Information Systems Engineering
Information Systems Engineering provides foundational and advanced techniques, algorithms, design and engineering approaches to model complete lifecycles of data-intensive and distributed information systems.
Contact
- Schahram Dustdar, Coordinator
Research Topics
- Compilers, Languages, and Middleware Engineering
- Programming Systems and Tools
- Distributed Systems
- High Performance Computing
- Data Analytics and Machine Learning
- Business Informatics
- E-commerce
- Informatics Didactics
About
Information Systems Engineering provides foundational and advanced techniques, algorithms, design and engineering approaches to model complete lifecycles of data-intensive and distributed information systems.
Information systems play a crucial role in many forms of organizations, and act as a facilitator and enabler for the digitalization of personal and social spaces. As such, information systems became the underlying “operating system” of our society.
Typical activities in the lifecycle of information systems are fundamental requirements elicitation as well as analysis and design of systems, their implementation, as well as subsequent execution and maintenance activities. Importantly, information systems engineering is not limited to technologies and methodological approaches, but comprises technical solutions as well as social and business-related implications of information systems. Therefore, information systems engineering can also act as an interface between computer science and other research disciplines (technical and non-technical) as well as business related activities.
Research Units
Six of the faculty’s twenty-six research units are primarily focused on topics related to Information Systems Engineering. Visit their pages to learn about current projects, publications, courses, and the people involved.
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Software Engineering
E194-01 / Head: Maria Christakis -
Distributed Systems
E194-02 / Head: Schahram Dustdar -
Business Informatics
E194-03 / Head: Dominik Bork -
Data Science
E194-04 / Head: Allan Hanbury -
Compilers and Languages
E194-05 / Head: M. Anton Ertl -
Machine Learning
E194-06 / Head: Thomas Gärtner
Below is a small selection of recent research activities related to Information Systems Engineering. To learn more, visit the pages of the research units listed above.
Recent Projects
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Securing Agentic AI in Software Engineering Tasks: Attack Surfaces, Threat Models, and Defenses
2026 – 2027 / Austrian Exchange Service (OeAD) -
Integrating Physical Modeling, AI, and Human Expertise for Energy-Efficient Tunnel Kiln Brick Production
2025 – 2028 / Austrian Research Promotion Agency (FFG) -
Types4Strings: Types for Strings
2024 – 2027 / Austrian Science Fund (FWF)
Publication: 221009 -
Operational data-driven SOH estimation and prediction for maritime battery system
2024 – 2025 / AVL List GmbH -
Intent-based data operation in the computing continuum
2024 – 2026 / European Commission
Publications: 195922 / 199889 / 201667 / 203889 / 204055 / 204350 / 208695 / 208717 / 208559 / 208718 / 208042 / 209928 / 209929 / 211104 / 211528 / 211167 / 213464 / 213934 / 216047 / 216048 / 216051 / 217905 / 219274 / 221010 / 222720 / 223085 / 223676 / 223680 / 225284 / 225669 / 227167 / 227082 -
Cloud Open Source Research Mobility Network
2023 – 2026 / European Commission
Publication: 226229 -
Trustworthy, Energy-Aware federated DAta Lakes along the Computing Continuum
2022 – 2025 / European Commission
Publications: 177474 / 189351 / 189044 / 189016 / 189544 / 190613 / 194409 / 195539 / 195922 / 195912 / 195917 / 195920 / 195914 / 195925 / 195916 / 196065 / 204916 / 196508 / 198064 / 200891 / 199515 / 201676 / 201665 / 204057 / 208695 / 208717 / 208718 / 208042 / 210205 / 210201 / 209777 / 211104 / 211007 / 212574 / 213464 / 213939 / 214607 / 216046 / 216051 / 216533 / 217604 / 217844 / 217610 / 217609 / 217887 / 219279 / 219274 / 221010 / 226154 / 227601 / 227637 / 227630 / 227817 / 227816 / 227838 / 227835 / 228799 -
OPC UA Rule Editor 2.0
2022 / Siemens AG -
OPC UA Rule Editor
2021 / Siemens AG
Publication: 190612 -
fAIr by design – solutions for discrimination reduction in AI de-velopment
2021 – 2024 / Austrian Research Promotion Agency (FFG) -
EGI Advanced Computing for EOSC
2021 – 2023 / European Commission -
Blockchain Technologies for the Internet of Things
2020 – 2022 / Federal Ministry of Science, Research and Economy (bm:wfw)
Publications: 137780 / 137781 / 176500 / 58438 / 58439 / 58542 / 58788 -
What Can You Trust in the Large and Noisy Web?
2020 – 2022 / No funding agency -
Protecting Sensitive Data in the Computing Continuum
2020 – 2022 / European Commission
Publications: 136154 / 136519 / 137920 / 201665 / 58446 / 58486 / 58540 / 58547 / 58572 / 58800 / 80255 / 101798 -
An open, trusted fog computing platform facilitating the deployment, orchestration and management of scalable, heterogeneous and secure IOT services and cross-cloud apps
2020 – 2022 / European Commission
Publications: 177093 / 177092 / 190652 / 201904 / 201905 / 58534 / 87224 -
STARCloud
2019 – 2021 / European Commission -
WellFort
2019 – 2022 / Austrian Research Promotion Agency (FFG) -
Visual History of the Holocaust: Rethinking Curation in the Digital Age
2019 – 2023 / European Commission
Publications: 150286 / 150288 / 150284 / 153859 / 192539 -
Vienna Informatics Living Lab
2018 – 2019 / Vienna Business Agency (WAW) -
Semantic Processing of Security Event Streams
2018 – 2021 / Austrian Science Fund (FWF)
Recent Publications
- A Metric for Assessing, Comparing, and Predicting the Performance of Autonomous RFID-Based Inventory Robots for Retail / Gaston, B., Casamayor Pujol, V., Lopez-Soriano, S., & Pous, R. (2022). A Metric for Assessing, Comparing, and Predicting the Performance of Autonomous RFID-Based Inventory Robots for Retail. IEEE Transactions on Industrial Electronics, 69(10), 10354–10362. https://doi.org/10.1109/tie.2021.3128917
- AI for next generation computing: Emerging trends and future directions / Gill, S. S., Xu, M., Ottaviani, C., Patros, P., Bahsoon, R., Shaghaghi, A., Golec, M., Stankovski, V., Wu, H., Abraham, A., Singh, M., Mehta, H., Ghosh, S. K., Baker, T., Parlikad, A. K., Lutfiyya, H., Kanhere, S. S., Sakellariou, R., Dustdar, S., … Uhlig, S. (2022). AI for next generation computing: Emerging trends and future directions. Internet of Things, 19, 100514. https://doi.org/10.1016/j.iot.2022.100514
- Towards Interoperable Metamodeling Platforms: The Case of Bridging ADOxx and EMF / Bork, D., Anagnostou, K., & Wimmer, M. (2022). Towards Interoperable Metamodeling Platforms: The Case of Bridging ADOxx and EMF. In X. Franch, G. Poels, F. Gailly, & M. Snoeck (Eds.), Advanced Information Systems Engineering. 34th International Conference, CAiSE 2022, Leuven, Belgium, June 6–10, 2022, Proceedings (pp. 479–497). Springer Cham. https://doi.org/10.1007/978-3-031-07472-1_28
- Review of Automated Vulnerability Analysis of Smart Contracts on Ethereum / Rameder, H., di Angelo, M., & Salzer, G. (2022). Review of Automated Vulnerability Analysis of Smart Contracts on Ethereum. Frontiers in Blockchain, 5. https://doi.org/10.3389/fbloc.2022.814977
- Secured Wireless Energy Transfer for the Internet of Everything in Ambient Intelligent Environments / Sah, D. K., Poongodi, M., Donta, P. K., Hamdi, M., Cengiz, K., Kamruzzaman, M. M., & Rauf, H. T. (2022, March). Secured Wireless Energy Transfer for the Internet of Everything in Ambient Intelligent Environments. IEEE Internet of Things Magazine, 5(1), 62–66. https://doi.org/10.1109/iotm.001.2100116
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An Empirical Investigation of Command-Line Customization
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Schröder, M., & Cito, J. (2022). An Empirical Investigation of Command-Line Customization. Empirical Software Engineering, 27(2), Article 30. https://doi.org/10.1007/s10664-021-10036-y
Download: PDF (1.85 MB) - A Simple Solution to Locate Groups of Items in Large Retail Stores Using an RFID Robot / Casamayor Pujol, V., Gaston, B., Lopez-Soriano, S., Alajami, A. A., & Pous, R. (2022). A Simple Solution to Locate Groups of Items in Large Retail Stores Using an RFID Robot. IEEE Transactions on Industrial Informatics, 18(2), 767–775. https://doi.org/10.1109/tii.2021.3080670
- LFM-2b: A Dataset of Enriched Music Listening Events for Recommender Systems Research and Fairness Analysis / Schedl, M., Brandl, S., Lesota, O., Parada-Cabaleiro, E., Penz, D., & Rekabsaz, N. (2022). LFM-2b: A Dataset of Enriched Music Listening Events for Recommender Systems Research and Fairness Analysis. In ACM SIGIR Conference on Human Information Interaction and Retrieval. CHIIR ’22: ACM SIGIR Conference on Human Information Interaction and Retrieval, Regensburg, Germany. ACM. https://doi.org/10.1145/3498366.3505791
- Roadmap for Edge AI: A Dagstuhl Perspective / Ding, A. Y., Peltonen, E., Meuser, T., Aral, A., Becker, C., Dustdar, S., Hiessl, T., Kranzlmüller, D., Liyanage, M., Maghsudi, S., Mohan, N., Ott, J., Rellermeyer, J. S., Schulte, S., Schulzrinne, H., Solmaz, G., Tarkoma, S., Varghese, B., & Wolf, L. (2022). Roadmap for Edge AI: A Dagstuhl Perspective. ACM SIGCOMM Computer Communication Review, 52(1), 28–33. https://doi.org/10.1145/3523230.3523235
- Dependent Function Embedding for Distributed Serverless Edge Computing / Deng, S., Zhao, H., Xiang, Z., Zhang, C., Jiang, R., Li, Y., Yin, J., Dustdar, S., & Zomaya, A. Y. (2022). Dependent Function Embedding for Distributed Serverless Edge Computing. IEEE Transactions on Parallel and Distributed Systems, 33(10), 2346–2357. https://doi.org/10.1109/tpds.2021.3137380
- Darwin-S: A Reference Software Architecture for Brain-Inspired Computers / Deng, S., Lv, P., Jin, O., Dustdar, S., Li, Y., Ma, D., Wu, Z., & Pan, G. (2022). Darwin-S: A Reference Software Architecture for Brain-Inspired Computers. Computer, 55(5), 51–63. https://doi.org/10.1109/mc.2022.3144397
- Secure and Efficient Decentralized Federated Learning with Data Representation Protection / Qin, Z., Deng, S., Yan, X., Dustdar, S., & Zomaya, A. Y. (2022). Secure and Efficient Decentralized Federated Learning with Data Representation Protection. arXiv. https://doi.org/10.48550/arXiv.2205.10568
- Autonomy and Intelligence in the Computing Continuum: Challenges, Enablers, and Future Directions for Orchestration / Kokkonen, H., Loven, L., Hossein Motlagh, N., Partala, J., Gonzalez-Gil, A., Sola, E., Angulo, I., Liyanage, M., Leppänen, T., Nguyen, T., Kostakos, P., Bennis, M., Tarkoma, S., Dustdar, S., Pirttikangas, S., & Riekki, J. (2022). Autonomy and Intelligence in the Computing Continuum: Challenges, Enablers, and Future Directions for Orchestration. arXiv. https://doi.org/10.48550/arXiv.2205.01423
- Multi-Component Optimization and Efficient Deployment of Neural-Networks on Resource-Constrained IoT Hardware / Sudharsan, B., Sundaram, D., Patel, P., Breslin, J. G., Ali, M. I., Dustdar, S., Zomaya, A., & Ranjan, R. (2022). Multi-Component Optimization and Efficient Deployment of Neural-Networks on Resource-Constrained IoT Hardware. arXiv. https://doi.org/10.48550/arXiv.2204.10183
- AI for Next Generation Computing: Emerging Trends and Future Directions / Gill, S. S., Xu, M., Ottaviani, C., Patros, P., Bahsoon, R., Shaghaghi, A., Golec, M., Stankovski, V., Wu, H., Abraham, A., Singh, M., Mehta, H., Ghosh, S. K., Baker, T., Parlikad, A. K., Lutfiyya, H., Kanhere, S. S., Sakellariou, R., Dustdar, S., … Uhlig, S. (2022). AI for Next Generation Computing: Emerging Trends and Future Directions. arXiv. https://doi.org/10.48550/arXiv.2203.04159
- Learning to Dispatch Multi-Server Jobs in Bipartite Graphs with Unknown Service Rates / Zhao, H., Deng, S., Chen, F., Yin, J., Dustdar, S., & Zomaya, A. Y. (2022). Learning to Dispatch Multi-Server Jobs in Bipartite Graphs with Unknown Service Rates. arXiv. https://doi.org/10.48550/arXiv.2204.04371
- High-Level Metrics for Service Level Objective-aware Autoscaling in Polaris: a Performance Evaluation / Bartelucci, N., Bellavista, P., Pusztai, T., Morichetta, A., & Dustdar, S. (2022). High-Level Metrics for Service Level Objective-aware Autoscaling in Polaris: a Performance Evaluation. In L. Mashayekhy, S. Schulte, V. Cardellini, B. Kantarci, Y. Simmhan, & B. Varghese (Eds.), 2022 IEEE 6th International Conference on Fog and Edge Computing (ICFEC). IEEE. https://doi.org/10.1109/icfec54809.2022.00017
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Specification and Operation of Privacy Models for Data Streams on the Edge
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Sedlak, B., Murturi, I., & Dustdar, S. (2022). Specification and Operation of Privacy Models for Data Streams on the Edge. In L. Mashayekhy, S. Schulte, V. Cardellini, B. Kantarci, Y. Simmhan, & B. Varghese (Eds.), 2022 IEEE 6th International Conference on Fog and Edge Computing (ICFEC). IEEE. https://doi.org/10.1109/icfec54809.2022.00018
Project: FogProtect (2020–2022) - Quantum Enabled Continuum Enterprise Computing / Dustdar, S. (2022). Quantum Enabled Continuum Enterprise Computing. 2nd SCORE Workshop: Quantum Computing, Sevilla, Spain. http://hdl.handle.net/20.500.12708/87322
- DT4GITM - A Vision for a Framework for Digital Twin enabled IT Governance / Poels, G., Proper, H. A., & Bork, D. (2022). DT4GITM - A Vision for a Framework for Digital Twin enabled IT Governance. In 55th Hawaii International Conference on System Sciences (HICSS´22) (pp. 6626–6635). AIS. http://hdl.handle.net/20.500.12708/58520
Recent Theses
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Distributed Union Find Data Structures for Skewed Data
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Vicevic, V. (2026). Distributed Union Find Data Structures for Skewed Data [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2026.138384
Download: PDF (1.25 MB) -
Designing Cloud Applications for Compatibility: A Case Study on Kubernetes and OpenShift
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Esberger, M. (2026). Designing Cloud Applications for Compatibility: A Case Study on Kubernetes and OpenShift [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2026.123042
Download: PDF (923 KB) - AI in manufacturing : Developing a Federated Machine Learning approach for production machines / Kanev, K. (2026). AI in manufacturing : Developing a Federated Machine Learning approach for production machines [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2026.131969
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Latency-Tiered Hallucination Detection: Optimizing Supervised-Unsupervised Pipelines for RAG Systems
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Rathmayr, M. (2026). Latency-Tiered Hallucination Detection: Optimizing Supervised-Unsupervised Pipelines for RAG Systems [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2026.139744
Download: PDF (2.09 MB) -
Evaluating Extraction-Based RAG: A Systematic Assessment of VerbatimRAG on the CLAPNQ Benchmark
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Kunerth, P. (2026). Evaluating Extraction-Based RAG: A Systematic Assessment of VerbatimRAG on the CLAPNQ Benchmark [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2026.140323
Download: PDF (804 KB) -
Real-time Prevention of Factual Hallucinations in Retrieval-Augmented Generation
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Beccard, L. (2026). Real-time Prevention of Factual Hallucinations in Retrieval-Augmented Generation [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2026.137481
Download: PDF (1.38 MB) -
Limitations of pKVM Isolation Under a Compromised TrustZone: An Evaluation of pKVM as a Trusted Execution Environment
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Kofler, L. (2026). Limitations of pKVM Isolation Under a Compromised TrustZone: An Evaluation of pKVM as a Trusted Execution Environment [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2026.139988
Download: PDF (2.61 MB) - LLM-based automated root-cause analysis for unexpected system behavior / Babic, S. (2026). LLM-based automated root-cause analysis for unexpected system behavior [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2026.126092
- Validating solidity compilers via assertion-driven metamorphic testing / Stromberger, A. M. K. (2026). Validating solidity compilers via assertion-driven metamorphic testing [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2026.138704
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Impact of Knowledge Graph Characteristics on Embedding Performance for Link Prediction
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Kalezic, L. (2026). Impact of Knowledge Graph Characteristics on Embedding Performance for Link Prediction [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2026.132947
Download: PDF (2.21 MB) -
Multi-Model Business Intelligence Exploration for Monitoring and Improving Institutional Reporting
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Schnabl, V. (2026). Multi-Model Business Intelligence Exploration for Monitoring and Improving Institutional Reporting [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2026.139329
Download: PDF (3.77 MB) -
Scalable Life Cycle Management and Deployment of Foundational AI Models for Research Settings
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Taha, J. (2026). Scalable Life Cycle Management and Deployment of Foundational AI Models for Research Settings [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2026.137402
Download: PDF (2.5 MB) -
General Continual Learning through Implicit Contrastive Replays
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Schwartz, S. (2026). General Continual Learning through Implicit Contrastive Replays [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2026.137181
Download: PDF (1.44 MB) -
Project Partner Extraction from Research Contracts
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Prisiazhniuk, A. (2026). Project Partner Extraction from Research Contracts [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2026.132974
Download: PDF (1.07 MB) -
Fairness in Public Screening Models for Hiring Tasks: Benchmarking and Stress Testing under Distribution Shifts
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Loos, A. K. (2026). Fairness in Public Screening Models for Hiring Tasks: Benchmarking and Stress Testing under Distribution Shifts [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2026.135740
Download: PDF (946 KB) -
EdgeSync: Local-First Inference for LLMs in Edge-Cloud Environments
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Kurz, M. (2026). EdgeSync: Local-First Inference for LLMs in Edge-Cloud Environments [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2026.127302
Download: PDF (1 MB) -
Advancing Radiotherapy with AI-Driven Outlier Detection
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Sperlich, R. (2026). Advancing Radiotherapy with AI-Driven Outlier Detection [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2026.137423
Download: PDF (2.14 MB) -
District-Level Prediction of Internal Migration in Austria Using Push/Pull Factors
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Jell, A. (2026). District-Level Prediction of Internal Migration in Austria Using Push/Pull Factors [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2026.132563
Download: PDF (6.03 MB) -
Relational Database Preservation
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Lahnsteiner, P. (2026). Relational Database Preservation [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2026.122572
Download: PDF (1.2 MB) -
Evaluation of Common Data Environment software for BIM
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Winterleitner, F. (2026). Evaluation of Common Data Environment software for BIM [Diploma Thesis, Technische Universität Wien]. reposiTUm. https://doi.org/10.34726/hss.2026.103110
Download: PDF (1.6 MB)
Recent Awards
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Schahram Dustdar:
Paper “Exploring the Potential of Distributed Computing Continuum Systems” (authors: Praveen Kumar Donta, Ilir Murturi, Victor Casamayor Pujol, Boris Sedlak, Schahram Dustdar), featured in a special edition of Computers entitled “Editor’s Choice Articles”
2025 / MDPI Computers / Switzerland -
Schahram Dustdar:
2024 Highly Ranked Scholar by ScholarGPS: Place in the top 0.05% of all scholars worldwide
2025 / ScholarGPS / USA -
Schahram Dustdar:
WILEY Top Viewed Article in Software: Practice and Experience: Raith P., Rausch T., Furutanpey A., Dustdar S. (2023) “faas-sim: A trace-driven simulation framework for serverless edge computing platforms” (Among work published in Software: Practice and Experience between January 1 - December 31, 2023, up to 12 months after publication)
2025 / USA -
Dominik Bork:
Best Reviewer Award for the SoSyM Journal 2024
2025 / Software and Systems Modeling Journal / USA -
Schahram Dustdar:
President
2024 / International Artificial Intelligence Industry Alliance (AIIA) / China -
Dominik Bork:
Eclipse Cloud DevTools Contributor Award
2023 / Eclipse Foundation / USA -
Dominik Bork:
Best Student Paper Award at EDOC 2023
2023 / 27th International EDOC Conference / Netherlands -
Dominik Bork:
Best Reviewer Award for the SoSyM Journal 2022
2023 / Software and Systems Modeling Journal / USA -
Dominik Bork:
Best Reviewer Award at the Modellierung 2022
2022 / Modellierung 2022 Conference Committee / Germany -
Dominik Bork:
Best Reviewer Award for the SoSyM Journal 2021
2022 / Software and Systems Modeling Journal / USA -
Schahram Dustdar:
EAI Fellow
2021 / EAI / Belgium / Website -
Schahram Dustdar:
IEEE TCI 2021 Distinguished Service Award
2021 / IEEE Technical Committee on the Internet / USA / Website -
Schahram Dustdar:
I2CICC Fellow for Contributions to Cognitive Informatics, Cognitive Computing, and General AI
2021 / I2CICC, University of Calgary, Canada / Canada / Website -
Nikolas Popper:
Österreicher des Jahres, Bereich Forschung
2021 / Österreicher:innen des Jahres / Austria / Website -
Schahram Dustdar:
Francqui Chair Professor at University of Namur
2021 / Belgium / Website -
Schahram Dustdar:
Asia-Pacific Artificial Intelligence Association (AAIA) President (2021-2023)
2021 / China -
Nikolas Popper:
Gerhart-Bruckmann-Preis 2021
2021 / Gerhart-Bruckmann-Preis / Austria / Website -
Schahram Dustdar:
Asia-Pacific Artificial Intelligence Association (AAIA) Fellow
2021 / China / Website -
Schahram Dustdar:
Research Excellence Award for delivering a keynote at the 21st IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing, CCGrid 2021
2021 / CCGrid 2021 General Chair Prof. Rajkumar Buyya / Australia -
Schahram Dustdar:
Best Paper Award: Aslanpour M. S., Toosi A. N., Cicconetti C., Javadi B., Sbarski P., Taibi D., Assuncao M., Gill S. S., Gaire R., Dustdar S. (2021). Serverless Edge Computing: Vision and Challenges. 19th Australasian Symposium on Parallel and Distributed Computing (AusPDC 2021), February 1-5, 2021, (Dunedin, New Zealand) online because of COVID-19 (Coronavirus)
2021 / Australia