Projekter pr. år
Organisationsprofil
Organisationsprofil
Data Engineering, Science and Systems (DESS) is one of four research groups in Department of Computer Science, Aalborg University.
DESS encompasses up-and-coming scientists as well as experienced scientists, all with strong records of excellence and contributions in data engineering, data science, and data systems that span up to 30 years. Embracing the opportunities enabled by the ongoing, sweeping digitalization of societal, industrial, and scientific processes, we collaborate with our partners to conduct research that aims to advance value creation from data.
VALUE CREATION FROM DATA
Targeting value creation from data, the research is generally constructive in nature, meaning that the research concerns:
- The invention of purposeful artifacts, such as frameworks, algorithms, data structures, indexes, languages, and techniques, as well as tools, systems, and solutions based on such components.
- The construction of prototype software, typically either for proof-of-concept or for the purpose of conducting empirical studies.
SCOPE
The research spans foundational topics as well as advanced applications and aims to take advantage of opportunities for cross-fertilization between foundational and applied research activities. The research also embraces a data science approach, where solutions to specific domain challenges are invented.
DATA
The research focuses on spatio-temporal, multidimensional, timeseries, sensor and metric data, but also contributes in relation to graph, text, and IoT, and electroencephalogram (EEG) data.
TOPICS
The research concerns data management and analytics, including query processing, data mining, and machine learning. Examples include:
- Data management: data integration and data lakes, data warehousing, and indexing
- Analytics: prediction and forecasting, pattern and outlier detection, similarity search, advanced routing, transfer learning, greenhouse gas emissions estimation, spatial keyword querying, clustering, why-not querying
APPLICATIONS
While key applications are in the general areas of intelligent transportation and digital energy, the group covers a wider range of data-intensive applications. Example applications include:
- Flexible energy grids that enable the ongoing transformation of the electricity grid and society-wide electrification.
- Smart services for energy efficient buildings
- IoT data-based diagnostics and prediction in the renewable energy sector
- Adaptability and failure prediction in power electronics
- Learning of travel times and travel-time based routing in dynamic and uncertain road networks
- Advanced spatial crowdsourcing in transportation and beyond
- Maritime analytics, including energy efficient routing and speed recommendation
- Personal data retention and GDPR compliance
- EGG based data analysis pipelines for neurorehabilitation, motion intent detection, and emotion and activity recognition
- Analysis of complex microbial community interactions
For more information see
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Samarbejde i de sidste fem år
Profiler
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Abduvoris Abduvakhobov
- Det Tekniske Fakultet for IT og Design - Ph.d.-stipendiat
- Institut for Datalogi - Ph.d.-stipendiat
- Data Engineering, Science and Systems - Ph.d.-stipendiat
Person: VIP
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Asger Horn Brorholt
- Det Tekniske Fakultet for IT og Design - Ph.d.-stipendiat
- Institut for Datalogi - Ph.d.-stipendiat
- Data Engineering, Science and Systems - Ph.d.-stipendiat
Person: VIP
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Jonas Brusokas
- Det Tekniske Fakultet for IT og Design - Videnskabelig assistent, Ph.d.-stipendiat
- Institut for Datalogi - Videnskabelig assistent, Ph.d.-stipendiat
- Data Engineering, Science and Systems - Videnskabelig assistent, Ph.d.-stipendiat
Person: VIP
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Inverse Design of Materials Using Diffusion Probabilistic Models
01/04/2024 → 31/03/2026
Projekter: Projekt › Forskning
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Data Management, Fundamental Algorithms, and Machine Learning for Emerging Problems in Large Networks – with Interdisciplinary Applications in Life and Health Sciences
01/05/2022 → 30/04/2027
Projekter: Projekt › Forskning
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Explainable AI for Complex Microbial Community Interactions and Predictions
Nielsen, P. H., Guo, C., Andersen, K. S. & Gomez, M. P.
01/01/2021 → 31/12/2024
Projekter: Projekt › Forskning
Publikationer
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Coalition-based task assignment with priority-aware fairness in spatial crowdsourcing
Zhao, Y., Zheng, K., Wang, Z., Deng, L., Yang, B., Pedersen, T. B., Jensen, C. S. & Zhou, X., jan. 2024, I: VLDB Journal. 33, 1, s. 163-184 22 s.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
Åben adgangFil1 Citationer (Scopus)21 Downloads (Pure) -
Digital Twin Empowered PV Power Prediction
Zhang, X., Li, Y., Li, T., Gui, Y., Sun, Q. & Gao, D. W., 2024, I: Journal of Modern Power Systems and Clean Energy. PP, 99, s. 1-13 13 s., 10322689.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
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FedAGL: A Communication-Efficient Federated Vehicular Network
Su, L., Li, Y., Guan, P., Li, T., Taherkordi, A. & Jensen, C. S., 2024, I: IEEE Transactions on Intelligent Vehicles. s. 1-17 17 s.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › peer review
Forskningsdatasæt
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Tutorial for the 2022 ACM SIGMOD Conference: Spatial Data Quality in the IoT Era: Management and Exploitation
Li, H. (Ophavsperson), Tang, B. (Ophavsperson), Lu, H. (Ophavsperson), Cheema, M. A. (Ophavsperson) & Jensen, C. S. (Ophavsperson), Zenodo, 17 jun. 2022
DOI: 10.5281/zenodo.7053915, https://zenodo.org/record/7053915
Datasæt
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The Project of Efficient and Error-bounded Spatiotemporal Quantile Monitoring in Edge Computing Environments
Li, H. (Ophavsperson), Yi, L. (Ophavsperson), Tang, B. (Ophavsperson), Lu, H. (Ophavsperson) & Jensen, C. S. (Ophavsperson), Zenodo, 25 maj 2022
DOI: 10.5281/zenodo.7053904, https://zenodo.org/record/7053904
Datasæt
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RDF2Vec Embeddings Generator
Christensen, M. P. (Ophavsperson), Lissandrini, M. (Ophavsperson) & Hose, K. (Ophavsperson), Zenodo, 22 mar. 2022
DOI: 10.5281/zenodo.6384728, https://zenodo.org/record/6384728
Datasæt
Priser
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The Best Paper Award from 2023 International Conference on Cyber-energy Systems and Intelligent Energies (ICCSIE)
Li, Yushuai (Modtager), 2023
Pris: Forsknings- uddannelses og innovationspriser
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The Excellent Young Expert Award from MPCE
Li, Yushuai (Modtager), 2023
Pris: Forsknings- uddannelses og innovationspriser
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Æresdoktor ved TU Dresden
Pedersen, Torben Bach (Modtager), 29 sep. 2021
Pris: Ærespriser og udnævnelser
Aktiviteter
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Norwegian Research Center for AI Innovation (Ekstern organisation)
Christian S. Jensen (Forperson)
2020 → …Aktivitet: Medlemskab › Bestyrelsesarbejde i virksomhed, forening eller organisation
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University of Stuttgart
Tobias Skovgaard Jepsen (Gæsteforsker)
29 sep. 2019 → 21 dec. 2019Aktivitet: Gæsteophold ved andre institutioner
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Bonsai Hackathon 2019
Massimo Pizzol (Deltager), Agneta Ghose (Deltager), Bo Pedersen Weidema (Deltager) & Matteo Lissandrini (Deltager)
25 mar. 2019 → 29 mar. 2019Aktivitet: Deltagelse i faglig begivenhed › Organisering af eller deltagelse i workshop, kursus, seminar, udstilling eller lignende
Presse/medier
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Villum Synergy: Tværfaglig forskning giver god synergi
Kamal Nasrollahi, Thomas Ploug, Morten Mattrup Smedskjær, Rasmus Waagepetersen, Johannes van Ommeren, Johannes Bjerva, Euan Lindsay & Jilin Hu
02/10/2023
1 element af Mediedækning
Presse/medie
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EWII køber andel af FlexShape for at styrke udviklingen af forbrugsfleksibilitet
Torben Bach Pedersen & Laurynas Siksnys
13/04/2023 → 19/04/2023
7 elementer af Mediedækning
Presse/medie