Dr Christos Anagnostopoulos
- Reader (Computing Science)
telephone:
01413307252
email:
Christos.Anagnostopoulos@glasgow.ac.uk
pronouns:
He/him/his
Office S114, School of Computing Science, Sir Alwyn Williams Building, University of Glasgow, G12 8QQ
Biography
I am an Associate Professor (Reader) in Distributed Computing & Data Engineering Systems and Director of the MSc Information Technology and MSc Software Development Programmes, School of Computing Science. My research expertise is at the intersection of large-scale Distributed Computing, Distributed AI/ML, and Data-centric AI. I have received funding for my research by the EC/H2020, EU Horizon, UK EPSRC and the industry. I am an author of over 180 scientific journals and conferences [scholar]. I am leading the Knowledge and Data Engineering Systems Group (IDA Section). I am Editor in Chief of the Open Computer Science (De Gruyter) and Associate Editor of IEEE Access. I serve as the General Chair of the IEEE ICDCS 2025. I am currently the PI/Technical Coordinator of the EU Horizon grants TRACE, COIN-3D, ELLIE, and TERRA. I am an associate fellow of the HEA and professional member of ACM, IEEE and IEEE STC.
Before joining Glasgow, I was an Assistant Professor (Lecturer) at Ionian University and University of Athens. I have been a MSCA Fellowship Supervisor in University of Glasgow (2018-2020) and have held a Research Fellowship at University of Glasgow (2015-2018) in the area of large-scale distributed computing. I hold a BSc Hons. (Valedictorian) in Computer Science & Telecommunications, MSc (Distinction) in Advanced Computing Systems, and PhD in Computing Science, University of Athens (2008).
Visit KDES Group for more information.
Research interests
Research Statement
My interests and contributions are at the intersection of large-scale distributed computing, distributed AI/ML, and data-centric AI (KDES Group). Throughout my career, I have been conducting research in Distributed Computing for Machine Learning, Federated Learning, in-network Data Management, on-line Stochastic Optimization, Epidemical-based Data Dissemination, and Decentralized Predictive Analytics. Currently, I have established theorerical and analytical models & algorithms for distributed data management and distributed ML/AI. I have published extensively in top journals (including ACM TKDD, ACM TIST, ACM TOIT, ACM TOSN, ACM Comput. Surv., IEEE TMC, IEEE TKDE) and conferences in the above areas (including KDD, ICDE, ICDCS, ICDM, ACML, BigData). I am an associate fellow of the HEA, member of ACM and IEEE member of IEEE Special Technical Community (Smart and Circular Cities).
I am Editor in Chief of the Open Computer Science (De Gruyter) and Associate Editor of IEEE Access. I serve as the General Chair of the IEEE ICDCS 2025.
Google Scholar: [citations]; DBLP [link]; ORCID [link]; ResearchGate [link]
Research Group
KDES Group: Knowledge & Data Engineering Systems.
Funded Projects
[*] EU Horizon: An Intelligent platform for integrating climate services (TERRA); 2025-2028, PI: Dr C Anagnostopoulos, Co-Is: Dr Z Gao, Dr M Hurst
According to Water Europe statistics, 90% of the global economy and 75% of jobs depend on water, while water-related risks are among the top 5 risks. Τhe term “water” includes both drinkable water (with respect to pollution) and hydrology water modelling (with respect to floods and sea level rise). As a result, the significance of modelling techniques, especially regarding water pollution, coastline management, flood prediction and sea level rise assessment cannot be overstated. TERRA envisions the creation of services and product chains that fuse Copernicus services with Digital Twins and AI technologies to provide solutions for coastline detection, coastline erosion prediction, flood risk assessment and mitigation, water pollution assessment and coastline modelling. TERRA provides the framework to promote its outcomes through the Global Earth Observation System of Systems (GEOSS).
[*] EU Horizon: On the use of Internet of Senses for the Cultural Heritage (ELLIE); 2025-2028, PI: Dr C Anagnostopoulos.
ELLIE research examines the impact of emerging technologies on creative processes, particularly in terms of technological advancements and innovation. Artificial Intelligence (AI), Generative AI, Internet of Senses and Digital Twins (DTs) are key technologies frequently explored in this context. ELLIE leverages these technologies within a virtual immersive world creating an innovative platform that opens up opportunities for novel services in the Cultural and Creative Industries (CCIs) domain.
[*] EU Horizon: Collaborative Innovation in 3D VLSI Reliability (COIN-3D); 2024-2027. PI: Dr C Anagnostopoulos.
COIN-3D fosters strategic networking and knowledge exchange between leading European research institutions to enhance research management and commercialization capacities in the area of 2.5/3D chiplet architectures. The main target of the COIN-3D project is to enhance the AI research capacity of an entity being active in a widening country with the assistance of more developed countries trying to expose the pathways for innovation and research excellence.
[*] EU Horizon: Integration and Harmonization of Logistics Operations (TRACE); 2023-2026. PI: Dr C Anagnostopoulos
TRACE targets to an AI-driven universal platform related to planning, scheduling, optimization and events management as well as the use of blockchain technology to facilitate the real time conclusion of smart contracts and financial operations, thus, becoming one of the first attempts to provide an ‘intelligent cover’ upon the current logistics frameworks. TRACE will perform studies related to the barriers towards the new logistics era, the new business opportunities, the requirements for the legislation and regulatory frameworks and expose the benefits of the proposed approach in terms of the reduction for energy demand and emissions while limiting the operational costs for logistics stakeholders.
[*] EU H2020 Marie Skłodowska-Curie IF (MSCA): Intelligent Applications over Large Scale Data Streams (INNOVATE); 2018-2020. PI: Dr C Anagnostopoulos
INNOVATE proposes novel methodologies and solutions adopting a pool of computational intelligence schemes and ensemble learning models for fusing local pieces of knowledge in a timely and efficient way. Distributed stochastic optimization techniques will be developed to provide efficient solutions that can support large-scale data steam-based predictive analytics.
[*] EU H2020 FIRE+: Glasgow Network Functions for Unmanned Vehicles (GNFUV) 2018-2019. PI: Dr C Anagnostopoulos
Glasgow Network Functions for Unmanned Vehicles (GNFUV) is an extension of the Glasgow Network Functions (GNF) framework that operates over UxV infrastructures being particularly well-suited for operating over resourced-constrained and mobile Internet of Things (IoT) environments. GNFUV aims to showcase the capabilities of UxVs as hosting platforms for (virtualised) tasks, ranging from always-on monitoring and network topology self-management, to in-network, contextual information processing algorithms for edge-computing predictive analytics.
[*] UK EPSRC: Closed-Loop Data Science for Complex, Computationally- and Data-Intensive Analytics (CLDS) 2018-2023. co-PI: Dr C Anagnostopoulos; PI: Prof R Murray-Smith.
Progress in sensing, computational power, storage and analytic tools has given us access to enormous amounts of complex data, which can inform us of better ways to manage our cities, run our companies or develop new medicines. However, the 'elephant in the room' is that when we act on that data we change the world, potentially invalidating the older data. In this project we will look at the overlap between the challenge someone faces when coping with all the choices associated with booking a flight for a weekend away, and an expert running complex experiments in a laboratory.
[*] EU Erasmus+ KA2: Personalised Recommendations and Internationalisation for MOOCs in European Schools (PRIMES), 2016-2019. co-PI: Dr C Anagnostopoulos
PRIMES aims to produce a novel e-learning platform, combining the wide reach and popularity of MOOCs with advanced artificial intelligence and data summarisation algorithms, to provide a truly personalised learning experience, fitted to the needs and characteristics of teenager (secondary school) students.
[*] BMW Research Group: Advanced Federated Learning in Vehicle Networks, 2019-2027. PI: Dr C Anagnostopoulos
[*] NXP Research: In-vehicle Edge Data Analytics, 2020-2021. co-PI: Dr C Anagnostopoulos
[*] NHS Golden Jubilee: Risk Prediction Models in Congenital Diseases, 2021. (PIs: Dr C Anagnostopoulos; Dr F Deligianni)
[*] Turing Network Development (Alan Turing Institute and EPSRC IAA) Turing Network for AI in offshore wind geotechnics, 2023 (PI: Dr Gao, Co-I: Dr Anagnostopoulos)
[*] QTS Group Research: Enabling AI for Tackling Overgrowing Vegetation, 2024 (PI: Dr Anagnostopoulos; Co-PI: Dr Gao)
Publications
Selected publications
Koukosias, A., Anagnostopoulos, C. and Kolomvatsos, K. (2024) Task-aware data selectivity in pervasive edge computing environments. IEEE Transactions on Knowledge and Data Engineering, (doi: 10.1109/TKDE.2024.3485531) (Early Online Publication)
Aladwani, T., Anagnostopoulos, C. and Kolomvatsos, K. (2024) Node and relevant data selection in distributed predictive analytics: a query-centric approach. Journal of Network and Computer Applications, (Accepted for Publication)
Aladwani, T., Anagnostopoulos, C. , Puthiya Parambath, S. and Deligianni, F. (2024) CL-FML: Cluster-based & Label-aware Federated Meta-Learning for On-Demand Classification Tasks. In: 11th IEEE International Conference on Data Science and Advanced Analytics (DSAA 2024), San Diego, CA, United States, 6-10 October 2024, (Accepted for Publication)
Puthiya Parambath, S. A. , Anagnostopoulos, C. and Murray-Smith, R. (2024) Sequential query prediction based on multi-armed bandits with ensemble of transformer experts and immediate feedback. Data Mining and Knowledge Discovery, 38(6), pp. 3758-3782. (doi: 10.1007/s10618-024-01057-4)
Aladwani, T., Parambath, S. , Anagnostopoulos, C. and Deligianni, F. (2024) The Price of Labelling: A Two-Phase Federated Self-Learning Approach. In: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD 2024), Vilnius, Lithuania, 9-13 September 2024, (Accepted for Publication)
Long, Q. , Anagnostopoulos, C. and Kolomvatsos, K. (2024) Enhancing knowledge reusability: a distributed multitask machine learning approach. IEEE Transactions on Emerging Topics in Computing, (doi: 10.1109/TETC.2024.3390811) (Early Online Publication)
Kolomvatsos, K. and Anagnostopoulos, C. (2024) Autonomous proactive data management in support of pervasive edge applications. Future Generation Computer Systems, 155, pp. 108-120. (doi: 10.1016/j.future.2024.02.003)
Long, Q. , Anagnostopoulos, C. , Puthiya, S. and Bi, D. (2024) FedDIP: Federated Learning with Extreme Dynamic Pruning and Incremental Regularization. In: IEEE ICDM 2023, Shanghai, China, 1-4 December 2023, pp. 1187-1192. ISBN 9798350307887 (doi: 10.1109/ICDM58522.2023.00146)
Long, Q. , Kolomvatsos, K. and Anagnostopoulos, C. (2022) Knowledge reuse in edge computing environments. Journal of Network and Computer Applications, 206, 103466. (doi: 10.1016/j.jnca.2022.103466)
Kolomvatsos, K. and Anagnostopoulos, C. (2022) A proactive statistical model supporting services and tasks management in pervasive applications. IEEE Transactions on Network and Service Management, 19(3), pp. 3020-3031. (doi: 10.1109/TNSM.2022.3161663)
Harth, N., Voegel, H.-J., Kolomvatsos, K. and Anagnostopoulos, C. (2022) Local federated learning at the network edge for efficient predictive analytics. Future Generation Computer Systems, 134, pp. 107-122. (doi: 10.1016/j.future.2022.03.030)
Kolomvatsos, K., Anagnostopoulos, C. , Koziri, M. and Loukopoulos, T. (2022) Proactive & time-optimized data synopsis management at the edge. IEEE Transactions on Knowledge and Data Engineering, 34(7), pp. 3478-3490. (doi: 10.1109/TKDE.2020.3021377)
Oikonomou, P., Karanika, A., Anagnostopoulos, C. and Kolomvatsos, K. (2021) On the use of intelligent models towards meeting the challenges of the edge mesh. ACM Computing Surveys, 54(6), 125. (doi: 10.1145/3456630)
Alghamdi, I., Anagnostopoulos, C. and Pezaros, D. P. (2021) Data quality-aware task offloading in mobile edge computing: an optimal stopping theory approach. Future Generation Computer Systems, 117, pp. 462-479. (doi: 10.1016/j.future.2020.12.017)
Kolomvatsos, K. and Anagnostopoulos, C. (2020) An intelligent edge-centric queries allocation scheme based on ensemble models. ACM Transactions on Internet Technology, 20(4), 45. (doi: 10.1145/3417297)
Savva, F. , Anagnostopoulos, C. , Triantafillou, P. and Kolomvatsos, K. (2020) Large-scale data exploration using explanatory regression functions. ACM Transactions on Knowledge Discovery from Data, 14(6), 76. (doi: 10.1145/3410448)
Anagnostopoulos, C. (2020) Edge-centric inferential modeling & analytics. Journal of Network and Computer Applications, 164, 102696. (doi: 10.1016/j.jnca.2020.102696)
Panagidi, K., Anagnostopoulos, C. , Chalvatzaras, A. and Hadjietfthymiades, S. (2020) To transmit or not to transmit: controlling the communications in the mobile IoT domain. ACM Transactions on Internet Technology, 20(3), 22. (doi: 10.1145/3369389)
Savva, F. , Anagnostopoulos, C. and Triantafillou, P. (2020) Adaptive learning of aggregate analytics under dynamic workloads. Future Generation Computer Systems, 109, pp. 317-330. (doi: 10.1016/j.future.2020.03.063)
Savva, F. , Anagnostopoulos, C. and Triantafillou, P. (2020) SuRF: Identification of Interesting Data Regions with Surrogate Models. In: 36th IEEE International Conference on Data Engineering (IEEE ICDE), Dallas, TX, USA, 20-24 April 2020, pp. 1321-1332. ISBN 9781728129037 (doi: 10.1109/ICDE48307.2020.00118)
Anagnostopoulos, C. and Triantafillou, P. (2020) Large-scale predictive modeling and analytics through regression queries in data management systems. International Journal of Data Science and Analytics, 9(1), pp. 17-55. (doi: 10.1007/s41060-018-0163-5)
Anagnostopoulos, C. and Kolomvatsos, K. (2019) An intelligent, time-optimized monitoring scheme for edge nodes. Journal of Network and Computer Applications, 148, 102458. (doi: 10.1016/j.jnca.2019.102458)
Cziva, R., Anagnostopoulos, C. and Pezaros, D. P. (2018) Dynamic, Latency-Optimal vNF Placement at the Network Edge. In: IEEE Conference on Computer Communications (INFOCOM 2018), Honolulu, HI, USA, 15-19 Apr 2018, pp. 693-701. ISBN 9781538641286 (doi: 10.1109/INFOCOM.2018.8486021)
Anagnostopoulos, C. , Savva, F. and Triantafillou, P. (2018) Scalable aggregation predictive analytics: a query-driven machine learning approach. Applied Intelligence, 48(9), pp. 2546-2567. (doi: 10.1007/s10489-017-1093-y)
Ali, A., Anagnostopoulos, C. and Pezaros, D. P. (2018) On the Optimality of Virtualized Security Function Placement in Multi-Tenant Data Centers. In: IEEE International Conference on Communications (ICC 2018), Kansas City, MO, USA, 20-24 May 2018, ISBN 9781538631805 (doi: 10.1109/ICC.2018.8422426)
Kolomvatsos, K., Anagnostopoulos, C. and Hadjiefthymiades, S. (2017) Data fusion and type-2 fuzzy inference in contextual data stream monitoring. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 47(8), pp. 1839-1853. (doi: 10.1109/TSMC.2016.2560533)
Cahsai, A., Anagnostopoulos, C. , Ntarmos, N. and Triantafillou, P. (2017) Scaling k-Nearest Neighbors Queries (The Right Way). In: 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS), Atlanta, GA, USA, 5-8 June 2017, pp. 1419-1430. ISBN 9781538617939 (doi: 10.1109/ICDCS.2017.267)
Anagnostopoulos, C. and Triantafillou, P. (2017) Query-driven learning for predictive analytics of data subspace cardinality. ACM Transactions on Knowledge Discovery from Data, 11(4), 47. (doi: 10.1145/3059177)
Anagnostopoulos, C. and Triantafillou, P. (2017) Efficient Scalable Accurate Regression Queries in In-DBMS Analytics. In: IEEE International Conference on Data Engineering (ICDE), San Diego, CA, USA, 19-22 Apr 2017, pp. 559-570. ISBN 9781509065431 (doi: 10.1109/ICDE.2017.111)
Anagnostopoulos, C. (2016) Quality-optimized predictive analytics. Applied Intelligence, 45(4), pp. 1034-1046. (doi: 10.1007/s10489-016-0807-x)
Anagnostopoulos, C. , Hadjiefthymiades, S. and Kolomvatsos, K. (2016) Accurate, dynamic, and distributed localization of phenomena for mobile sensor networks. ACM Transactions on Sensor Networks, 12(2), 9. (doi: 10.1145/2882966)
Kolomvatsos, K., Anagnostopoulos, C. and Hadjiefthymiades, S. (2016) Distributed localized contextual event reasoning under uncertainty. IEEE Internet of Things Journal, 4(1), pp. 183-191. (doi: 10.1109/JIOT.2016.2638119)
Anagnostopoulos, C. , Kolomvatsos, K. and Hadjiefthymiades, S. (2015) Time-optimised user grouping in location based services. Computer Networks, 81, pp. 220-244. (doi: 10.1016/j.comnet.2015.02.017)
Anagnostopoulos, C. and Triantafillou, P. (2015) Learning set cardinality in distance nearest neighbours. In: IEEE International Conference on Data Mining (IEEE ICDM 2015), Atlantic City, NJ, USA, 14-17 Nov 2015, pp. 691-696. ISBN 9781467395038 (doi: 10.1109/ICDM.2015.17)
Kolomvatsos, K., Anagnostopoulos, C. and Hadjiefthymiades, S. (2014) An efficient recommendation system based on the optimal stopping theory. Expert Systems with Applications, 41(15), pp. 6796-6806. (doi: 10.1016/j.eswa.2014.04.039)
Anagnostopoulos, C. and Hadjiefthymiades, S. (2014) Advanced principal component-based compression schemes for wireless sensor networks. ACM Transactions on Sensor Networks, 11(1), 7. (doi: 10.1145/2629330)
Anagnostopoulos, C. and Hadjiefthymiades, S. (2014) Intelligent trajectory classification for improved movement prediction. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 44(10), pp. 1301-1314. (doi: 10.1109/TSMC.2014.2316742)
Anagnostopoulos, C. and Triantafillou, P. (2014) Scaling out Big Data Missing Value Imputations: Pythia vs. Godzilla. In: 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD '14), New York, N.Y., U.S.A, 24-27 Aug 2014, pp. 651-660. ISBN 9781450329569 (doi: 10.1145/2623330.2623615)
Kolomvatsos, K., Anagnostopoulos, C. and Hadjiefthymiades, S. (2014) Determining the optimal stopping time for automated negotiations. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 44(7), pp. 908-921. (doi: 10.1109/TSMC.2013.2279665)
Anagnostopoulos, C. (2014) Time-optimized contextual information forwarding in mobile sensor networks. Journal of Parallel and Distributed Computing, 74(5), pp. 2317-2332. (doi: 10.1016/j.jpdc.2014.01.008)
Anagnostopoulos, C. and Hadjiefthymiades, S. (2013) Multivariate context collection in mobile sensor networks. Computer Networks, 57(6), pp. 1394-1407. (doi: 10.1016/j.comnet.2013.01.001)
Anagnostopoulos, C. , Sekkas, O. and Hadjiefthymiades, S. (2012) An adaptive epidemic information dissemination model for wireless sensor networks. Pervasive and Mobile Computing, 8(5), pp. 751-763. (doi: 10.1016/j.pmcj.2011.06.005)
Anagnostopoulos, C. and Hadjiefthymiades, S. (2012) Optimal, quality-aware scheduling of data consumption in mobile ad hoc networks. Journal of Parallel and Distributed Computing, 72(10), pp. 1269-1279. (doi: 10.1016/j.jpdc.2012.05.011)
Anagnostopoulos, C. , Hadjiefthymiades, S. and Georgas, P. (2012) PC3: principal component-based context compression. Journal of Parallel and Distributed Computing, 72(2), pp. 155-170. (doi: 10.1016/j.jpdc.2011.10.001)
Kolomvatsos, K., Anagnostopoulos, C. and Hadjiefthymiades, S. (2012) A fuzzy logic system for bargaining in information markets. ACM Transactions on Intelligent Systems and Technology, 3(2), pp. 1-26. (doi: 10.1145/2089094.2089108)
Anagnostopoulos, C. and Hadjiefthymiades, S. (2011) Delay-tolerant delivery of quality information in ad hoc networks. Journal of Parallel and Distributed Computing, 71(7), pp. 974-987. (doi: 10.1016/j.jpdc.2010.11.007)
Anagnostopoulos, T., Anagnostopoulos, C. and Hadjiefthymiades, S. (2011) An adaptive location prediction model based on fuzzy control. Computer Communications, 34(7), pp. 816-834. (doi: 10.1016/j.comcom.2010.09.001)
Anagnostopoulos, C. , Hadjiefthymiades, S. and Zervas, E. (2011) Information dissemination between mobile nodes for collaborative context awareness. IEEE Transactions on Mobile Computing, 10(12), pp. 1710-1725. (doi: 10.1109/TMC.2011.19)
Anagnostopoulos, C. , Hadjiefthymiades, S. and Zervas, E. (2011) An analytical model for multi-epidemic information dissemination. Journal of Parallel and Distributed Computing, 71(1), pp. 87-104. (doi: 10.1016/j.jpdc.2010.08.010)
Anagnostopoulos, C. and Hadjiefthymiades, S. (2009) Advanced inference in situation-aware computing. IEEE Transactions on Systems, Man, and Cybernetics. Part A: Systems and Humans, 39(5), pp. 1108-1115. (doi: 10.1109/TSMCA.2009.2025023)
Anagnostopoulos, C. and Hadjiefthymiades, S. (2008) Enhancing situation-aware systems through imprecise reasoning. IEEE Transactions on Mobile Computing, 7(10), pp. 1153-1168. (doi: 10.1109/TMC.2008.34)
All publications
Grants
- EU Horizon: An Intelligent platform for integrating climate services (TERRA); PI; 2025-2028; £2M
- EU Horizon: On the use of Internet of Senses for the Cultural Heritage (ELLIE); PI; 2025-2028; £2.8M
- EU Horizon: Collaborative Innovation in 3D VLSI Reliability (COIN-3D); PI; 2024-2027; £1.2M
- EU Horizon: Integration and Harmonization of Logistics Operations (TRACE); PI; 2023-2026; £8.5M
- UK EPSRC: Closed-Loop Data Science for Complex, Computationally- and Data-Intensive Analytics (CLDS); 2018-2023; Co-PI, £3M
- EU H2020 Marie Skłodowska-Curie IF 2017 (MSCA): Intelligent Applications over Large Scale Data Streams (INNOVATE); 2018-2020; PI, £200K
- EU H2020 Future Internet Research and Experimentation (FIRE+): Glasgow Network Functions for Unmanned Vehicles (GNFUV); 2018-2019; PI, £100K
- EU Erasmus+ KA2: Personalised Recommendations and Internationalisation for MOOCs in European Schools (PRIMES), 2016-2019; co-PI, £414K
- BMW Research Group: Advanced Federated Learning in Vehicle Networks, 2019-2027; PI
- NXP Research: In-vehicle Edge Data Analytics, 2020-2021; co-PI
- NHS Research: Risk Prediction Models in Congenital Diseases, 2021
- Turing Network Development (Alan Turing Institute and EPSRC IAA): Turing Network for AI in offshore wind geotechnics, 2023; Co-PI
- QTS Group Research: Enabling AI for Tackling Overgrowing Vegetation, 2024; PI
Supervision
Open PhD posts
- Prospective PhD Students: feel free to contact me via e-mail and visit PhD Opportunities (Open PhD Calls).
Former PhD Students
- Dr Kostas Kolomvatsos (University of Athens); 2010-2013. 'Automated Negotiations between Intelligent Entities in Electronic Marketplaces'.
- Dr Theodore Anagnostopoulos (University of Athens); 2009-2012. 'Advanced Location Prediction Techniques in Mobile Computing'.
- Dr Abeer Farouk Tawfeek Ali (University of Glasgow); 2017-2020. 'On the Placement of Security-related Virtualized Network Functions over Data Center Networks.'
- Dr Atoshum Samuel Cahsai (University of Glasgow); 2017-2020. 'Scaling kNN Queries using Statistical Learning'
- Dr Fotis Savva (University of Glasgow); 2018-2021. 'Query-driven Learning for Automating Exploratory Analytics in Large-scale Data Management Systems'
- Dr Natascha Harth (University of Glasgow); 2018-2021. 'Quality-aware predictive modelling & inferential analytics at the network edge'
- Dr Ibrahim Alghamdi (University of Glasgow); 2018-2021. 'Computation offloading in mobile edge computing: an optimal stopping theory approach'
Current PhD Students
- Aladwani, Tahani
Diagnosis of Diseases as Cloud Computing Service (DoDaaS) - Alfahad, Saleh Abdullah M
Engineering Edge Computing with Predictive Intelligence - Alsharif, Ghadeer Obaid F
Security-by-Design Framework for the IoT - Ghanduri, Fatima H M
Predictive Intelligence of Interpretable Models in the Financial Domain - LI, WENHAO
Mini-batch Gradient-parallel Heterogeneous Ensembles for Large-scale Multi-feature Data Learning Optimization - Liu, Qianying
Deep Learning for Health Informatics - Long, Qianyu
Collaborative Distributed Machine Learning: From Knowledge Reuse to Sparsification in Federated Learning - Tan, Zhuoran
Cyber Attack Chain Analysis with Federated Graph Neural Network - Wang, Qiyuan
Resource-aware & Adaptive Novelty Detection in Edge Computing Environments - Xiao, Ke
Resilient Learning in Edge Computing
Teaching
- Database Systems (H/MSc)
- Database Theory & Analytics (MSc IT+)
Professional activities & recognition
Prizes, awards & distinctions
- 2019: Best Paper Runner-Up Award (IEEE Wireless Days)
- 2019: 2nd Place Student Research Competition (ACM SIGMOD)
- 2018: Best Student Paper (IEEE BigData)
- 2017: Nomination for Best Dissertation Supervisor (STA University of Glasgow)
- 2017: Best Poster Award (BMW Workshop)
- 2017: Best Poster Award (International Conference of Big Data in Cyber Security)
Research fellowships
- 2018 - 2020: Marie Sklodowska-Curie (EU/MSCA-IF) Fellowship Supervisor
- 2015 - 2017: Big Data Research Fellow
Grant committees & research advisory boards
- 2020 - date: EU CHIST-ERA, Grant Proposal Reviewer and Panel Member
- 2021 - date: UK Research and Innovation Future Leaders Fellowships (FLF), Peer Review College (PRC) Member
- 2021 - date: Qatar National Research Fund (QNRF), Peer Reviewer
- 2020 - date: International Hellenic University, Faculty Board Election Member
- 2021 - date: Dutch Research Council, Peer Reviewer
- 2013 - 2014: Greek State Scholarship Foundation, Grant Fellowship Reviewer
- 2021 - date: Irish Research Council, Grant Reviewer
- 2022 - date: Austrian Science Fund (FWF), Grant Reviewer
- 2024 - date: Swiss National Science Foundation (SNSF), Grant Reviewer
Editorial boards
- 2019 - present: Open Computer Science (Editor in Chief)
- 2021 - present: IEEE Access (Associate Editor)
- 2015 - present: International Journal of Distributed Sensor Networks (Associate Editor)
- 2015 - present: Applied Intelligence (Associate Editor)
- 2022 - present: Frontiers in the Internet of Things (Associate Editor)
- 2022 - present: Journal of Smart Cities and Society (Associate Editor)
- 2016 - 2017: SI: Machine Learning and Computational Intelligence for Big Data; Journal of Machine Learning and Cybernetics (Springer)
- 2017 - 2018: SI: Mobile Sensor Networks; Electronics (MDPI)
- 2019 - 2020: SI: Distributed Artificial & Machine Intelligence in Evolving Sensor Networks, Journal of Distributed sensor Networks
- 2019 - 2020: SI: Recent Advancement in Edge/Fog Computing for Intelligent IoT Applications, Sensors J
- 2020 - 2021: SI: Intelligent Edge Computing for Smart Cities, Smart Cities J
Professional & learned societies
- 2017 - date: Professional Senior Member, Association of Computing Machinery (ACM)
- 2015 - date: Computer Society Member, IEEE (The Institute of Electrical and Electronics Engineers)
- 2016 - date: Associate Fellow, Higher Education Academy
- 2015 - date: Regular Member, INSTICC
Research datasets
Additional information
General Chair
- 45th IEEE International Confernece on Distributed Computing Systems (IEEE ICDCS 2025)
Workshop Organizer
- IEEE MAB-KD Workshop Chair/Organizer, IEEE International Conference on Data Mining (IEEE ICDM 2023)
- IEEE EdgeAI-IoT Workshop Chair/Organizer, IEEE WF-IoT 2023
- IEEE EdgeAI-IoT Workshop Chair/Organizer, IEEE WF-IoT 2022
Programme Committee Member/Co-chair
- ACM SIGKDD 2024 (KDD-24)
- AAAI Conference on Artificial Intelligence (AAAI-24)
- ECML/PKDD 2024
- Euro-Par 2023
- IEEE Future Networks World Forum 2023
- IEEE Special Technical Community Smart and Circular Cities
- IEEE Cyber Security & Resilience IEEE CSR 2021-2023
- IEEE Data Science for Cyber Security 2021-2023 (IEEE DS4CS)
- IEEE Workshop on Secure IoT, Edge and Cloud systems SIoTEC 2022-2023
- IEEE International Conference on Data Engineering; Intl Workshop of Data-Driven Smart Cities IEEE DASC/ICDE 2019-2023
- IEEE Intelligent Systems Conference IEEE IntelliSys 2015-2023
- IEEE Consumer Communications & Networking Conference IEEE CCNC 2018-2023
- IEEE International Conference on Data Management Technologies and Applications (DATA 2016-2024)
- IEEE International Workshop on Pervasive Intelligent Systems PIS 2017-2021
- IEEE International Workshop on Distributed and Intelligent Systems DaIS 2021
- IEEE International Conference on Computer Applications & Information Security IEEE ICCAIS 2021
- IEEE International Conference on Computational Intelligence and Communication Networks (CICN 2022-2023)
- IEEE International Conference on Data Engineering IEEE ICDE 2016, KEYS 2016
- IEEE International Conference on Computer Communications IEEE INFOCOM 2019-2021
- Wireless Days 2019-2021 IEEE WD'21
- IEEE International Conference on Future Internet of Things and Cloud IEEE FiCloud 2017-2018
- IEEE International Workshop on Information and Knowledge in the Internet of Things IEEE IKIT 2017
- 7th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare ICTH 2017
- IEEE International Conference on Big Data 2015; Session Chair: Data mining and learning (IEEE BigData 2015)
- IEEE International Conference on Information, Intelligence, Systems and Applications; Session Chair: Making Sense from Large-scale Data Streams (IEEE IISA 2016)
- International Workshop on Algorithmic Aspects of Cloud Computing (ALGOCLOUD 2015-2016)
- Workshop on Recent Advances in Behaviour Prediction and Pro-active Pervasive Computing (AwareCast-Pervasive 2012-2015)
- International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP 2012-2015)
- IEEE Panhellenic Conference on Informatics (PCI 2014-2021)
- International Workshop on Semantic Web for Services and Processes; Session Chair (SWSP07)
- International Conference on Metadata and Semantics Research (MTSR 2007)