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Informatics Institute Informatics Institute

Dr Z. (Zhiming) Zhao

Associate professor
Faculty of Science
Informatics Institute
Visiting address
  • Science Park 904
  • Room number: L5.40
Postal address
  • Postbus 94323
    1090 GH Amsterdam
Contact details
Social media
  • About
    Personal page

    Dr. Zhiming Zhao is an associate professor and the chair of the Multiscale Network Systems (MNS) research group in the Informatics Institute (IvI) at UvA. He is the technical manager of the Virtual Lab and Innovation Center (VLIC) of LifeWatch ERIC, a European research infrastructure in ecology and biodiversity science.

    His research focuses on quality-critical distributed computing, data-intensive workflow management, virtual research environments, and digital twins. He is the Co-PI of the Dutch LTER-LIFE project and coordinate the UvA effort in EU projects ENVRI-HUB next, EVERSE, OSCARS and BlueCloud 2026 to develop Digital Twin Virtual Research Environment, research assets search engine, and Cloud automation and optimization solutions.

    He is an IEEE Senior member and the managing editor of the Journal of Cloud Computing.

     

  • Publications

    2025

    • Wang, Y., Tripathi, S., Farshidi, S., & Zhao, Z. (2025). D-VRE: From a Jupyter-enabled Private Research Environment to Decentralized Collaborative Research Ecosystem. Blockchain: Research and Applications, 6(1), Article 100244. https://doi.org/10.1016/j.bcra.2024.100244 [details]
    • Zhao, Z., Kissling, W. D., Hengeveld, G. M., Athanasiadis, I., Soetaert, K., & Hof, A. (2025). A Virtual Lab Maturity Model for Guiding the Co-Development of Advanced Virtual Research Environments. In Proceedings - 19th IEEE International Conference on Service-Oriented System Engineering, SOSE 2025 (pp. 20-26). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SOSE67019.2025.00007

    2024

    • Cheng, L., Chen, X., & Zhao, Z. (2024). Preface of special issue on Artificial Intelligence for time-critical computing systems. Future Generation Computer Systems, 159, 102-104. https://doi.org/10.1016/j.future.2024.05.011 [details]
    • Cheng, L., Wang, Y., Cheng, F., Liu, C., Zhao, Z., & Wang, Y. (2024). A Deep Reinforcement Learning-Based Preemptive Approach for Cost-Aware Cloud Job Scheduling. IEEE Transactions on Sustainable Computing, 9(3), 422-432. https://doi.org/10.1109/TSUSC.2023.3303898 [details]
    • Hou, S., Wang, Y., & Zhao, Z. (2024). CrowdAL: Towards a Blockchain-empowered Active Learning System in Crowd Data Labeling. In EScience '24 proceedings: 2024 IEEE 20th International Conference on e-Science (e-Science) : September 16-20, 2024, Osaka, Japan (pp. 299-300). IEEE. https://doi.org/10.1109/e-science62913.2024.10678683 [details]
    • Jiang, W., Chen, K., Liang, Z., Luo, T., Yue, G., Zhao, Z., Song, W., Zhao, L., & Wen, J. (2024). HT-RCM: Hashimoto's Thyroiditis Ultrasound Image Classification Model Based on Res-FCT and Res-CAM. IEEE Journal of Biomedical and Health Informatics, 28(2), 941-951. https://doi.org/10.1109/JBHI.2023.3331944 [details]
    • Jiang, W., Luo, T., Liang, Z., Chen, K., He, J., Zhao, Z., Wen, J., Zhao, L., & Song, W. (2024). FBENet: Feature-Level Boosting Ensemble Network for Hashimoto’s Thyroiditis Ultrasound Image Classification. IEEE Journal of Biomedical and Health Informatics, 28(9), 5360–5369. https://doi.org/10.1109/jbhi.2024.3414389 [details]
    • Krishnasamy, A., Wang, Y., & Zhao, Z. (2024). A Collaborative Framework for Facilitating Federated Learning among Jupyter Users. In EScience '24 proceedings: 2024 IEEE 20th International Conference on e-Science (e-Science) : September 16-20, 2024, Osaka, Japan (pp. 305-306). IEEE. https://doi.org/10.1109/e-science62913.2024.10678679 [details]
    • Li, N., Qi, Y., Li, C., & Zhao, Z. (2024). Active Learning for Data Quality Control: A Survey. Journal of Data and Information Quality, 16(2), 1–45. https://doi.org/10.1145/3663369
    • Pan, R., Shi, Z., Belloum, A., & Zhao, Z. (2024). Operating ZKPs on Blockchain: A Performance Analysis Based on Hyperledger Fabric. In 2024 IEEE International Conference on Decentralized Applications and Infrastructures: DAPPS 2024 : proceedings : 15-18 July 2024, Shanghai, China (pp. 69-78). IEEE Computer Society. https://doi.org/10.1109/DAPPS61106.2024.00018 [details]
    • Petzold, A., Bundke, U., Hienola, A., Laj, P., Lund Myhre, C., Vermeulen, A., Adamaki, A., Kutsch, W., Thouret, V., Boulanger, D., Fiebig, M., Stocker, M., Zhao, Z., & Asmi, A. (2024). Opinion: New directions in atmospheric research offered by research infrastructures combined with open and data-intensive science. Atmospheric Chemistry and Physics, 24(9), 5369-5388. https://doi.org/10.5194/acp-24-5369-2024 [details]
    • Song, Y., Xin, R., Chen, P., Zhang, R., Chen, J., & Zhao, Z. (2024). Autonomous selection of the fault classification models for diagnosing microservice applications. Future Generation Computer Systems, 153, 326-339. https://doi.org/10.1016/j.future.2023.12.005 [details]
    • Wang, Y., Kanwal, N., Engan, K., Rong, C., Grosso, P., & Zhao, Z. (2024). PriCE: Privacy-Preserving and Cost-Effective Scheduling for Parallelizing the Large Medical Image Processing Workflow over Hybrid Clouds. In J. Carretero, S. Shende, J. Garcia-Blas, I. Brandic, K. Olcoz, & M. Schreiber (Eds.), Euro-Par 2024: Parallel Processing: 30th European Conference on Parallel and Distributed Processing, Madrid, Spain, August 26–30, 2024 : proceedings (Vol. I, pp. 210-224). (Lecture Notes in Computer Science; Vol. 14801), (Advanced Research in Computing and Software Science). Springer. https://doi.org/10.1007/978-3-031-69577-3_15 [details]
    • Xin, R., Chen, P., Grosso, P., & Zhao, Z. (2024). A fine-grained robust performance diagnosis framework for run-time cloud applications. Future Generation Computer Systems, 155, 300-311. https://doi.org/10.1016/j.future.2024.02.014 [details]
    • Yuan, S., Chen, J., Jiang, W., Zhao, Z., & Guo, S. (2024). LHNetV2: A Balanced Low-Cost Hybrid Network for Single Image Dehazing. IEEE Transactions on Multimedia, 26, 8197-8209. https://doi.org/10.1109/tmm.2024.3377133 [details]
    • Zhu, P., Li, N., & Zhao, Z. (2024). Retrieval-augmented Query Reformulation for Heterogeneous Research Asset Retrieval in Virtual Research Environment. In WWW '24 Companion: Companion proceedings of the ACM Web Conference 2024 : May 13-17, 2024, Singapore, Singapore (pp. 907–910). The Association for Computing Machinery. https://doi.org/10.1145/3589335.3651553 [details]
    • van de Kamp, R., Bakker, K., & Zhao, Z. (2024). Paving the Path Towards Platform Engineering Using a Comprehensive Reference Model. In T. Prince Sales, S. de Kinderen, H. A. Proper, L. Pufahl, D. Karastoyanova, & M. van Sinderen (Eds.), Enterprise Design, Operations, and Computing. EDOC 2023 Workshops: IDAMS, iRESEARCH, MIDas4CS, SoEA4EE, EDOC Forum, Demonstrations Track and Doctoral Consortium, Groningen, The Netherlands, October 30–November 3, 2023 : revised selected papers (pp. 177–193). (Lecture Notes in Business Information Processing; Vol. 498). Springer. https://doi.org/10.1007/978-3-031-54712-6_11 [details]

    2023

    • Chen, S., Huang, G., Lin, S., Jiang, W., & Zhao, Z. (2023). Overlapping Community Discovery Algorithm Based on Three-Level Neighbor Node Influence. In Y. Xu, H. Yan, H. Teng, J. Cai, & J. Li (Eds.), Machine Learning for Cyber Security: 4th International Conference, ML4CS 2022, Guangzhou, China, December 2–4, 2022 : proceedings (Vol. II, pp. 335-344). (Lecture Notes in Computer Science; Vol. 13656). Springer. https://doi.org/10.1007/978-3-031-20099-1_28 [details]
    • Christou, V., Wang, Y., & Zhao, Z. (2023). Towards a Knowledge Graph Enhanced Automation and Collaboration Framework for Digital Twins. In 2023 IEEE 19th International Conference on e-Science: (e-Science) : October 9-14, 2023, Limassol, Cyprus : proceedings (pp. 465-466). Article 62 IEEE. https://doi.org/10.1109/e-Science58273.2023.10254845 [details]
    • Farshidi, S., Liao, X., Li, N., Goldfarb, D., Magagna, B., Stocker, M., Jeffery, K., Thijsse, P., Pichot, C., Petzold, A., & Zhao, Z. (2023). Knowledge sharing and discovery across heterogeneous research infrastructures. Open Research Europe, 1, Article 68. https://doi.org/10.12688/openreseurope.13677.3 [details]
    • Fuertes Blanco, A., Shi, Z., Roy, D., & Zhao, Z. (2023). Improving the Resiliency of Decentralized Crowdsourced Blockchain Oracles. In J. Mikyška, C. de Mulatier, M. Paszynski, V. V. Krzhizhanovskaya, J. J. Dongarra, & P. M. A. Sloot (Eds.), Computational Science – ICCS 2023: 23rd International Conference, Prague, Czech Republic, July 3–5, 2023 : proceedings (Vol. I, pp. 3-17). (Lecture Notes in Computer Science; Vol. 14073). Springer. https://doi.org/10.1007/978-3-031-35995-8_1 [details]
    • Geng, J., Chen, Z., Wang, Y., Woisetschläger, H., Schimmler, S., Mayer, R., Zhao, Z., & Rong, C. (2023). A Survey on Dataset Distillation: Approaches, Applications and Future Directions. In E. Elkind (Ed.), Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence: IJCAI 2023, Macao, S.A.R, 19-25 August 2023 (Vol. 10, pp. 6610-6618). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2023/741 [details]
    • Kontomaris, C., Wang, Y., & Zhao, Z. (2023). CWL-FLOps: A Novel Method for Federated Learning Operations at Scale. In 2023 IEEE 19th International Conference on e-Science: (e-Science) : October 9-14, 2023, Limassol, Cyprus : proceedings (pp. 479-480). Article 69 IEEE. https://doi.org/10.1109/e-Science58273.2023.10254788 [details]
    • La Marra, M., Blanson Henkemans, D., Titocci, J., Koulouzis, S., Rosati, I., & Zhao, Z. (2023). Integrating R in a distributed scientific workflow via a Jupyter-based Environment. In 2023 IEEE 19th International Conference on e-Science: (e-Science) : October 9-14, 2023, Limassol, Cyprus : proceedings (pp. 481-482). Article 70 IEEE. https://doi.org/10.1109/e-Science58273.2023.10254945 [details]
    • Launet, L., Wang, Y., Colomer, A., Igual, J., Pulgarín-Ospina, C., Koulouzis, S., Bianchi, R., Mosquera-Zamudio, A., Monteagudo, C., Naranjo, V., & Zhao, Z. (2023). Federating Medical Deep Learning Models from Private Jupyter Notebooks to Distributed Institutions. Applied Sciences, 13(2), Article 919. https://doi.org/10.3390/app13020919 [details]
    • Li, J., Li, J., Xie, C., Liang, Y., Qu, K., Cheng, L., & Zhao, Z. (2023). PipCKG-BS: A Method to Build Cybersecurity Knowledge Graph for Blockchain Systems via the Pipeline Approach. Journal of Circuits, Systems and Computers, 32(16), Article 2350274. https://doi.org/10.1142/S0218126623502742 [details]
    • Li, N., Zhang, Y., & Zhao, Z. (2023). A Dense Retrieval System and Evaluation Dataset for Scientific Computational Notebooks. In 2023 IEEE 19th International Conference on e-Science: (e-Science) : October 9-14, 2023, Limassol, Cyprus : proceedings (pp. 179-188). Article 19 IEEE. https://doi.org/10.1109/e-Science58273.2023.10254859 [details]
    • Li, N., Zhang, Y., & Zhao, Z. (2023). CNSVRE: A Query Reformulated Search System with Explainable Summarization for Virtual Research Environment. In The ACM Web Conference 2023: Companion of the World Wide Web Conference WWW 2023 : April 30-May 4, 2023, Austin, Texas, USA (pp. 254-257). Association for Computing Machinery. https://doi.org/10.1145/3543873.3587360 [details]
    • Liu, H., Chen, P., Ouyang, X., Gao, H., Yan, B., Grosso, P., & Zhao, Z. (2023). Robustness challenges in Reinforcement Learning based time-critical cloud resource scheduling: A Meta-Learning based solution. Future Generation Computer Systems, 146, 18-33. https://doi.org/10.1016/j.future.2023.03.029 [details]
    • Liu, H., Oudejans, M., Xin, R., Grosso, P., & Zhao, Z. (2023). A Performance-Adaptive and Time-Monitored Autonomous Ticket Booking Service in Cloud. In 2023 IEEE 32nd International Symposium on Industrial Electronics (ISIE): 19-21 June, 2023, Helsinki-Espoo, Finland : proceedings (pp. 940-945). IEEE. https://doi.org/10.1109/ISIE51358.2023.10228152 [details]
    • Liu, H., Xin, R., Chen, P., Gao, H., Grosso, P., & Zhao, Z. (2023). Robust-PAC time-critical workflow offloading in edge-to-cloud continuum among heterogeneous resources. Journal of Cloud Computing, 12, Article 58. https://doi.org/10.1186/s13677-023-00434-6 [details]
    • Rito Lima, I., Filipe, V., Marinho, C., Ulisses, A., Chakravorty, A., Hristov, A., Saurabh, N., Zhao, Z., Xin, R., & Prodan, R. (2023). ARTICONF decentralized social media platform for democratic crowd journalism. Social Network Analysis and Mining, 13, Article 116. https://doi.org/10.1007/s13278-023-01110-y [details]
    • Shi, Z., de Laat, C., Grosso, P., & Zhao, Z. (2023). Integration of Blockchain and Auction Models: A Survey, Some Applications, and Challenges. IEEE Communications Surveys and Tutorials, 25(1), 497-537. https://doi.org/10.1109/COMST.2022.3222403 [details]
    • Song, Y., Xin, R., Chen, P., Zhang, R., Chen, J., & Zhao, Z. (2023). Identifying performance anomalies in fluctuating cloud environments: A robust correlative-GNN-based explainable approach. Future Generation Computer Systems, 145, 77-86. https://doi.org/10.1016/j.future.2023.03.020 [details]
    • Tabatabaei, Z., Wang, Y., Colomer, A., Oliver Moll, J., Zhao, Z., & Naranjo, V. (2023). WWFedCBMIR: World-Wide Federated Content-Based Medical Image Retrieval. Bioengineering, 10(10), Article 1144. https://doi.org/10.3390/bioengineering10101144 [details]
    • Wang, Y., Janse, N., Bianchi, R., Koulouzis, S., & Zhao, Z. (2023). Towards a Service-based Adaptable Data Layer for Cloud Workflows. In H. Shahriar, Y. Teranishi, A. Cuzzocrea, M. Sharmin, D. Towey, A. K. M. J. A. Majumder, H. Kashiwazaki, J.-J. Yang, M. Takemoto, N. Sakib, R. Banno, & S. I. Ahamed (Eds.), 2023 IEEE 47th Annual Computers, Software, and Applications Conference: 27-29 June 2023, Torino, Italy : proceedings (pp. 904-911). (COMPSAC; Vol. 2023). IEEE Computer Society. https://doi.org/10.1109/COMPSAC57700.2023.00121 [details]
    • Wang, Y., Kanwal, N., Engan, K., Rong, C., & Zhao, Z. (2023). Towards a Privacy-Preserving Distributed Cloud Service for Preprocessing Very Large Medical Images. In C. K. Chang, R. N. Chang, J. Fan, G. C. Fox, Z. Jin, G. Pravadelli, & H. Shahriar (Eds.), 2023 IEEE International Conference on Digital Health: IEEE ICDH 2023 : hybrid conference, Chicago, Illinois, 2-8 July 2023 : proceedings (pp. 325-327). IEEE Computer Society. https://doi.org/10.1109/ICDH60066.2023.00055 [details]
    • Xin, R., Chen, P., & Zhao, Z. (2023). CausalRCA: Causal inference based precise fine-grained root cause localization for microservice applications. Journal of Systems and Software, 203, Article 111724. https://doi.org/10.1016/j.jss.2023.111724 [details]
    • Xin, R., Liu, H., Chen, P., & Zhao, Z. (2023). Robust and accurate performance anomaly detection and prediction for cloud applications: a novel ensemble learning-based framework. Journal of Cloud Computing, 12, Article 7. https://doi.org/10.1186/s13677-022-00383-6 [details]
    • Zhang, J., Cheng, L., Liu, C., Zhao, Z., & Mao, Y. (2023). Cost-aware scheduling systems for real-time workflows in cloud: An approach based on Genetic Algorithm and Deep Reinforcement Learning. Expert Systems With Applications, 234, Article 120972. https://doi.org/10.1016/j.eswa.2023.120972 [details]
    • Zhu, Z., Ai, C., Chen, H., Chen, B., Duan, W., Qiu, X., Lu, X., He, M., Zhao, Z., & Liu, Z. (2023). Understanding the Necessity and Economic Benefits of Lockdown Measures to Contain COVID-19. IEEE Transactions on Computational Social Systems, 10(4), 1888-1900. https://doi.org/10.1109/TCSS.2022.3194639 [details]

    2022

    • Boyko, A., Farshidi, S., & Zhao, Z. (2022). An Adaptable Framework for Entity Matching Model Selection in Business Enterprises. In 2022 IEEE 24th Conference on Business Informatics: CBI 2022 : proceedings : Amsterdam, The Netherlands, 15-17 June 2022 (Vol. 1, pp. 90-99). IEEE Computer Society. https://doi.org/10.1109/CBI54897.2022.00017 [details]
    • Chen, P., Liu, H., Xin, R., Carval, T., Zhao, J., Xia, Y., & Zhao, Z. (2022). Effectively Detecting Operational Anomalies In Large-Scale IoT Data Infrastructures By Using A GAN-Based Predictive Model. Computer Journal, 65(11), 2909-2925. https://doi.org/10.1093/comjnl/bxac085 [details]
    • Farshidi, S., & Zhao, Z. (2022). An Adaptable Indexing Pipeline for Enriching Meta Information of Datasets from Heterogeneous Repositories. In J. Gama, T. Li, Y. Yu, E. Chen, Y. Zheng, & F. Teng (Eds.), Advances in Knowledge Discovery and Data Mining: 26th Pacific-Asia Conference, PAKDD 2022, Chengdu, China, May 16–19, 2022 : proceedings (Vol. II, pp. 472-484). (Lecture Notes in Computer Science; Vol. 13281), (Lecture Notes in Artificial Intelligence). Springer. https://doi.org/10.1007/978-3-031-05936-0_37 [details]
    • Hoogenkamp, B., Farshidi, S., Xin, R., Shi, Z., Chen, P., & Zhao, Z. (2022). A Decentralized Service Control Framework for Decentralized Applications in Cloud Environments. In F. Montesi, G. A. Papadopoulos, & W. Zimmermann (Eds.), Service-Oriented and Cloud Computing: 9th IFIP WG 6.12 European Conference, ESOCC 2022, Wittenberg, Germany, March 22–24, 2022 : proceedings (pp. 65-73). (Lecture Notes in Computer Science; Vol. 13226). Springer. https://doi.org/10.1007/978-3-031-04718-3_4 [details]
    • Ivankovic, V., Shi, Z., & Zhao, Z. (2022). A Customizable dApp Framework for User Interactions in Decentralized Service Marketplaces. In 2022 IEEE International Conference on Smart Internet of Things: IEEE SmartIoT 2022 : proceedings : 19-21 August 2022, Suzhou, China, hybrid conference (onsite and virtual) (pp. 224-231). IEEE Computer Society. https://doi.org/10.1109/SmartIoT55134.2022.00043 [details]
    • Jiang, W., Pan, S., Lu, C., Zhao, Z., Lin, S., Xiong, M., & He, Z. (2022). Label entropy-based cooperative particle swarm optimization algorithm for dynamic overlapping community detection in complex networks. International Journal of Intelligent Systems, 37(2), 1371-1407. https://doi.org/10.1002/int.22673 [details]
    • Koulouzis, S., Bianchi, R., van der Linde, R., Wang, Y., & Zhao, Z. (2022). SPIRIT: A Microservice-Based Framework for Interactive Cloud Infrastructure Planning. In R. Chaves, D. B. Heras, A. Ilic, & D. Unat (Eds.), Euro-Par 2021: Parallel Processing Workshops: Euro-Par 2021 International Workshops, Lisbon, Portugal, August 30-31, 2021 : revised selected papers (pp. 405-416). (Lecture Notes in Computer Science; Vol. 13098). Springer. https://doi.org/10.1007/978-3-031-06156-1_32 [details]
    • Launet, L., del Amor, R., Colomer, A., Mosquera-Zamudio, A., Moscardó, A., Monteagudo, C., Zhao, Z., & Naranjo, V. (2022). Federating Unlabeled Samples: A Semi-supervised Collaborative Framework for Whole Slide Image Analysis. In H. Yin, D. Camacho, & P. Tino (Eds.), Intelligent Data Engineering and Automated Learning – IDEAL 2022: 23rd International Conference, IDEAL 2022, Manchester, UK, November 24–26, 2022 : proceedings (pp. 64-72). (Lecture Notes in Computer Science; Vol. 13756). Springer. https://doi.org/10.1007/978-3-031-21753-1_7 [details]
    • Li, M., Su, J., Liu, H., Zhao, Z., Ouyang, X., & Zhou, H. (2022). The Extreme Counts: Modeling the Performance Uncertainty of Cloud Resources with Extreme Value Theory. In J. Troya, B. Medjahed, M. Piattini, L. Yao, P. Fernández, & A. Ruiz-Cortés (Eds.), Service-Oriented Computing: 20th International Conference, ICSOC 2022, Seville, Spain, November 29–December 2, 2022 : proceedings (pp. 498-512). (Lecture Notes in Computer Science; Vol. 13740). Springer. https://doi.org/10.1007/978-3-031-20984-0_35 [details]
    • Li, N., Farshidi, S., Bianchi, R., Koulouzis, S., & Zhao, Z. (2022). Context-Aware Notebook Search in a Jupyter-Based Virtual Research Environment. In eScience '22 : Democratizing science : 2022 IEEE 18th International Conference on e-Science: proceedings : eScience 2022 : Salt Lake City, Utah, USA, 10-14 October 202 (pp. 393-394). Conference Publishing Services, IEEE Computer Society. https://doi.org/10.1109/eScience55777.2022.00054 [details]
    • Liu, H., Xin, R., Chen, P., & Zhao, Z. (2022). Multi-Objective Robust Workflow Offloading in Edge-to-Cloud Continuum. In C. A. Ardagna, N. Atukorala, R. Buyya, C. K. Chang, R. N. Chang, E. Damiani, G. B. Dasgupta, F. Gagliardi, C. Hagleitner, D. Milojicic, T. M. H. Trong, R. Ward, F. Xhafa, & J. Zhang (Eds.), 2022 IEEE 15th International Conference on Cloud Computing (IEEE CLOUD 2022): proceedings : hybrid conference, Barcelona, Spain, 11-15 July 2022 (pp. 469-478). IEEE Computer Society. https://doi.org/10.1109/CLOUD55607.2022.00070 [details]
    • Rito Lima, I., Marinho, C., Filipe, V., Ulisses, A., Saurabh, N., Chakravorty, A., Zhao, Z., Hristov, A., & Prodan, R. (2022). MOGPlay: A Decentralized Crowd Journalism Application for Democratic News Production. In J. An, C. Charalampos, & W. Magdy (Eds.), Proceedings of the 2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining: ASONAM 2022 : FAB 2022, FOSINT-SI 2022, HI-BI-BI 2022 : Istanbul, Turkey (Hybrid), November 10-13, 2022 (pp. 462-469). IEEE. https://doi.org/10.1109/ASONAM55673.2022.10068697 [details]
    • Shi, Z., Ivankovic, V., Farshidi, S., Surbiryala, J., Zhou, H., & Zhao, Z. (2022). AWESOME: an auction and witness enhanced SLA model for decentralized cloud marketplaces. Journal of Cloud Computing, 11, Article 27. https://doi.org/10.1186/s13677-022-00292-8 [details]
    • Shi, Z., Zhou, H., de Laat, C., & Zhao, Z. (2022). A Bayesian game-enhanced auction model for federated cloud services using blockchain. Future Generation Computer Systems, 136, 49-66. https://doi.org/10.1016/j.future.2022.05.017 [details]
    • Song, Y., Xin, R., Zhang, R., Chen, J., & Zhao, Z. (2022). A Robust and Accurate Multivariate Time Series Anomaly Detection in Fluctuating Cloud-Edge Computing Systems. In Proceedings: 24th IEEE International Conference on High Performance Computing & Communications; 8th IEEE International Conference on Data Science & Systems; 20th IEEE International Conference on Smart City; 8th IEEE International Conference on Dependability in Sensor, Cloud & Big Data Systems & Application: HPCC/DSS/SmartCity/DependSys : 18-21 December 2022, Chengdu, China (pp. 357-365). IEEE Computer Society. https://doi.org/10.1109/HPCC-DSS-SmartCity-DependSys57074.2022.00077 [details]
    • Wang, Y., Koulouzis, S., Bianchi, R., Li, N., Shi, Y., Timmermans, J., Kissling, W. D., & Zhao, Z. (2022). Scaling Notebooks as Re-configurable Cloud Workflows. Data Intelligence, 4(2), 409-425. https://doi.org/10.1162/dint_a_00140 [details]
    • Wittenburg, P., Hardisty, A., Franc, Y. L., Mozaffari, A., Peer, L., Skvortsov, N. A., Zhao, Z., & Spinuso, A. (2022). Canonical Workflows to Make Data FAIR. Data Intelligence, 4(2), 286-305. https://doi.org/10.1162/dint_a_00132 [details]
    • Wittenburg, P., Hardisty, A., Mozzafari, A., Peer, L., Skvortsov, N., Spinuso, A., & Zhao, Z. (2022). Editors’ Note: Special Issue on Canonical Workflow Frameworks for Research. Data Intelligence, 4(2), 149-154. https://doi.org/10.1162/dint_e_00122 [details]
    • Xiao, H., Li, P., Zeng, H., Liang, T., Jiang, W., & Zhao, Z. (2022). Metric learning‐based whole health indicator model for industrial robots. International Journal of Intelligent Systems, 37(11), 9508-9519. https://doi.org/10.1002/int.23008 [details]
    • Xin, R., Mohazzab, J., Shi, Z., & Zhao, Z. (2022). CBProf: Customisable Blockchain-as-a-Service Performance Profiler in Cloud Environments. In K. Lee, & L.-J. Zhang (Eds.), Blockchain – ICBC 2021: 4th International Conference, held as part of the Services Conference Federation, SCF 2021, virtual event, December 10–14, 2021 : proceedings (pp. 131-139). (Lecture Notes in Computer Science; Vol. 12991). Springer. https://doi.org/10.1007/978-3-030-96527-3_9 [details]
    • Xin, R., Stallinga, S., Liu, H., Chen, P., & Zhao, Z. (2022). Provenance-enhanced Root Cause Analysis for Jupyter Notebooks. In 2022 IEEE/ACM 15th International Conference on Utility and Cloud Computing: UCC 2022 : Vancouver, Washington, USA, 6-9 December 2022 : proceedings (pp. 327-333). IEEE. https://doi.org/10.1109/UCC56403.2022.00058, https://doi.org/10.1109/UCC56403.2022.00058 [details]
    • Yuan, S., Wang, Y., Liang, T., Jiang, W., Lin, S., & Zhao, Z. (2022). Real‐time recognition and warning of mask wearing based on improved YOLOv5 R6.1. International Journal of Intelligent Systems, 37(11), 9309-9338. https://doi.org/10.1002/int.22994 [details]
    • Zhang, L., Jiang, W., & Zhao, Z. (2022). Short‐text feature expansion and classification based on nonnegative matrix factorization. International Journal of Intelligent Systems, 37(12), 10066-10080. Advance online publication. https://doi.org/10.1002/int.22290 [details]
    • Zhao, Z., Koulouzis, S., Bianchi, R., Farshidi, S., Shi, Z., Xin, R., Wang, Y., Li, N., Shi, Y., Timmermans, J., & Kissling, W. D. (2022). Notebook-as-a-VRE (NaaVRE): From private notebooks to a collaborative cloud virtual research environment. Software - Practice and Experience, 52(9), 1947-1966. https://doi.org/10.1002/spe.3098 [details]
    • Zhu, Z., Chen, B., Chen, H., Qiu, S., Fan, C., Zhao, Y., Guo, R., Ai, C., Liu, Z., Zhao, Z., Fang, L., & Lu, X. (2022). Strategy evaluation and optimization with an artificial society toward a Pareto optimum. The Innovation, 3(5), Article 100274. https://doi.org/10.1016/j.xinn.2022.100274 [details]

    2021

    • Bergers, J., Shi, Z., Korsmit, K., & Zhao, Z. (2021). DWH-DIM: A Blockchain Based Decentralized Integrity Verification Model for Data Warehouses. In Y. Xiang, Z. Wang, H. Wang, & V. Niemi (Eds.), 2021 IEEE International Conference on Blockchain : Blockchain 2021: proceedings : 6-8 December 2021, Melbourne, Australia (pp. 221-228). IEEE Computer Society. https://doi.org/10.1109/Blockchain53845.2021.00037 [details]
    • Calyam, P., Wilkins‐Diehr, N., Miller, M., Brookes, E. H., Arora, R., Chourasia, A., Jennewein, D. M., Nandigam, V., LaMar, M. D., Cleveland, S. B., Newman, G., Wang, S., Zaslavsky, I., Cianfrocco, M. A., Ellett, K., Tarboton, D., Jeffery, K. G., Zhao, Z., González‐Aranda, J., ... Gesing, S. (2021). Measuring success for a future vision: Defining impact in science gateways/virtual research environments. Concurrency and Computation: Practice and Experience, 33(19), Article e6099. https://doi.org/10.1002/cpe.6099 [details]
    • Karandikar, N., Abhishek, R., Saurabh, N., Zhao, Z., Lercher, A., Marina, N., Prodan, R., Rong, C., & Chakravorty, A. (2021). Blockchain-based prosumer incentivization for peak mitigation through temporal aggregation and contextual clustering. Blockchain: Research and Applications, 2(2), Article 100016. https://doi.org/10.1016/j.bcra.2021.100016 [details]
    • Liu, H., Chen, P., & Zhao, Z. (2021). Towards A Robust Meta-Reinforcement Learning-Based Scheduling Framework for Time Critical Tasks in Cloud Environments. In C. A. Ardagna, C. Chang, E. Daminai, R. Ranjan, Z. Wang, R. Ward, J. Zhang, & W. Zhang (Eds.), 2021 IEEE 14th International Conference on Cloud Computing: CLOUD 2021 : proceedings : virtual conference, 5-11 September 2021 (pp. 637-647). IEEE Computer Society. https://doi.org/10.1109/CLOUD53861.2021.00082 [details]
    • Poon, L., Farshidi, S., Li, N., & Zhao, Z. (2021). Unsupervised Anomaly Detection in Data Quality Control. In Y. Chen, H. Ludwig, Y. Tu, U. Fayyad, X. Zhu, X. Hu, S. Byna, X. Liu, J. Zhang, S. Pan, V. Papalexakis, J. Wang, A. Cuzzocrea, & C. Ordonez (Eds.), 2021 IEEE International Conference on Big Data: proceedings : Dec 15-Dec 18, 2021 : virtual event (pp. 2327-2336). IEEE. https://doi.org/10.1109/BigData52589.2021.9671672 [details]
    • Saurabh, N., Rubia, C., Palanisamy, A., Koulouzis, S., Sefidanoski, M., Chakravorty, A., Zhao, Z., Karadimce, A., & Prodan, R. (2021). The ARTICONF approach to decentralized car-sharing. Blockchain: Research and Applications, 2(3), Article 100013. https://doi.org/10.1016/j.bcra.2021.100013 [details]
    • Shi, Z., Farshidi, S., Zhou, H., & Zhao, Z. (2021). An auction and witness enhanced trustworthy SLA model for decentralized cloud marketplaces. In GoodIT '21: proceedings of the Conference on Information Technology for Social Good : September 9-11, 2021, Roma, Italy (pp. 109-114). The Association for Computing Machinery. https://doi.org/10.1145/3462203.3475876, https://doi.org/10.1145/3462203.3475876 [details]
    • Uriarte, R. B., Zhou, H., Kritikos, K., Shi, Z., Zhao, Z., & De Nicola, R. (2021). Distributed service‐level agreement management with smart contracts and blockchain. Concurrency and Computation: Practice and Experience, 33(14), Article e5800. https://doi.org/10.1002/cpe.5800 [details]
    • Zhou, H., Ouyang, X., Su, J., de Laat, C., & Zhao, Z. (2021). Enforcing trustworthy cloud SLA with witnesses: A game theory–based model using smart contracts. Concurrency and Computation: Practice and Experience, 33(14), Article e5511. https://doi.org/10.1002/cpe.5511 [details]
    • Zhou, H., Shi, Z., Ouyang, X., & Zhao, Z. (2021). Building a blockchain-based decentralized ecosystem for cloud and edge computing: an ALLSTAR approach and empirical study. Peer-to-Peer Networking and Applications, 14(6), 3578-3594. https://doi.org/10.1007/s12083-021-01198-z [details]
    • Zhu, Z., Chen, B., Liu, W., Zhao, Y., Liu, Z., & Zhao, Z. (2021). A Cost-Quality Beneficial Cell Selection Approach for Sparse Mobile Crowdsensing with Diverse Sensing Costs. IEEE Internet of Things Journal, 8(5), 3831-3850. https://doi.org/10.1109/JIOT.2020.3024833 [details]

    2020

    • Hu, Y., Zhou, H., de Laat, C., & Zhao, Z. (2020). Concurrent container scheduling on heterogeneous clusters with multi-resource constraints. Future Generation Computer Systems, 102, 562-573. https://doi.org/10.1016/j.future.2019.08.025 [details]
    • Jeffery, K., Pursula, A., & Zhao, Z. (2020). ICT Infrastructures for Environmental and Earth Sciences. In Z. Zhao, & M. Hellström (Eds.), Towards Interoperable Research Infrastructures for Environmental and Earth Sciences: A Reference Model Guided Approach for Common Challenges (pp. 17-29). (Lecture Notes in Computer Science; Vol. 12003). Springer. https://doi.org/10.1007/978-3-030-52829-4_2 [details]
    • Koulouzis, S., Carval, T., Heikkinen, J., Pursula, A., & Zhao, Z. (2020). Case Study: Data Subscriptions Using Elastic Cloud Services. In Z. Zhao, & M. Hellström (Eds.), Towards Interoperable Research Infrastructures for Environmental and Earth Sciences: A Reference Model Guided Approach for Common Challenges (pp. 293-306). (Lecture Notes in Computer Science; Vol. 12003). Springer. https://doi.org/10.1007/978-3-030-52829-4_16 [details]
    • Koulouzis, S., Martin, P., & Zhao, Z. (2020). Virtual Infrastructure Optimisation. In Z. Zhao, & M. Hellström (Eds.), Towards Interoperable Research Infrastructures for Environmental and Earth Sciences: A Reference Model Guided Approach for Common Challenges (pp. 192-207). (Lecture Notes in Computer Science; Vol. 12003). Springer. https://doi.org/10.1007/978-3-030-52829-4_11 [details]
    • Koulouzis, S., Martin, P., Zhou, H., Hu, Y., Wang, J., Carval, T., Grenier, B., Heikkinen, J., de Laat, C., & Zhao, Z. (2020). Time-critical data management in clouds: challenges and a Dynamic Real-time Infrastructure Planner (DRIP) solution. Concurrency and Computation: Practice and Experience, 32(16), Article e5269. https://doi.org/10.1002/cpe.5269 [details]
    • Magagna, B., Goldfarb, D., Martin, P., Atkinson, M., Koulouzis, S., & Zhao, Z. (2020). Data Provenance. In Z. Zhao, & M. Hellström (Eds.), Towards Interoperable Research Infrastructures for Environmental and Earth Sciences: A Reference Model Guided Approach for Common Challenges (pp. 208-225). (Lecture Notes in Computer Science; Vol. 12003). Springer. https://doi.org/10.1007/978-3-030-52829-4_12 [details]
    • Magagna, B., Martin, P., Nieva de la Hidalga, A., Atkinson, M., & Zhao, Z. (2020). Common Challenges and Requirements. In Z. Zhao, & M. Hellström (Eds.), Towards Interoperable Research Infrastructures for Environmental and Earth Sciences: A Reference Model Guided Approach for Common Challenges (pp. 30-57). (Lecture Notes in Computer Science; Vol. 12003). Springer. https://doi.org/10.1007/978-3-030-52829-4_3 [details]
    • Martin, P., Liao, X., Magagna, B., Stocker, M., & Zhao, Z. (2020). Semantic and Knowledge Engineering Using ENVRI RM. In Z. Zhao, & M. Hellström (Eds.), Towards Interoperable Research Infrastructures for Environmental and Earth Sciences: A Reference Model Guided Approach for Common Challenges (pp. 100-119). (Lecture Notes in Computer Science; Vol. 12003). Springer. https://doi.org/10.1007/978-3-030-52829-4_6 [details]
    • Martin, P., Magagna, B., Liao, X., & Zhao, Z. (2020). Semantic Linking of Research Infrastructure Metadata. In Z. Zhao, & M. Hellström (Eds.), Towards Interoperable Research Infrastructures for Environmental and Earth Sciences: A Reference Model Guided Approach for Common Challenges (pp. 226-246). (Lecture Notes in Computer Science; Vol. 12003). Springer. https://doi.org/10.1007/978-3-030-52829-4_13 [details]
    • Nieva de la Hidalga, A., Hardisty, A., Martin, P., Magagna, B., & Zhao, Z. (2020). The ENVRI Reference Model. In Z. Zhao, & M. Hellström (Eds.), Towards Interoperable Research Infrastructures for Environmental and Earth Sciences: A Reference Model Guided Approach for Common Challenges (pp. 61-81). (Lecture Notes in Computer Science; Vol. 12003). Springer. https://doi.org/10.1007/978-3-030-52829-4_4 [details]
    • Prodan, R., Saurabh, N., Zhao, Z., Orton-Johnson, K., Chakravorty, A., Karadimce, A., & Ulisses, A. (2020). ARTICONF: Towards a Smart Social Media Ecosystem in a Blockchain Federated Environment. In U. Schwardmann, C. Boehme, & D. B. Heras (Eds.), Euro-Par 2019: Parallel Processing Workshops: Euro-Par 2019 International Workshops, Göttingen, Germany, August 26–30, 2019 : revised selected papers (pp. 417-428). (Lecture Notes in Computer Science; Vol. 11997). Springer. https://doi.org/10.5281/zenodo.3580716, https://doi.org/10.1007/978-3-030-48340-1_32 [details]
    • Quimbert, E., Jeffery, K., Martens, C., Martin, P., & Zhao, Z. (2020). Data Cataloguing. In Z. Zhao, & M. Hellström (Eds.), Towards Interoperable Research Infrastructures for Environmental and Earth Sciences: A Reference Model Guided Approach for Common Challenges (pp. 140-161). (Lecture Notes in Computer Science; Vol. 12003). Springer. https://doi.org/10.1007/978-3-030-52829-4_8 [details]
    • Shi, Z., Zhou, H., Koulouzis, S., Rubia, C., & Zhao, Z. (2020). Co-located and Orchestrated Network Fabric (CONF): An Automated Cloud Virtual Infrastructure for Social Network Applications. In U. Schwardmann, C. Boehme, & D. B. Heras (Eds.), Euro-Par 2019: Parallel Processing Workshops: Euro-Par 2019 International Workshops, Göttingen, Germany, August 26–30, 2019 : revised selected papers (pp. 464-475). (Lecture Notes in Computer Science; Vol. 11997). Springer. https://doi.org/10.1007/978-3-030-48340-1_36 [details]
    • Wang, Y., & Zhao, Z. (2020). Decentralized workflow management on software defined infrastructures. In 2020 IEEE World Congress on Services: proceedings : 18-24 October 2020 : virtual event (pp. 265-268). (SERVICES). IEEE Computer Society. https://doi.org/10.1109/SERVICES48979.2020.00059 [details]
    • Zhang, L., Jiang, W., & Zhao, Z. (2020). Short-Text Feature Expansion and Classification Based on Non-negative Matrix Factorization. In X. Chen, H. Yan, Q. Yan, & X. Zhang (Eds.), Machine Learning for Cyber Security - Third International Conference, ML4CS 2020, Proceedings (pp. 347-362). (Lecture Notes in Computer Science; Vol. 12488). Springer. https://doi.org/10.1007/978-3-030-62463-7_32
    • Zhao, Z., & Hellström, M. (Eds.) (2020). Towards Interoperable Research Infrastructures for Environmental and Earth Sciences: A Reference Model Guided Approach for Common Challenges. (Lecture Notes in Computer Science; Vol. 12003). Springer. https://doi.org/10.1007/978-3-030-52829-4 [details]
    • Zhao, Z., & Jeffery, K. (2020). Reference Model Guided Engineering. In Z. Zhao, & M. Hellström (Eds.), Towards Interoperable Research Infrastructures for Environmental and Earth Sciences: A Reference Model Guided Approach for Common Challenges (pp. 82-99). (Lecture Notes in Computer Science; Vol. 12003). Springer. https://doi.org/10.1007/978-3-030-52829-4_5 [details]
    • Zhao, Z., Jeffery, K., Stocker, M., Atkinson, M., & Petzold, A. (2020). Towards Operational Research Infrastructures with FAIR Data and Services. In Z. Zhao, & M. Hellström (Eds.), Towards Interoperable Research Infrastructures for Environmental and Earth Sciences: A Reference Model Guided Approach for Common Challenges (pp. 360-372). (Lecture Notes in Computer Science; Vol. 12003). Springer. https://doi.org/10.1007/978-3-030-52829-4_20 [details]
    • Zhao, Z., Taylor, I., & Prodan, R. (2020). Editorial for FGCS Special issue on “Time-critical Applications on Software-defined Infrastructures”. Future Generation Computer Systems, 112, 1170-1171. https://doi.org/10.1016/j.future.2020.07.056 [details]
    • Zhou, H., Ouyang, X., & Zhao, Z. (2020). ALLSTAR: A Blockchain Based Decentralized Ecosystem for Cloud and Edge Computing. In 2020 IEEE International Conference on JointCloud Computing: proceedings : 3-6 August 2020, Oxford, United Kingdom (pp. 55-62). IEEE Computer Society. https://doi.org/10.1109/JCC49151.2020.00018 [details]
    • de Jong, K., Fahrenfort, C., Younis, A., & Zhao, Z. (2020). Sharing digital object across data infrastructures using Named Data Networking (NDN). In L. Levevre, C. A. Varela, G. Pallis, A. N. Toosi, O. Rana, & R. Buyya (Eds.), 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing: proceedings : 11-14 May 2020, Melbourne, Australia (pp. 873-880). IEEE Computer Society. https://doi.org/10.1109/CCGrid49817.2020.00013 [details]

    2019

    • Demchenko, Y., Zhao, Z., Surbiryala, J., Koulouzis, S., Shi, Z., Liao, X., & Gordiyenko, J. (2019). Teaching DevOps and Cloud based Software Engineering in University Curricula. In IEEE 15th International Conference on eScience: proceedings : 24-27 September 2019, San Diego, California (pp. 548-552). IEEE Computer Society. https://doi.org/10.1109/eScience.2019.00075 [details]
    • El Khaldi Ahanach, E., Koulouzis, S., & Zhao, Z. (2019). Contextual linking between workflow provenance and system performance logs. In IEEE 15th International Conference on eScience: proceedings : 24-27 September 2019, San Diego, California (pp. 634-635). IEEE Computer Society. https://doi.org/10.1109/eScience.2019.00093 [details]
    • Fahrenfort, C., & Zhao, Z. (2019). Effective digital object access and sharing over a networked environment using DOIP and NDN. In IEEE 15th International Conference on eScience: proceedings : 24-27 September 2019, San Diego, California (pp. 632-633). IEEE Computer Society. https://doi.org/10.1109/eScience.2019.00092 [details]
    • Hu, Y., de Laat, C., & Zhao, Z. (2019). Learning Workflow Scheduling on Multi-Resource Clusters. In 2019 IEEE International Conference on Networking, Architecture and Storage (NAS): proceedings : Enshi, China, 15-17 August 2019 (pp. 17-24). IEEE. https://doi.org/10.1109/NAS.2019.8834720 [details]
    • Hu, Y., de Laat, C., & Zhao, Z. (2019). Multi-objective Container Deployment on Heterogeneous Clusters. In Proceedings 19th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing: CCGrid 2019, Cyprus (pp. 592-599). IEEE Computer Society. https://doi.org/10.1109/CCGRID.2019.00076 [details]
    • Hu, Y., de Laat, C., & Zhao, Z. (2019). Optimizing Service Placement for Microservice Architecture in Clouds. Applied Sciences, 9(21), Article 4663. https://doi.org/10.3390/app9214663 [details]
    • Liao, X., & Zhao, Z. (2019). Unsupervised Approaches for Textual Semantic Annotation, A Survey. ACM Computing Surveys, 52(4), Article 66. https://doi.org/10.1145/3324473 [details]
    • Liao, X., Bottelier, J., & Zhao, Z. (2019). A Column Styled Composable Schema Matcher for Semantic Data-types. Data Science Journal, 18, Article 25. https://doi.org/10.5334/dsj-2019-025 [details]
    • Martin, P., Remy, L., Theodoridou, M., Jeffery, K., & Zhao, Z. (2019). Mapping heterogeneous research infrastructure metadata into a unified catalogue for use in a generic virtual research environment. Future Generation Computer Systems, 101, 1-13. https://doi.org/10.1016/j.future.2019.05.076 [details]
    • Petzold, A., Asmi, A., Vermeulen, A., Pappalardo, G., Bailo, D., Schaap, D., Glaves, H. M., Bundke, U., & Zhao, Z. (2019). ENVRI-FAIR - Interoperable environmental FAIR data and services for society, innovation and research. In IEEE 15th International Conference on eScience: proceedings : 24-27 September 2019, San Diego, California (pp. 277-280). IEEE Computer Society. https://doi.org/10.1109/eScience.2019.00038 [details]
    • Remy, L., Ivanović, D., Theodoridou, M., Kritsotaki, A., Martin, P., Bailo, D., Sbarra, M., Zhao, Z., & Jeffery, K. (2019). Building an Integrated Enhanced Virtual Research Environment Metadata Catalogue. The electronic library, 37(6), 929-951. https://doi.org/10.5281/zenodo.3497055, https://doi.org/10.1108/EL-09-2018-0183 [details]
    • Shi, Z., Zhou, H., Hu, Y., Surbiryala, J., de Laat, C., & Zhao, Z. (2019). Operating Permissioned Blockchain in Clouds: A Performance Study of Hyperledger Sawtooth. In 2019 18th International Symposium on Parallel and Distributed Computing: ISPDC 2019 : proceedings : 5-7 June 2019, Amsterdam, the Netherlands (pp. 50-57). (Proceedings International Symposium on Parallel and Distributed Computing; Vol. 2019). IEEE Computer Society. https://doi.org/10.1109/ISPDC.2019.00010 [details]
    • Shi, Z., Zhou, H., Surbiryala, J., Hu, Y., de Laat, C., & Zhao, Z. (2019). An Automated Customization and Performance Profiling Framework for Permissioned Blockchains in a Virtualized Environment. In J. Chen, & L. T. Yang (Eds.), The 11th IEEE International Conference on Cloud Computing Technology and Science (CloudCom 2019): the 19th IEEE International Conference on Computer and Information Technology (CIT 2019) ; the 2019 International Workshop on Resource Brokering with Blockchain (RBchain 2019) ; the 2019 Asia-Pacific Services Computing Conference (APSCC 2019) : proceedings : 11-13 December 2019, Sydney, Australia (pp. 404-410). IEEE Computer Society. https://doi.org/10.1109/CloudCom.2019.00069 [details]
    • Taal, A., Wang, J., de Laat, C., & Zhao, Z. (2019). Profiling the scheduling decisions for handling critical paths in deadline-constrained cloud workflows. Future Generation Computer Systems, 100, 237-249. https://doi.org/10.1016/j.future.2019.05.002 [details]
    • Tanhua, T., Pouliquen, S., Hausman, J., O’Brien, K., Bricher, P., de Bruin, T., Buck, J. J. H., Burger, E. F., Carval, T., Casey, K. S., Diggs, S., Giorgetti, A., Glaves, H., Harscoat, V., Kinkade, D., Muelbert, J. H., Novellino, A., Pfeil, B., Pulsifer, P. L., ... Zhao, Z. (2019). Ocean FAIR Data Services. Frontiers in Marine Science, 6, Article 440. https://doi.org/10.3389/fmars.2019.00440 [details]
    • Zhao, Z., Liao, X., Martin, P., Maduro, J., Thijsse, P., Schaap, D., Stocker, M., Goldfarb, D., & Magagna, B. (2019). Knowledge-as-a-Service: a community knowledge base for research infrastructures in environmental and earth sciences. In Proceedings 2019 IEEE World Congress on Services: IEEE SERVICES 2019 : 8-13 July 2019, Milan, Italy (pp. 127-132). IEEE Computer Society. https://doi.org/10.1109/SERVICES.2019.00041 [details]
    • Zhao, Z., Liao, X., Wang, X., Ruan, C., Zhu, Y., & Feng, D. (2019). 农业大数据基础设施开发的参考模型方法. 華東師範大學学报. 自然科学版 = Journal of East China Normal University. Natural science edition, 2019(2), 77-96. https://doi.org/10.3969/j.issn.1000-5641.2019.02.009 [details]
    • Zhou, H., Ouyang, X., Ren, Z., Su, J., de Laat, C., & Zhao, Z. (2019). A Blockchain based Witness Model for Trustworthy Cloud Service Level Agreement Enforcement. In IEEE INFOCOM 2019 - IEEE Conference on Computer Communications (pp. 1567-1575). IEEE. https://doi.org/10.1109/INFOCOM.2019.8737580 [details]
    • Zhou, H., Shi, Z., Hu, Y., Donkers, P., Afanasyev, A., Koulouzis, S., Taal, A., Ulisses, A., & Zhao, Z. (2019). Large distributed virtual infrastructure partitioning and provisioning across providers. In 2019 IEEE International Conference on Smart Internet of Things: proceedings : 9-11 August 2019, Tianjin, China : IEEE SmartIoT 2019 (pp. 56-63). Conference Publishing Services, IEEE Computer Society. https://doi.org/10.1109/SmartIoT.2019.00018 [details]
    • Štefanič, P., Cigale, M., Jones, A. C., Knight, L., Taylor, I., Istrate, C., Suciu, G., Ulisses, A., Stankovski, V., Taherizadeh, S., Flores Salado, G., Koulouzis, S., Martin, P., & Zhao, Z. (2019). SWITCH workbench: A novel approach for the development and deployment of time-critical microservice-based cloud-native applications. Future Generation Computer Systems, 99, 197-212. Advance online publication. https://doi.org/10.1016/j.future.2019.04.008 [details]

    2018

    • Jiang, W., Zhai, Y., Martin, P., & Zhao, Z. (2018). Structure Properties of Generalized Farey graphs based on Dynamical Systems for Networks. Scientific Reports, 8, Article 12194. https://doi.org/10.1038/s41598-018-30712-2 [details]
    • Jiang, W., Zhai, Y., Zhuang, Z., Martin, P., Zhao, Z., & Liu, J-B. (2018). An efficient method of generating deterministic small-world and scale-free graphs for simulating real-world networks. IEEE Access, 6, 59833-59842. https://doi.org/10.1109/ACCESS.2018.2875928 [details]
    • Jiang, W., Zhai, Y., Zhuang, Z., Martin, P., Zhao, Z., & Liu, J.-B. (2018). Vertex Labeling and Routing for Farey-Type Symmetrically-Structured Graphs. Symmetry, 10(9), Article 407. https://doi.org/10.3390/sym10090407 [details]
    • Koulouzis, S., Mousa, R., Karakannas, A., Laat, C. D., & Zhao, Z. (2018). Information Centric Networking for Sharing and Accessing Digital Objects with Persistent Identifiers on Data Infrastructures. In 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing: proceedings : 1-4 May 2018, Washington, DC (pp. 661-668). IEEE Computer Society. https://doi.org/10.1109/CCGRID.2018.00098 [details]
    • Li, J., Yang, Y., Wang, X., Zhao, Z., & Li, T. (2018). A novel parallel distance metric-based approach for diversified ranking on large graphs. Future Generation Computer Systems, 88, 79-91. Advance online publication. https://doi.org/10.1016/j.future.2018.05.031 [details]
    • Qin, Y., Chi, M., Liu, X., Zhang, Y., Zeng, Y., & Zhao, Z. (2018). Classification of high resolution urban remote sensing images using deep networks by integration of social media photos. In 22018 IEEE International Geoscience & Remote Sensing Symposium: proceedings : July 22-27, 2018, Valencia, Spain (pp. 7243-7246). (IGARSS; Vol. 2018). IEEE. https://doi.org/10.1109/IGARSS.2018.8518538 [details]
    • Taherizadeh, S., Jones, A. C., Taylor, I., Zhao, Z., & Stankovski, V. (2018). Monitoring self-adaptive applications within edge computing frameworks: A state-of-the-art review. Journal of Systems and Software, 136, 19-38. https://doi.org/10.1016/j.jss.2017.10.033 [details]
    • Zhou, H., Hu, Y., Su, J., Chi, M., de Laat, C., & Zhao, Z. (2018). Empowering Dynamic Task-based Applications with Agile Virtual Infrastructure Programmability. In 2018 IEEE International Conference on Cloud Computing : IEEE CLOUD 2018 : proceedings : 2-7 July 2018, San Francisco, California, USA (pp. 484-491). IEEE. https://doi.org/10.1109/CLOUD.2018.00068 [details]
    • Zhou, H., Hu, Y., Su, J., de Laat, C., & Zhao, Z. (2018). CloudsStorm: An Application-Driven Framework to Enhance the Programmability and Controllability of Cloud Virtual Infrastructures. In M. Luo, & L.-J. Zhang (Eds.), Cloud Computing – CLOUD 2018: 11th International Conference, held as part of the Services Conference Federation, SCF 2018, Seattle, WA, USA, June 25–30, 2018 : proceedings (pp. 265-280). (Lecture Notes in Computer Science; Vol. 10967). Springer. https://doi.org/10.1007/978-3-319-94295-7_18 [details]
    • Zhou, H., Koulouzis, S., Hu, Y., Wang, J., Ulisses, A., de Laat, C., & Zhao, Z. (2018). Migrating live streaming applications onto clouds: challenges and a CloudStorm solution. In A. Sill, & J. Spillner (Eds.), 11th IEEE/ACM International Conference on Utility and Cloud Computing companion: UCC-C 2018 : proceedings : 17-20 December 2018, Zurich, Switzerland (pp. 321-326). IEEE Computer Society. https://doi.org/10.1109/UCC-Companion.2018.00075 [details]
    • Zhou, H., Taal, A., Koulouzis, S., Wang, J., Hu, Y., Suciu, G., Poenaru, V., de Laat, C., & Zhao, Z. (2018). Dynamic Real-Time Infrastructure Planning and Deployment for Disaster Early Warning Systems. In Y. Shi, H. Fu, Y. Tian, V. V. Krzhizhanovskaya, M. H. Lees, J. Dongarra, & P. M. A. Sloot (Eds.), Computational Science – ICCS 2018: 18th International Conference, Wuxi, China, June 11–13, 2018 : proceedings (Vol. 2, pp. 644-654). (Lecture Notes in Computer Science; Vol. 10861). Springer. https://doi.org/10.1007/978-3-319-93701-4_51 [details]
    • Zhou, H., de Laat, C., & Zhao, Z. (2018). Trustworthy Cloud Service Level Agreement Enforcement with Blockchain based Smart Contract. In IEEE 10th International Conference on Cloud Computing Technology and Science: proceedings : 10-13 December 2018, Nicosia, Cyprus (pp. 255-260). IEEE Computer Society. https://doi.org/10.1109/CloudCom2018.2018.00057 [details]

    2017

    • Hu, Y., Wang, J., Zhou, H., Martin, P., Taal, A., de Laat, C., & Zhao, Z. (2017). Deadline-Aware Deployment for Time Critical Applications in Clouds. In F. F. Rivera, T. F. Pena, & J. C. Cabaleiro (Eds.), Euro-Par 2017: Parallel Processing: 23rd International Conference on Parallel and Distributed Computing, Santiago de Compostela, Spain, August 28-September 1, 2017 : proceedings (pp. 345-357). ( Lecture Notes in Computer Science; Vol. 10417), (Advanced Research in Computing and Software Science). Springer. https://doi.org/10.1007/978-3-319-64203-1_25 [details]
    • Kutsch, W. L., Zhao, Z., Hardisty, A., Hellström, M., Chin, Y., Magagna, B., ... Atkinson, M. (2017). Data interoperabilty between European Environmental Research Infrastructures and their contribution to global data networks. In AGU Fall Meeting Abstracts (AGU Fall Meeting Abstracts).
    • Martin, P., Chen, Y., Hardisty, A., Jeffery, K., & Zhao, Z. (2017). Computational Challenges in Global Environmental Research Infrastructures. In A. Chabbi, & H. W. Loescher (Eds.), Terrestrial Ecosystem Research Infrastructures: Challenges and Opportunities (pp. 305-340). CRC Press. https://doi.org/10.1201/9781315368252 [details]
    • Taherizadeh, S., Taylor, I., Jones, A., Zhao, Z., & Stankovski, V. (2017). A network edge monitoring approach for real-time data streaming applications. In J. A. Banares, J. Altmann, & K. Tserpes (Eds.), Economics of Grids, Clouds, Systems, and Services - 13th International Conference, GECON 2016, Revised Selected Papers (pp. 293-303). (Lecture Notes in Computer Science; Vol. 10382). Springer. https://doi.org/10.1007/978-3-319-61920-0_21
    • Wang, J., Zhou, H., Hu, Y., de Laat, C., & Zhao, Z. (2017). Deadline-Aware Coflow Scheduling in a DAG. In 2017 IEEE 9th International Conference on Cloud Computing Technology and Science: CloudCom 2017 : proceedings : 11-14 December 2017, Hong Kong, Hong Kong (pp. 341-346). IEEE Computer Society. https://doi.org/10.1109/CloudCom.2017.55 [details]

    2016

    • Casale, G., Chesta, C., Deussen, P., Di Nitto, E., Gouvas, P., Koussouris, S., Stankovski, V., Symeonidis, A., Vlassiou, V., Zafeiropoulos, A., & Zhao, Z. (2016). Current and Future Challenges of Software Engineering for Services and Applications. Procedia Computer Science, 97, 34–42. https://doi.org/10.1016/j.procs.2016.08.278 [details]
    • Koulouzis, S., Belloum, A. S. Z., Bubak, M. T., Zhao, Z., Živković, M., & de Laat, C. T. A. M. (2016). SDN-aware federation of distributed data. Future Generation Computer Systems, 56, 64-76. https://doi.org/10.1016/j.future.2015.09.032 [details]
    • Martin, P., Taal, A., Quevedo, F., Rogers, D., Evans, K., Jones, A., Stankovski, V., Taherizadeh, S., Trnkoczy, J., Suciu, G., & Zhao, Z. (2016). Information modelling and semantic linking for a software workbench for interactive, time critical and self-adaptive cloud applications. In L. Barolli, M. Takizawa, T. Enokido, A. J. Jara, & Y. Bocchi (Eds.), Proceedings IEEE 30th International Conference on Advanced Information Networking and Applications Workshops: WAINA 2016 : 23-25 March 2016, Crans-Montana, Switzerland (pp. 127-132). IEEE Computer Society. https://doi.org/10.1109/WAINA.2016.38 [details]
    • Petcu, D., Fazio, M., Prodan, R., Zhao, Z., & Rak, M. (2016). On the Next Generations of Infrastructure-as-a-Services. In J. Cardoso, D. Ferguson, V. Méndez Muñoz, & M. Helfert (Eds.), CLOSER 2016: proceedings of the 6th International Conference on Cloud Computing and Services Science: April 23-25, 2016, Rome, Italy (Vol. 1, pp. 320-326). SciTePress Science and Technology Publications. https://doi.org/10.5220/0005912503200326 [details]

    2015

    • Jeferry, K., Kousiouris, G., Kyriazis, D., Altmann, J., Ciuffoletti, A., Maglogiannis, I., Nesi, P., Suzic, B., & Zhao, Z. (2015). Challenges emerging from future cloud application scenarios. Procedia Computer Science, 68, 227-237. https://doi.org/10.1016/j.procs.2015.09.238 [details]
    • Martin, P., Grosso, P., Magagna, B., Schentz, H., Chen, Y., Hardisty, A., Los, W., Jeffery, K., de Laat, C., & Zhao, Z. (2015). Open Information Linking for Environmental Research Infrastructures. In Proceedings, 11th IEEE International Conference on eScience: 31 August-4 September 2015, Munich, Germany (pp. 513-520). IEEE Computer Society. https://doi.org/10.1109/eScience.2015.66 [details]
    • Zhao, Z., Martin, P., Grosso, P., Los, W., de Laat, C., Jeffrey, K., Hardisty, A., Vermeulen, A., Castelli, D., Legré, Y., & Kutsch, W. (2015). Reference Model Guided System Design and Implementation for Interoperable Environmental Research Infrastructures. In Proceedings, 11th IEEE International Conference on eScience: 31 August-4 September 2015, Munich, Germany (pp. 551-556). IEEE Computer Society. https://doi.org/10.1109/eScience.2015.41 [details]
    • Zhao, Z., Martin, P., Wang, J., Taal, A., Jones, A., Taylor, I., Stankovski, V., Garcia Vega, I., Suciu, G., Ulisses, A., & de Laat, C. (2015). Developing and operating time critical applications in clouds: the state of the art and the SWITCH approach. Procedia Computer Science, 68, 17-28. https://doi.org/10.1016/j.procs.2015.09.220 [details]
    • Zhao, Z., Taal, A., Jones, A., Taylor, I., Stankovski, V., Hidalgo, F. J., Suciu, G., Ulisses, A., Ferreira, P., & de Laat, C. (2015). A Software Workbench for Interactive, Time Critical and Highly self-adaptive cloud applications (SWITCH). In 2015 IEEE/ACM 15th International Symposium on Cluster, Cloud and Grid Computing : CCGrid 2015: proceedings : 4-7 May 2015, Shenzhen, China (pp. 1181-1184). IEEE Computer Society. https://doi.org/10.1109/CCGrid.2015.73 [details]
    • Zhu, H., van der Veldt, K., Zhao, Z., Grosso, P., Pavlov, D., Soeurt, J., Liao, X., & de Laat, C. (2015). A semantic enhanced Power Budget Calculator for distributed computing using IEEE 802.3az. Cluster Computing, 18(1), 61-77. https://doi.org/10.1007/s10586-014-0395-7 [details]

    2013

    • Chen, Y., Hardisty, A., Preece, A., Martin, M., Atkinson, M., Zhao, Z., Magagna, B., Schentz, H., & Legre, Y. (2013). Analysis of Common Requirements for Environmental Science Research Infrastructures. In The International Symposium on Grids and Clouds (ISGC)
    • Chen, Y., Martin, P., Schentz, H., Magagna, B., Zhao, Z., Hardisty, A., ... Legre, Y. (2013). Building a common reference model for environmental science research infrastructures. In Proceedings of EnviroInfo2013
    • Dumitru, C., Zhao, Z., Grosso, P., & de Laat, C. (2013). HybridFlow: Towards intelligent video delivery and processing over hybrid infrastructures. In W. W. Smari, & G. C. Fox (Eds.), Proceedings of the 2013 International Conference on Collaboration Technologies and Systems: May 20-24, 2013, Sheraton San Diego Hotel & Marina, San Diego, California (pp. 473-478). IEEE. https://doi.org/10.1109/CTS.2013.6567271 [details]
    • Ghijsen, M., van der Ham, J., Grosso, P., Dumitru, C., Zhu, H., Zhao, Z., & de Laat, C. (2013). A semantic-web approach for modeling computing infrastructures. Computers & Electrical Engineering, 39(8), 2553-2565. https://doi.org/10.1016/j.compeleceng.2013.08.011 [details]
    • Jiang, W., Zhao, Z., & de Laat, C. (2013). An Autonomous Security Storage Solution for Data-Intensive Cooperative Cloud Computing. In Proceedings IEEE Ninth International Conference on e-Science: e-Science 2013 : 22-25 October 2013, Beijing, China (pp. 369-372). IEEE Computer Society. https://doi.org/10.1109/eScience.2013.31 [details]
    • Jiang, W., Zhao, Z., Wibisono, A., Grosso, P., & de Laat, C. (2013). Dynamic Workflow Planning on Programmable Infrastructure. In Proceedings : 2013 IEEE Eighth International Conference on Networking, Architecture, and Storage: NAS 2013 : 17-19 July 2013 : Xi'an, Shaanxi, China (pp. 326-330). IEEE Computer Society. https://doi.org/10.1109/NAS.2013.53 [details]

    2012

    • Demchenko, Y., Zhao, Z., Grosso, P., Wibisono, A., & de Laat, C. (2012). Addressing big data challenges for scientific data infrastructure. In 4th IEEE International Conference on Cloud Computing Technology and Science proceedings (CloudCom2012): Taipei, Taiwan, 3-6 December 2012 (pp. 614-617). IEEE. https://doi.org/10.1109/CloudCom.2012.6427494 [details]
    • Pavlov, D., Soeurt, J., Grosso, P., Zhao, Z., van der Veldt, K., Zhu, H., & de Laat, C. (2012). Towards energy efficient data intensive computing using IEEE 802.3az. In 2012 SC companion: high performance computing, networking, storage and analysis (SCC 2012) : Salt Lake City, Utah, USA, 10 - 16 November 2012 (pp. 806-810). IEEE. https://doi.org/10.1109/SC.Companion.2012.112 [details]
    • Zhao, Z., Dumitru, C., Grosso, P., & de Laat, C. (2012). Network resource control for data intensive applications in heterogeneous infrastructures. In Proceedings of the 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshop: IPDPS 2012 : 21-25 May 2012, Shanghai, China (pp. 2069-2076). IEEE Computer Society. https://doi.org/10.1109/IPDPSW.2012.243 [details]
    • Zhao, Z., Grosso, P., & de Laat, C. (2012). OEIRM: An Open Distributed Processing based Interoperability Reference Model for e-Science. In J. J. Park, A. Zomaya, S.-S. Yeo, & S. Sahni (Eds.), Network and Parallel Computing: 9th IFIP International Conference, NPC 2012, Gwangju, Korea, September 6-8, 2012 : proceedings (pp. 437-444). (Lecture Notes in Computer Science; Vol. 7513). Springer. https://doi.org/10.1007/978-3-642-35606-3_52 [details]
    • Zhao, Z., Grosso, P., van der Ham, J., & de Laat, C. (2012). Quality guaranteed media delivery over advanced network. In G. Fortino, & C. E. Palau (Eds.), Next generation content delivery infrastructure: emerging paradigms and technologies (pp. 121-146). IGI Global. https://doi.org/10.4018/978-1-4666-1794-0.ch006 [details]
    • Zhao, Z., van der Ham, J., Taal, A., Koning, R., Dumitru, C., Wibisono, A., Grosso, P., & de Laat, C. (2012). Planning data intensive workflows on inter-domain resources using the Network Service Interface (NSI). In 2012 SC companion: high performance computing, networking, storage and analysis (SCC 2012): Salt Lake City, Utah, USA, 10 - 16 November 2012 (pp. 150-156). IEEE. https://doi.org/10.1109/SC.Companion.2012.30 [details]
    • Zhu, H., van der Veldt, K., Grosso, P., Zhao, Z., Liao, X., & de Laat, C. (2012). Energy-aware semantic modeling in large scale infrastructures. In Work in Progress Sessions (WiP): the 2012 IEEE International Conference on Internet of Things (iThings 2012), the 2012 IEEE International Conference on Cyber, Physical and Social Computing (CPSCom 2012), the 2012 IEEE International Conference on Green Computing and Communications (GreenCom 2012): 20-23 November 2012, Besançon, France (pp. 11-14). IEEE. [details]

    2011

    • Belloum, A., Inda, M. A., Vasunin, D., Korkhov, V., Zhao, Z., Rauwerda, H., Breit, T. M., Bubak, M., & Hertzberger, L. O. (2011). Collaborative e-Science Experiments and Scientific Workflows. IEEE Internet Computing, 15(4), 39-47. https://doi.org/10.1109/MIC.2011.87 [details]
    • Zhao, Z., Grosso, P., van der Ham, J., Koning, R., & de Laat, C. (2011). An agent based network resource planner for workflow applications. Multiagent and Grid Systems, 7(6), 187-202. https://doi.org/10.3233/MGS-2011-0180 [details]
    • Zhao, Z., Taal, A., Grosso, P., & de Laat, C. (2011). Resource discovery in large scale network infrastructure. In the Sixth IEEE international conference on Networking, Architecture, and Storage (pp. 186-190). IEEE Conference Publishing Services. https://doi.org/10.1109/NAS.2011.43 [details]

    2010

    • Lu, S., Deelman, E., & Zhao, Z. (2010). Scientific workflows special issue: preface. In International journal of business process integration and management (Vol. 5, pp. 1-2). Inderscience Enterprises Ltd.. http://www.inderscience.com/editorials/f385411271261910.pdf [details]
    • Zhao, Z., Grosso, P., Koning, R., van der Ham, J., & de Laat, C. (2010). An agent based planner for including network QoS in scientific workflows. In M. Ganzha, & M. Paprzycki (Eds.), Proceedings of the International Multiconference on Computer Science and Information Technology (IMCSIT 2010) (pp. 231-238). IEEE. http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=5680060&isnumber=5679615 [details]
    • Zhao, Z., Grosso, P., Koning, R., van der Ham, J., & de Laat, C. (2010). An architecture including network QoS in scientific workflows. In Proceedings of the 9th International Conference on Grid and Cloud Computing (GCC 2010) (pp. 104-109). IEEE Computer Society. https://doi.org/10.1109/GCC.2010.32 [details]
    • Zhao, Z., Grosso, P., Koning, R., van der Ham, J., & de Laat, C. (2010). Network resource selection for data transfer processes in scientific workflows. In 2010 5th Workshop on Workflows in Support of Large-Scale Science (WORKS): 14 Nov. 2010, New Orleans, LA, USA : in conjunction with SC 10 IEEE. https://doi.org/10.1109/WORKS.2010.5671840 [details]

    2009

    2008

    • Wibisono, A., Zhao, Z., Belloum, A., & Bubak, M. (2008). A framework for interactive parameter sweep applications. In M. Bubak, G. D. van Albada, J. Dongarra, & P. M. A. Sloot (Eds.), Computational Science – ICCS 2008: 8th International Conference, Kraków, Poland, June 23-25, 2008 : proceedings (Vol. III, pp. 481-490). (Lecture Notes in Computer Science; Vol. 5103). Springer. https://doi.org/10.1007/978-3-540-69389-5_55 [details]
    • Wibisono, A., Zhao, Z., Belloum, A., & Bubak, M. (2008). A framework for interactive parameter sweep applications. In T. Priol, L. Lefevre, & R. Buyya (Eds.), CCGRID 2008: Eighth IEEE International Symposium on Cluster Computing and the Grid : proceedings : 19-22 May, 2008, Lyon, France (pp. 703). IEEE Computer Society. https://doi.org/10.1109/CCGRID.2008.111 [details]
    • Wibisono, A., Zhao, Z., Belloum, A., & Bubak, M. (2008). Towards a Virtual Laboratory for interactive parameter sweep applications on the Grid. In M. Bubak, M. Turała, & K. Wiatr (Eds.), Cracow'07 Grid Workshop: October 15-17, 2007 Cracow, Poland: proceedings (pp. 266-271). Kraków: Academic Computer Centre CYFRONET AGH. [details]
    • Zhao, Z., Belloum, A., Bubak, M., & Hertzberger, B. (2008). Support for cooperative experiments in VL-e: from scientific workflows to knowledge sharing. In Fourth IEEE International Conference on eScience (eScience 2008) (pp. 329-330). IEEE Computer Society. https://doi.org/10.1109/eScience.2008.120 [details]

    2023

    2021

    2019

    • Zhou, H., Hu, Y., Ouyang, X., Su, J., Koulouzis, S., de Laat, C., & Zhao, Z. (2019). CloudsStorm: A framework for seamlessly programming and controlling virtual infrastructure functions during the DevOps lifecycle of cloud applications. Software, practice & experience, 49(10), 1421-1447. https://doi.org/10.1002/spe.2741 [details]

    2018

    • Hu, Y., Zhou, H., de Laat, C., & Zhao, Z. (2018). ECSched: Efficient Container Scheduling on Heterogeneous Clusters. In M. Aldinucci, L. Padovani, & M. Torquati (Eds.), Euro-Par 2018: Parallel Processing: 24th International Conference on Parallel and Distributed Computing, Turin, Italy, August 27-31, 2018 : proceedings (pp. 365-377). (Lecture Notes in Computer Science; Vol. 11014). Springer. https://doi.org/10.1007/978-3-319-96983-1_26 [details]

    2017

    • Elzinga, O., Koulouzis, S., Taal, A., Wang, J., Hu, Y., Zhou, H., Martin, P., de Laat, C., & Zhao, Z. (2017). Automatic collector for dynamic cloud performance Information. In 2017 IEEE International Conference on Networking, Architecture, and Storage (NAS): proceedings : 7-9 August 2017, Shenzhen, China (pp. 226-231). IEEE. https://doi.org/10.1109/NAS.2017.8026845 [details]
    • Wang, J., Taal, A., Martin, P., Hu, Y., Zhou, H., Pang, J., de Laat, C., & Zhao, Z. (2017). Planning virtual infrastructures for time critical applications with multiple deadline constraints. Future Generation Computer Systems, 75, 365-375. https://doi.org/10.1016/j.future.2017.02.001 [details]
    • Wang, J., de Laat, C., & Zhao, Z. (2017). QoS-aware virtual SDN network planning. In P. Chemouil, E. Monteiro, M. Charalambides, E. Madeira, P. Simões, S. Secci, L. Paschoal Gaspary, & C. R. P. dos Santos (Eds.), Proceedings of the IM 2017 - 2017 IFIP/IEEE International Symposium on Integrated Network Management: May 8-12, 2017, Lisbon, Portugal (pp. 644-647). IEEE. https://doi.org/10.23919/INM.2017.7987350 [details]

    2016

    • Taherizadeh, S., Jones, A., Taylor, I., Zhao, Z., Martin, P., & Stankovski, V. (2016). Runtime Network-level Monitoring Framework in the Adaptation of Distributed Time-critical Cloud Applications. In H. Arabnia, H. Ishii, K. Joe, & H. Nishikawa (Eds.), PDPTA 2016: proceedings of the 2016 International Conference on Parallel and Distributed Processing Techniques and Applications, Las Vegas, Nevada, USA, July 25-28, 2016 (pp. 78-83). CSREA Press. https://doi.org/10.5281/zenodo.53869 [details]
    • Zhou, H., Hu, Y., Wang, J., Martin, P., de Laat, C., & Zhao, Z. (2016). Fast and Dynamic Resource Provisioning for Quality Critical Cloud Applications. In 2016 IEEE 19th International Symposium on Real-Time Distributed Computing : proceedings: ISORC 2016 : 17-20 May 2016, York, United Kingdom (pp. 92-99). IEEE Computer Society. https://doi.org/10.1109/ISORC.2016.22 [details]
    • Zhou, H., Wang, J., Hu, Y., Su, J., Martin, P., de Laat, C., & Zhao, Z. (2016). Fast Resource Co-provisioning for Time Critical Application Based on Networked Infrastructures. In I. Foster, & N. Radia (Eds.), Proceedings, 2016 IEEE 9th International Conference on Cloud Computing: CLOUD 2016 : 27 June-2 July 2016, San Francisco, California, USA (pp. 802-805). IEEE Computer Society, Conference Publishing Services. https://doi.org/10.1109/CLOUD.2016.0111 [details]

    2015

    • Evans, K., Jones, A., Preece, A., Quevedo, F., Rogers, D., Spasić, I., Taylor, I., Stankovski, V., Taherizadeh, S., Trnkoczy, J., Suciu, G., Suciu, V., Martin, P., Wang, J., & Zhao, Z. (2015). Dynamically Reconfigurable Workflows for Time-Critical Applications. In Proceedings of WORKS 2015: the 10th Workshop on Workflows in Support of Large-Scale Science : November 15, 2015 Article 7 The Association for Computing Machinery. https://doi.org/10.1145/2822332.2822339 [details]
    • Mork, R., Martin, P., & Zhao, Z. (2015). Contemporary Challenges for Data-intensive Scientific Workflow Management Systems. In Proceedings of WORKS 2015: the 10th Workshop on Workflows in Support of Large-Scale Science : November 15, 2015 Article 4 The Association for Computing Machinery. https://doi.org/10.1145/2822332.2822336 [details]

    2013

    • Belloum, A. S. Z., Cushing, R., Koulouzis, S., Korkhov, V., Vasunin, D., Guevara-Masis, V., Zhao, Z., & Bubak, M. (2013). Support for Cooperative Experiments in e-Science: From Scientific Workflows to Knowledge Sharing. In I. Roterman-Konieczna (Ed.), Identification of ligand binding site and protein-protein interaction area (pp. 135-159). (Focus on structural biology; Vol. 8). Springer. https://doi.org/10.1007/978-94-007-5285-6_7 [details]

    2008

    • Belloum, A., Zhao, Z., & Bubak, M. (2008). International Workshop on Applications of Workflows in Computational Science (AWCS 08). In M. Bubak, G. D. van Albada, J. Dongarra, & P. M. A. Sloot (Eds.), Computational Science – ICCS 2008: 8th International Conference, Kraków, Poland, June 23-25, 2008 : proceedings (Vol. III, pp. 459-462). (Lecture Notes in Computer Science; Vol. 5103). Springer. https://doi.org/10.1007/978-3-540-69389-5_52 [details]

    2018

    • Koulouzis, S., Carval, T., Martin, P., Grenier, B., Chen, Y., Heikkinen, J., & Zhao, Z. (2018). Dynamic Optimization for Time-critical Data Services: A Case Study in Euro-Argo Research Infrastructure. 16012. Abstract from EGU (European Geosciences Union) General Assembly 2018, Austria.
    • Nieva de la Hidalga, A., Hardisty, A. R., Magagna, B., Martin, P. W., & Zhao, Z. (2018). Use of the ENVRI Reference Model to Support the Design of Environmental Research Infrastructures. 18552. Abstract from EGU (European Geosciences Union) General Assembly 2018, Austria.
    • Zhou, H., de Laat, C. T. A. M., & Zhao, Z. (2018). CloudsStorm: An Application-driven DevOps Framework for Managing Networked Infrastructures on Federated Clouds. Paper presented at the 3rd edition in the series of workshop on Interoperable infrastructures for interdisciplinary big data sciences (IT4RIs 18), Amsterdam, Netherlands.

    2017

    • Koulouzis, S., Martin, P. W., Carval, T., Grenier, B., Judeau, G., Wang, J., Zhou, H., de Laat, C. T. A. M., & Zhao, Z. (2017). Seamless Infrastructure Customisation and Performance Optimisation for Time-critical Services in Data Infrastructures. Paper presented at the Eighth International Workshop on Data-Intensive Computing in the Clouds, in the context of Supercomputing, Denver, United States.
    • Martin, P. W., Jones, A., Taylor, I., Stankovski, V., George, S. G., Ulisses, A., ... de Laat, C. T. A. M. (2017). Developing, provisioning and controlling time critical applications in Cloud. Paper presented at EU Project track at ESOCC17, Oslo, Norway.

    2016

    • Zhao, Z., Martin, P., de Laat, C., Jeffery, K., Jones, A., Taylor, I., Hardisty, A., Atkinson, M., Zuiderwijk-van Eijk, A., Yin, Y., & Chen, Y. (2016). Time critical requirements and technical considerations for advanced support environments for data-intensive research. Paper presented at International workshop on Interoperable infrastructures for interdisciplinary big data sciences, Porto, Portugal. https://doi.org/10.5281/zenodo.204756 [details]
    • Zhou, H., Martin, P., Su, J., de Laat, C., & Zhao, Z. (2016). A Flexible Inter-locale Virtual Cloud For Nearly Real-time Big Data Applications. Paper presented at International workshop on Interoperable infrastructures for interdisciplinary big data sciences, Porto, Portugal. https://doi.org/10.5281/zenodo.204774 [details]

    2012

    • Demchenko, Y., Zhao, Z., Grosso, P., Wibisono, A., & de Laat, C. T. A. M. (2012). Big data challenges for e-science infrastructure. Paper presented at The 7th International Conference on Cooperation and Promotion of Information Resources in Science and Technology (COINFO'12): Open Sharing in Cloud Context, .

    Prize / grant

    Journal editor

    • Lu, S. (editor), Deelman, E. (editor) & Zhao, Z. (editor) (2010). International Journal of Business Process Integration and Management (Journal).
    • Belloum, A. S. Z. (editor), Deelman, E. (editor) & Zhao, Z. (editor) (2006). Journal of Scientific Programming (Journal).

    Others

    • Zhao, Z. (chair), Prodan, R. (organiser), Keith, J. (organiser) & Ulisses, A. (organiser) (18-1-2018). the 3rd edition in the series of workshop on Interoperable infrastructures for interdisciplinary big data sciences (IT4RIs 18), Amsterdam. Real-time applications (disaster warning and response, traffic flow control, weather monitoring and forecasting, etc.) are among the most challenging (…) (organising a conference, workshop, ...). https://zenodo.org/record/1162865
    • Zhao, Z. (chair), Prodan, R. (organiser), Jeffery, K. (organiser) & Ulisses, A. (organiser) (18-1-2018). the 3rd edition in the series of workshop on Interoperable infrastructures for interdisciplinary big data sciences (IT4RIs 18), Amsterdam. Time critical applications and infrastructure optimizationthe 3rd edition in the series of workshop onInteroperable infrastructures for (…) (organising a conference, workshop, ...). https://staff.fnwi.uva.nl/z.zhao/workshop/it4ris/2018/
    • Zhao, Z. (participant) (29-11-2016). International workshop on Interoperable infrastructures for interdisciplinary big data sciences, Porto (organising a conference, workshop, ...).
    • Zhao, Z. (chair), Atkinson, M. (organiser) & Jeffery, K. (organiser) (2015). 1st International workshop on Interoperable infrastructures for interdisciplinary big data research (IT4RIs), IEEE e-Science 2015 (organising a conference, workshop, ...).

    2025

    • Li, N. (2025). Data quality control and research asset discovery for open science. [Thesis, fully internal, Universiteit van Amsterdam]. [details]
    • Wang, Y. (2025). From computational notebooks to collaborative workflows: A decentralized virtual research environment solution. [Thesis, fully internal, Universiteit van Amsterdam]. [details]

    2024

    • Liu, H. (2024). Robust resource management for time-critical tasks in the cloud-edge continuum. [Thesis, fully internal, Universiteit van Amsterdam]. [details]

    2023

    • Xin, R. (2023). Towards effective performance diagnosis for distributed applications. [Thesis, fully internal, Universiteit van Amsterdam]. [details]

    2022

    • Shi, Z. (2022). Enhancing service-level agreements using decentralized auctions and witnesses. [Thesis, fully internal, Universiteit van Amsterdam]. [details]

    2019

    • Hu, Y. (2019). Resource scheduling for quality-critical applications on cloud infrastructure. [Thesis, fully internal, Universiteit van Amsterdam]. [details]
    • Zhou, H. (2019). Seamless infrastructure programming and control for quality-critical cloud applications. [Thesis, fully internal, Universiteit van Amsterdam]. [details]

    2021

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