2021) A Comparative Study of Using Spatial-Temporal Graph Convolutional Networks for Predicting Availability in Bike Sharing Schemes [Link] [DOI] | |
| 2021 | Wu, H.; Chen, Z.; O'Connor, N.E.; Liu, M. (2021) IoTDI 2021 - Proceedings of the 2021 International Conference on Internet-of-Things Design and Implementation Optimal Distributed Bandwidth Allocation in NB-IoT Networks: Poster Abstract [Link] [DOI] | |
| 2021 | Liu, M. (2021) Fed-BEV: A Federated Learning Framework for Modelling Energy Consumption of Battery Electric Vehicles [Link] [DOI] | |
| 2021 | Chen, Beiran; Liu, Mingming; Zhang, Yi; Chent, Zhengyong; Gu, Yingqi; O'Connor, Noel E. (2021) 2021 IEEE 93RD VEHICULAR TECHNOLOGY CONFERENCE (VTC2021-SPRING) An Intelligent Multi-Speed Advisory System using Improved Whale Optimisation Algorithm [DOI] | |
| 2020 | Chen, B.; Zhang, Y.; Iosifidis, G.; Liu, M. (2020) IEEE World Forum on Internet of Things, WF-IoT 2020 - Symposium Proceedings Reinforcement Learning on Computational Resource Allocation of Cloud-based Wireless Networks [Link] [DOI] | |
| 2020 | Murthy, R.D.; Liu, M. (2020) 2020 IEEE Global Conference on Artificial Intelligence and Internet of Things, GCAIoT 2020 An Elastic IoT Device Management Platform [Link] [DOI] | |
| 2018 | Gu Y.; Crisostomi E.; Liu M.; Shorten R. (2018) 2018 IEEE Conference on Control Technology and Applications, CCTA 2018 Identification of New Patterns in Urban Traffic Flows [DOI] | |
| 2018 | Epperlein J.P.; Monteil J.; Liu M.; Gu Y.; Zhuk S.; Shorten R. (2018) IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC Bayesian classifier for Route prediction with Markov chains [DOI] | |
| 2018 | Gu Y.; Liu M.; Souza M.; Shorten R. (2018) IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC On the Design of an Intelligent Speed Advisory System for Cyclists [DOI] | |
| 2016 | Liu M.; Ordóñez-Hurtado R.H.; Wirth F.R.; Gu Y.; Crisostomi E.; Shorten R. (2016) 2015 International Conference on Connected Vehicles and Expo, ICCVE 2015 - Proceedings An intelligent speed advisory system for electric vehicles [DOI] | |
| 2014 | Mingming Liu; Emanuele Crisostomi; Yingqi Gu; Robert Shorten (2014) 2014 IEEE International Electric Vehicle Conference (IEVC) Optimal distributed consensus algorithm for fair V2G power dispatch in a microgrid [DOI] | |
| 2014 | Yingqi Gu; Mingming Liu; Emanuele Crisostomi; Robert Shorten (2014) 2014 International Conference on Connected Vehicles and Expo (ICCVE) Optimised consensus for highway speed limits via intelligent speed advisory systems [DOI] | |
| 2014 | Mingming Liu; Paul McNamara; Robert Shorten; Sean McLoone (2014) Proceedings of the 19th World Congress The International Federation of Automatic Control Distributed Consensus Charging for Current Unbalance Reduction [DOI] | |
| 2013 | Liu M.; McLoone S.; Studli S.; Middleton R.; Shorten R.; Braslavs J. (2013) Asia-Pacific Power and Energy Engineering Conference, APPEEC On-off based charging strategies for EVs connected to a Low Voltage distributon network [DOI] | |
| 2013 | Liu M.; Griggs W.; King C.; Wirth F.; Borrel P.; Shorten R. (2013) 2013 International Conference on Connected Vehicles and Expo, ICCVE 2013 - Proceedings Applying a QoS-based fleet dimension method to reduce fleet emissions [DOI] | |
| 2013 | Liu M.; Crisostomi E.; Raugi M.; Shorten R. (2013) 2013 4th IEEE/PES Innovative Smart Grid Technologies Europe, ISGT Europe 2013 Optimal distributed power generation for thermal and electrical scheduling in a microgrid [DOI] | |
| 2013 | Liu M.; McNamara P.; McLoone S. (2013) 2013 4th IEEE/PES Innovative Smart Grid Technologies Europe, ISGT Europe 2013 Fair charging strategies for EVs connected to a low-voltage distribution network [DOI] |
Certain data included herein are derived from the © Web of Science (2025) of Clarivate. All rights reserved.
Research Interests
Machine Learning, Deep Learning, Reinforcement Learning, Federated Learning, Data Science, Distributed Control, Mathematical Modelling, Convex Optimisation, IoT, Linear and Nonlinear Dynamical Systems, Edge Computing, Fog Computing, Cloud Computing, Electric Vehicles, Smart Grids, Intelligent Transportation Systems, Smart Healthcare, Smart Cities
Teaching Interests
Machine Learning, Deep Learning, System and Control, Applied Optimisation, Mathematical Modelling, Data Science, IoT, Electric Vehicles, Smart Grids, Smart Transportation