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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Netværk
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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Frederik Agneborn
- Det Tekniske Fakultet for IT og Design - Assistent, Studerende, div. stillinger
- Institut for Datalogi - Assistent, Studerende, div. stillinger
- Data Engineering, Science and Systems - Assistent, Studerende, div. stillinger
Person: TAP
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Esben Rask Bach
- Det Tekniske Fakultet for IT og Design - Studenterunderviser
- Institut for Datalogi - Studenterunderviser
- Data Engineering, Science and Systems - Studenterunderviser
Person: VIP
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PREDICTION-ENABLED DYNAMIC SCHEDULING OF HOUSEHOLD ELECTRICITY USAGE
01/01/2023 → 01/07/2023
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., Hove Hansen, S. & Andersen, K. S.
01/01/2021 → 31/12/2023
Projekter: Projekt › Forskning
Publikationer
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Adversarial Autoencoder for Unsupervised Time Series Anomaly Detection and Interpretation
Chen, X., Deng, L., Zhao, Y. & Zheng, K., 2023, WSDM 2023.Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review
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CityCross: Transferring Attention-based Knowledge for Location-based Advertising Recommendation
Qiu, D., Wang, Y., Zhao, Y., Deng, L. & Zheng, K., 2023, MDM 2022.Publikation: Bidrag til bog/antologi/rapport/konference proceeding › Konferenceartikel i proceeding › Forskning › peer review
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Efficient and Effective Similar Subtrajectory Search: A Spatial-aware Comprehension Approach
Deng, L., Sun, H., Sun, R., Zhao, Y. & Su, H., 2023, I: ACM Transactions on Intelligent Systems and Technology (TIST). 13, 3, s. 1 22 s., 35.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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Æresdoktor ved TU Dresden
Pedersen, Torben Bach (Modtager), 29 sep. 2021
Pris: Ærespriser og udnævnelser
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SSTD 2021 Best Paper Candidate
Chan, Harry Kai Ho (Modtager), Liu, Tiantian (Modtager), Li, Huan (Modtager) & Lu, Hua (Modtager), 2021
Pris: Konferencepriser
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Best Paper Award Runner-Up
Isaj, Suela (Modtager), Zimányi, Esteban (Modtager) & Pedersen, Torben Bach (Modtager), 20 aug. 2019
Pris: Konferencepriser
Fil
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 eller lignende
Presse/medier
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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
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