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Dr. Zhiming Zhao home
page |
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Multiscale
Networked Systems (MNS) University of
Amsterdam Email: z.zhao[at]uva.nl Tel: +31
638560996 Office: C.3.145 Science park 904, 1098XH Amsterdam the Netherlands |
We
are looking for 1. Part time programmers 2. Post doctors 3. PhD students... |
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Recent activities 1. IEEE DAPPS 2022 |
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I am an assistant professor
and senior researcher at University of Amsterdam (UvA).
I lead a team on “Quality Critical Distributed Computing” in the context of
Multiscale Networked Systems (MNS) research group, the
System and Networking Lab (SNE). My research
focuses on innovative programming and
control models for quality critical systems on programmable
infrastructures such as Clouds, Edges, and Software Defined Networking using
optimization, semantic linking, blockchain and artificial intelligence
technologies. I am specifically interested in big data management,
infrastructure optimization for data intensive applications, and trustworthy
service level agreement. Since 2014, I obtained more
than 3M euro funding from the EU H2020 research program to support my
research activities in UvA. I am the
scientific coordinator of the project SWITCH (Software
Workbench for interactive time critical and highly self-adaptive cloud
applications). I am the leader of the Data for Science theme
in the environmental science cluster project ENVRIPLUS and
lead the technical development work package in its follow up project ENVRI-FAIR.
I also lead the UvA effort in ARTICONF, CLARIFY, BLUECLOUD, and VRE4EIC projects.
I was involved in a number of other projects, such
as the EU FP7 ENVRI project.
I also lead the Virtual Research Environment (VRE) development in the LifeWatch Virtual Lab & Innovation Center. |
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Research: Quality Critical Applications on Programmable
Infrastructures |
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In both
scientific and industrial contexts, there are distributed application systems
which 1. have very high
business value (e.g., on-demand business collaboration platforms), or social
impact (e.g., for early warning of disasters); and 2. have very critical
requirements for Quality of Service (QoS) (e.g., tsunami emergency response
time) or quality of experience (QoE) (e.g., delivery
of ultra-high definition television, or
collaborative business interactions); but 3. are very difficult to
develop and operate because of their distributed nature and the high
requirements for the runtime environment, and in particular, the sophisticated
optimization mechanisms needed for developing and integrating the system
components. Cloud
environments provide virtualized, elastic, controllable, and quality
on-demand services for supporting complex application systems. However,
developing, deploying, and executing quality-critical applications in
programmable infrastructure is still difficult and challenging due to a lack
of effective programming and control mechanisms. My research
interests have revolved around modeling,
developing, controlling, and optimizing such Distributed Quality-Critical
Systems. I specifically focus on novel models for programming, executing,
and optimizing such applications on programmable infrastructures,
such as Cloud- and software-defined networking technologies. My basic
approach is to use autonomous agent technologies to decompose system
complexity, to develop distributed control and optimization intelligence by
combining both application logic and infrastructure programmability, and to
investigate self-adaptable cooperative control models for Cloud-based
quality-critical systems. |
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Leader: Dr. Zhiming
Zhao Researchers: ·
Dr. Uraz Odyurt, AI and cloud computing
(2021-) ·
Mr. Riccardo Bianchi (M.Sc), DevOps (2020-) ·
Dr. Siamak Farshidi, Knowledge base and data set search (2020-) ·
Dr. Spiros Koulouzis,
DRIP, CONF, VRE and use cases (2017-) Ph.D. students: ·
Yuandou Wang, Distributed data processing
(2020-) ·
Na Li, Knowledge discovery (2020-) ·
HongYun Liu, Cloud resource management (2019-) ·
Zhengqiu Zhu, Incentive models in crowd
applications (2020-) ·
Ruyue Xin, Virtual Infrastructure control
and adaptation (2019-) ·
Zeshun Shi, Trustworthy Virtual
infrastructure (2018-) Visiting scholars: ·
Mr. Ning Chen, Sensor network and robustness (2021-) Former members ·
Dr. Peng Chen, Cloud infrastructure
optimization (2020-2021) ·
Dr. Xiaofeng Liao,
Alignment, annotation (2017-2020) ·
Dr. Paul Martin, Semantic information
linking (2015-2018) ·
Dr. Arie Taal, Time critical
applications (2016-2019) ·
Junchao Wang, Virtual Infrastructure
planning (2015-2020) ·
Hu Yang, Time critical application deployment
(2015-2019) [thesis] ·
Huan Zhou, Virtual infrastructure provisioning
and DevOps (2015-2019)[thesis] |
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Funding and
projects (PI) |
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1.
EU H2020 CLARIFY
(CLoud ARtificial
Intelligence For pathologY). Grant No. 860627.
H2020-MSCA-ITN-2019 call. [Newsletter
in IvI] Duration: Nov 2019-Oct 2023. 2.
EU H2020 BLUECLOUD
(Blue-Cloud: Piloting innovative services for Marine Research & the Blue
Economy).H2020-BG-2018-2020. Grant No. 862409. Duration: Nov 2019-Oct 2022. 3.
EU H2020 ARTICONF (smART socIal media eCOsytstem in a blockchaiN Federated
environment). Grant No 825134. H2020-ICT-2018-2 call. Duration: January
2019-December 2021 [Newsletter in IvI]. 4.
EU H2020 ENVRIFAIR (ENVironmental Research Infrastructures building Fair
services Accessible for society, Innovation and Research). Grant No 824068.
H2020-INFRAEOSC-2018-2 call. Duration: January 2019-December 2022 [Newsletter in IvI]. Finished projects 1.
EU H2020 ENVRIPLUS (ENVironmental Research Infrastructures Providing
shared soLUtions for Science
and society). Leader of the Data for Science Theme. Grant No. 654182 (News
letter in IvI, ENVRIPLUS, EGI). Duration: May 2015- April 2019, Project
website: www.envriplus.eu. 2.
EU H2020 VRE4EIC (A Europe-wide
interoperable Virtual Research Environment to Empower multidisciplinary
research communities and accelerate Innovation and Collaboration). Grant
number 676247. H2020-EINFRA-2015-1.
Duration October 2015- September 2018. (Newsletter in IvI) 3. EU H2020 SWITCH (Software
Workbench for Interactive, Time Critical and Highly self-adaptive cloud
applications). Grant No 643963. H2020-ICT 9-2014-1 call: Tools and methods
for software development. Duration: February 2015- January 2018. (Newsletter in IvI)
(SWITCH
project). Participated
projects 1.
EU FP7 ENVRI.
Task leader, task 3.4: linking data and infrastructure - Common operations of
Environmental Research Infrastructure (ENVRI). Grant number 283465. 2.
EU FP7 Geysers, Researcher Generalised Architecture for Dynamic
Infrastructure Services 3.
Gigaport/CineGrid,
Researcher. Including network QoS in planning Workflows. 4.
Dutch Virtual
Laboratory for e-Science (VL-e), 2005-2009 5.
EU FP 6 CrossGrid, 2004-2005 |
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Please feel
free contact me for
details. 1. We are looking for part
time programmers. 2. Open phd/post doc positions in big data infrastructures and
applications. 3. We welcome CSC (Chinese
Scholar Council) funded students |
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Community |
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Editorial board 1.
Managing editor, Journal of cloud computing,
advances, systems and applications 2.
International journal of: Blockchains:
research and applications 3.
Journal of Circuits,
Systems and Computers Organizer/co-organizer
1. Special session: Using heterogeneous environmental
data for system-level science, 2018, Vienna, EGU
1. in Digital
Infrastructure for research 2016, Krakow, Poland 2. in Digital Infrastructure for research 2017, Brussels,
Belgium
Summer school 1. International summer school on data
management in environmental and earth sciences (2018
| 2019
| 2020) Workshop/Panel
chair
Program
committee
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Journals 1.
Zeshun Shi, Veno Ivankovic, Siamak Farshidi, Jayachander Surbiryala, Huan Zhou and Zhiming Zhao: AWESOME:
an auction and witness enhanced SLA model for decentralized cloud
marketplaces, Journal of Cloud Computing: Advances, Systems (2022), https://doi.org/10.1186/s13677-022-00292-8
2.
Zhu,
Z., Chen, B., Chen, H., Qiu, S., Fan, C., Zhao, Y.,
Guo, R., Ai, C., Liu, Z., Zhao, Z., Fang, L., Lu, X.: Strategy
evaluation and optimization with an artificial society toward a Pareto
optimum. The Innovation. 3, 100274 (2022). https://doi.org/10.1016/j.xinn.2022.100274
3.
Peng
Chen, Hongyun Liu, Ruyue
Xin, Thierry Carval, Jiale Zhao, Yunni Xia and Zhiming Zhao: Effectively
Detecting Operational Anomalies in Large-scale IoT Data Infrastructures by
using a GAN-based Predictive Model, The Computer Journal, to appear. 4.
Shi,
Z., Zhou, H., de Laat, C., Zhao, Z.: A Bayesian game-enhanced auction
model for federated cloud services using blockchain. Future Generation
Computer Systems. S0167739X22001881 (2022). https://doi.org/10.1016/j.future.2022.05.017.
5.
Zhao,
Z., Koulouzis, S., Bianchi, R., Farshidi,
S., Shi, Z., Xin, R., Wang, Y., Li, N., Shi, Y., Timmermans, J., Kissling,
W.D.: Notebook-as-a-VRE (NaaVRE): From private
notebooks to a collaborative cloud virtual research environment. Softw Pract Exp. spe.3098
(2022). https://doi.org/10.1002/spe.3098. 6.
Wang,
Y., Koulouzis, S., Bianchi, R., Li, N., Shi, Y.,
Timmermans, J., Kissling, W.D., Zhao, Z.: Scaling Notebooks as
Re-configurable Cloud Workflows. Data Intelligence. 4, 409–425 (2022). https://doi.org/10.1162/dint_a_00140. 7.
Wittenburg, P., Hardisty, A., Franc, Y.L., Mozaffari,
A., Peer, L., Skvortsov, N.A., Zhao, Z., Spinuso, A.: Canonical Workflows to Make Data FAIR. Data
Intelligence. 1–20 (2022). https://doi.org/10.1162/dint_a_00132 8.
Jiang,
W., Pan, S., Lu, C., Zhao, Z., Lin, S., Xiong,
M., He, Z.: Label entropy-based cooperative particle swarm optimization algorithm
for dynamic overlapping community detection in complex networks. Int J Intell Syst. int.22673 (2021). https://doi.org/10.1002/int.22673. 9.
Farshidi, S., Liao, X., Li, N., Goldfarb, D., Magagna, B., Stocker, M., Jeffery, K., Thijsse, P., Pichot, C., Petzold, A., Zhao, Z.: Knowledge sharing and
discovery across heterogeneous research infrastructures. Open Res Europe. 1,
68 (2021). https://doi.org/10.12688/openreseurope.13677.1.
10. Karandikar, N., Abhishek, R., Saurabh, N., Zhao, Z., Lercher, A., Marina, N., Prodan, R., Rong, C., Chakravorty, A.: Blockchain-based prosumer
incentivization for peak mitigation through temporal aggregation and contextual
clustering. Blockchain: Research and Applications. 2, 100016 (2021). https://doi.org/10.1016/j.bcra.2021.100016 11. Saurabh, N., Rubia, C., Palanisamy,
A., Koulouzis, S., Sefidanoski,
M., Chakravorty, A., Zhao, Z., Karadimce, A., Prodan, R.: The ARTICONF Approach to
Decentralized Car-Sharing. Blockchain: Research and Applications. 100013
(2021). https://doi.org/10.1016/j.bcra.2021.100013.
12. Zhou, H., Shi, Z., Ouyang, X. Zhao, Z.,
Building a blockchain-based decentralized ecosystem for cloud and edge
computing: an ALLSTAR approach and empirical study. Peer-to-Peer Network
Application. (2021). https://doi.org/10.1007/s12083-021-01198-z
[OA] 13. Calyam, P., Wilkins‐Diehr, N.,
Miller, M., Brookes, E.H., Arora, R., Chourasia, A., Jennewein,
D.M., Nandigam, V., Drew LaMar,
M., Cleveland, S.B., Newman, G., Wang, S., Zaslavsky,
I., Cianfrocco, M.A., Ellett,
K., Tarboton, D., Jeffery, K.G., Zhao, Z.,
González - Aranda, J., Perri, M.J., Tucker, G., Candela, L., Kiss, T., Gesing, S.: Measuring success for a future vision:
Defining impact in science gateways/virtual research environments.
Concurrency Computat Pract
Exper. cpe.6099 (2020). https://doi.org/10.1002/cpe.6099. 14. Zhu, Z., Chen, B., Liu, W., Zhao, Y., Liu, Z., and Zhao Z., A Cost-Quality Beneficial
Cell Selection Approach for Sparse Mobile Crowdsensing With Diverse Sensing
Costs, in IEEE Internet of Things Journal, vol. 8, no. 5, pp.
3831-3850, 1 March1, 2021, https://doi.org/10.1109/JIOT.2020.3024833.[OA]. 15. Zhang, L., Jiang, W., Zhao, Z.: Short -text feature
expansion and classification based on nonnegative matrix factorization. Int
Journal of Intelligent Systems. int.22290 (2020)https://doi.org/10.1002/int.22290[OA]. 16. Uriarte, R.B., Zhou, H., Kritikos,
K., Shi, Z., Zhao, Z., De Nicola,
R.: Distributed service- level agreement management with smart contracts and
blockchain. Concurrency Computat Pract Exper. (2020). https://doi.org/10.1002/cpe.5800. 17. Hu, Y., de Laat, C., Zhao, Z.: Optimizing Service Placement for Microservice
Architecture in Clouds. Applied Sciences. 9, 4663 (2019). https://doi.org/10.3390/app9214663. 18. Hu, Y., Zhou, H., de Laat, C., Zhao, Z.: Concurrent container scheduling on heterogeneous
clusters with multi-resource constraints. Future Generation Computer Systems.
102, 562–573 (2020). https://doi.org/10.1016/j.future.2019.08.025. 19. Remy, L., Ivanovic, D., Theodoridou,
M., Kritsotaki, A., Martin, P., Bailo,
D., Sbarra, M., Zhao, Z., Jeffery, K.: Building an Integrated Enhanced Virtual
Research Environment Metadata Catalogue. The Electronic Library. (2019) https://doi.org/10.1108/EL-09-2018-0183
[OA]. 20. Zhou, H., Hu, Y., Ouyang, X., Su,
J., Koulouzis, S., Laat, C., Zhao, Z.: CloudsStorm: A framework for
seamlessly programming and controlling virtual infrastructure functions
during the DevOps lifecycle of cloud applications. Softw:
Pract Exper. 49,
1421–1447 (2019). https://doi.org/10.1002/spe.2741. 21. 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., Van de Putte, A., Robinson, E., Schaap, D.,
Smirnov, A., Smith, N., Snowden, D., Spears, T., Stall, S., Tacoma, M., Thijsse, P., Tronstad, S., Vandenberghe, T., Wengren, M., Wyborn, L., Zhao,
Z.: Ocean FAIR Data Services. Front. Mar. Sci. 6, 440 (2019). https://doi.org/10.3389/fmars.2019.00440. 22. Martin, P., Remy, L., Theodoridou,
M., Jeffery, K., Zhao, Z.: Mapping
heterogeneous research infrastructure metadata into a unified catalogue for
use in a generic virtual research environment. Future Generation Computer
Systems. 101, 1–13 (2019). https://doi.org/10.1016/j.future.2019.05.076.
[OA] 23. Zhou, H., Ouyang, X., Su,
J., Laat, C., Zhao, Z.: Enforcing
trustworthy cloud SLA with witnesses: A game theory–based model using smart
contracts. Concurrency Computat Pract
Exper. (2019). https://doi.org/10.1002/cpe.5511. 24. Taal, A., Wang, J., de Laat, C., Zhao, Z.: Profiling the scheduling
decisions for handling critical paths in deadline-constrained cloud
workflows. Future Generation Computer Systems. 100, 237–249 (2019). https://doi.org/10.1016/j.future.2019.05.002. 25. Štefanič, P., Cigale, M., Jones,
A.C., Knight, L., Taylor, I., Istrate, C., Suciu,
G., Ulisses, A., Stankovski,
V., Taherizadeh, S., Salado, G.F., Koulouzis, S., Martin, P., Zhao, Z.: 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 (2019). https://doi.org/10.1016/j.future.2019.04.008. 26. Liao, X., Zhao,
Z.: Unsupervised Approaches for Textual Semantic Annotation, A Survey.
ACM Comput. Surv. 52,
1–45 (2019). https://doi.org/10.1145/3324473. 27. Liao, X., Bottelier, J., Zhao, Z.: A Column Styled Composable
Schema Matcher for Semantic Data-Types. Data Science
Journal. 18-25 (2019). https://doi.org/10.5334/dsj-2019-025. 28. Koulouzis, S., Martin, P., Zhou, H., Hu, Y., Wang, J.,
Carval, T., Grenier, B., Heikkinen, J., Laat, C., Zhao, Z.: Time-critical data
management in clouds: Challenges and a Dynamic Real-Time Infrastructure
Planner (DRIP) solution. Concurrency Computat Pract Exper. e5269 (2019). https://doi.org/10.1002/cpe.5269. 29. Taherizadeh, S., Jones, A.C., Taylor, I., Zhao, Z., Stankovski, V.: Monitoring
self-adaptive applications within edge computing frameworks: A
state-of-the-art review. Journal of Systems and Software. 136, 19–38 (2018). https://doi.org/10.1016/j.jss.2017.10.033. 30. Li, J., Yang, Y., Wang, X., Zhao, Z., Li, T.: A novel parallel distance metric-based approach
for diversified ranking on large graphs. Future Generation Computer Systems.
88, 79–91 (2018). https://doi.org/10.1016/j.future.2018.05.031. 31. Jiang, W., Zhai, Y.,
Zhuang, Z., Martin, P., Zhao, Z.,
Liu, J.-B.: Vertex Labelling and Routing for Farey-Type Symmetrically-Structured
Graphs. Symmetry. 10, 407 (2018). https://doi.org/10.3390/sym10090407. 32. Jiang, W., Zhai, Y.,
Zhuang, Z., Martin, P., Zhao, Z.,
Liu, J.-B.: An Efficient Method of Generating Deterministic Small-World and
Scale-Free Graphs for Simulating Real-World Networks. IEEE Access. 6,
59833–59842 (2018). https://doi.org/10.1109/ACCESS.2018.2875928. 33. Jiang, W., Zhai, Y.,
Martin, P., Zhao, Z.: Structure
Properties of Generalized Farey graphs based on Dynamical Systems for
Networks. Sci Rep. 8, 12194 (2018). https://doi.org/10.1038/s41598-018-30712-2. 34. Wang, J., Taal, A., Martin, P., Hu, Y., Zhou, H.,
Pang, J., de Laat, C., Zhao, Z.:
Planning virtual infrastructures for time critical applications with multiple
deadline constraints. Future Generation Computer Systems. 75, 365–375 (2017).
https://doi.org/10.1016/j.future.2017.02.001,
[Zenodo]. 35. Koulouzis, S., Belloum, A.S.Z., Bubak, M.T., Zhao,
Z., Živković, M., de Laat, C.T.A.M.: SDN-aware
federation of distributed data. Future Generation Computer Systems. 56, 64–76
(2016). https://doi.org/10.1016/j.future.2015.09.032. 36. Zhu, H., van der Veldt, K., Zhao, Z., Grosso, P., Pavlov, D., Soeurt,
J., Liao, X., de Laat, C.: A semantic enhanced Power Budget Calculator for
distributed computing using IEEE 802.3az. Cluster Comput.
18, 61–77 (2015). https://doi.org/10.1007/s10586-014-0395-7. 37. Ghijsen, M., van der Ham, J., Grosso, P., Dumitru, C., Zhu,
H., Zhao, Z., de Laat, C.: A
semantic-web approach for modelling computing infrastructures. Computers
& Electrical Engineering. 39, 2553–2565 (2013). https://doi.org/10.1016/j.compeleceng.2013.08.011. 38. Zhao,
Z., Grosso, P., van der Ham,
J., Koning, R., de Laat, C.: An agent-based network resource planner for
workflow applications. MGS. 7, 187–202 (2011). https://doi.org/10.3233/MGS-2011-0180. 39. Belloum, A., Inda, M.A., Vasunin, D., Korkhov, V., Zhao, Z., Rauwerda,
H., Breit, T.M., Bubak, M.,
Hertzberger, L.O.: Collaborative e-Science
Experiments and Scientific Workflows. IEEE Internet Comput.
15, 39–47 (2011). https://doi.org/10.1109/MIC.2011.87. 40. Zhao,
Z., van Albada,
D., Sloot, P.: Agent-Based Flow Control for HLA Components. SIMULATION. 81,
487–501 (2005). https://doi.org/10.1177/0037549705058060. 41. Kommers, P. and Zhao, Z.: Conceptual
Support with Virtual Reality in Web-based Learning, International Journal
of Continuing Engineering Education and Life-Long Learning, vol. 8, nr 1
1998. ISSN 0957-4344 (1998). https://www.inderscienceonline.com/doi/abs/10.1504/IJCEELL.1998.030134. Editorial
(special issues and proceedings) 42. Wittenburg, P., Hardisty, A., Mozzafari,
A., Peer, L., Skvortsov, N., Spinuso,
A., Zhao, Z.: Editors’ Note: Special Issue on Canonical Workflow
Frameworks for Research. Data Intelligence. 4, 149–154 (2022). https://doi.org/10.1162/dint_e_00122. 43. Rong, C., Zhao, Z.: Welcome to the
new Journal of Cloud Computing by Springer. J Cloud Comp. 10, 49,
s13677-021-00263–5 (2021). https://doi.org/10.1186/s13677-021-00263-5.
44. Zhao, Z., Taylor, I., Prodan, R.: Editorial for
FGCS Special issue on “Time-critical Applications on Software-defined
Infrastructures.” Future Generation Computer Systems. 112, 1170–1171 (2020). https://doi.org/10.1016/j.future.2020.07.056.[OA] [Content]
45. Zhao, Z., Altmeyer,
S., Keith J., Atkinson, M. and Ulisses A.: Nearly
real time data processing and time critical cloud applications. Proceedings
of the 2nd International workshop
on Interoperable infrastructures for interdisciplinary big data sciences
(IT4RIs 16), in the context of IEEE Real-time System Symposium (RTSS), Porto,
Portugal, November 29-December 2, (2016). [doi:10.5281/zenodo.204685] 46. Lu, S., Deelman,
E. & Zhao, Z.: Scientific
workflows special issue. International journal of business process
integration and management (pp. 1-2). Inder science
Enterprises Ltd. (2010). [Full text] 47. Zhao, Z., Belloum, A., Bubak, M.: Special section on workflow systems and
applications in e-Science. Future Generation Computer Systems. 25, 525–527
(2009). https://doi.org/10.1016/j.future.2008.10.011. 48. Belloum, A., Deelman,
E. & Zhao, Z.: Scientific
workflows. Scientific Programming, 14(3-4), 171-171 (2006). [Full text] Book
(Eds) 49. Zhao, Z., Hellström,
M. eds: Towards Interoperable Research Infrastructures for Environmental and
Earth Sciences: A Reference Model Guided Approach for Common Challenges.
Springer International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4.
[ENVRI archive][Book interview] Book
chapters 50. Jeffery, K., Pursula, A., Zhao, Z.: ICT Infrastructures for
Environmental and Earth Sciences. In: Zhao,
Z. and Hellström, M. (eds.) Towards
Interoperable Research Infrastructures for Environmental and Earth Sciences.
pp. 17–29. Springer International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_2. 51. Magagna, B., Martin, P., de la Hidalga,
A.N., Atkinson, M., Zhao, Z.:
Common Challenges and Requirements. In: Zhao,
Z. and Hellström, M. (eds.) Towards
Interoperable Research Infrastructures for Environmental and Earth Sciences.
pp. 30–57. Springer International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_3. 52. de la Hidalga, A.N.,
Hardisty, A., Martin, P., Magagna, B., Zhao, Z.: The ENVRI Reference Model.
In: Zhao, Z. and Hellström, M. (eds.) Towards Interoperable Research
Infrastructures for Environmental and Earth Sciences. pp. 61–81. Springer
International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_4. 53. Zhao, Z., Jeffery, K.: Reference
Model Guided Engineering. In: Zhao, Z. and Hellström,
M. (eds.) Towards Interoperable Research Infrastructures for Environmental
and Earth Sciences. pp. 82–99. Springer International Publishing, Cham
(2020). https://doi.org/10.1007/978-3-030-52829-4_5. 54. Martin, P., Liao, X., Magagna,
B., Stocker, M., Zhao, Z.: Semantic
and Knowledge Engineering Using ENVRI RM. In: Zhao, Z. and Hellström, M. (eds.)
Towards Interoperable Research Infrastructures for Environmental and Earth
Sciences. pp. 100–119. Springer International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_6. 55. Quimbert, E., Jeffery, K., Martens, C., Martin, P., Zhao, Z.: Data Cataloguing. In: Zhao, Z. and Hellström,
M. (eds.) Towards Interoperable Research Infrastructures for Environmental
and Earth Sciences. pp. 140–161. Springer International Publishing, Cham
(2020). https://doi.org/10.1007/978-3-030-52829-4_8. 56. Koulouzis, S., Martin, P., Zhao, Z.: Virtual Infrastructure Optimisation. In: Zhao, Z. and Hellström,
M. (eds.) Towards Interoperable Research Infrastructures for Environmental
and Earth Sciences. pp. 192–207. Springer International Publishing, Cham (2020).
https://doi.org/10.1007/978-3-030-52829-4_11. 57. Magagna, B., Goldfarb, D., Martin, P., Atkinson, M., Koulouzis, S., Zhao,
Z.: Data Provenance. In: Zhao, Z.
and Hellström, M. (eds.) Towards Interoperable
Research Infrastructures for Environmental and Earth Sciences. pp. 208–225.
Springer International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_12. 58. Martin, P., Magagna, B.,
Liao, X., Zhao, Z.: Semantic
Linking of Research Infrastructure Metadata. In: Zhao, Z. and Hellström, M. (eds.)
Towards Interoperable Research Infrastructures for Environmental and Earth
Sciences. pp. 226–246. Springer International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_13. 59. Koulouzis, S., Carval, T., Heikkinen, J., Pursula,
A., Zhao, Z.: Case Study: Data
Subscriptions Using Elastic Cloud Services. In: Zhao, Z. and Hellström, M. (eds.)
Towards Interoperable Research Infrastructures for Environmental and Earth
Sciences. pp. 293–306. Springer International Publishing, Cham (2020). https://doi.org/10.1007/978-3-030-52829-4_16. 60. Zhao,
Z., Jeffery, K., Stocker, M.,
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& de Laat, C.: Quality guaranteed media delivery over
advanced network. Chapter in book Next Generation Content Delivery
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Adaptable Framework for Entity Matching Model Selection in Business
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R., Shi, Z., Chen, P., Zhao, Z.: A Decentralized Service Control
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[OA] 69. Poon, L., Farshidi, S.,
Li, N., Zhao, Z.: Unsupervised Anomaly Detection in Data Quality
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[OA](Best student paper) 71. Shi Ze., Farshidi S., Zhou
H., Zhao Z., An Auction and Witness Enhanced Trustworthy SLA Model
for Decentralized Cloud
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[OA] 72. Xin R., Mohazzab J., Shi
Z., and Zhao Z.: CBProf: Customisable
Blockchain-as-a-service Performance Profiler in Cloud Environments,
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Bianchi, Robin van der Linde, Yuandou Wang and Zhiming
Zhao, SPIRIT: A microservice-based framework for interactive Cloud
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S., Li N., Bianchi R., Zhao, Z.: FAIR-Cells: an interactive tool for
enabling the FAIRness of code fragments in Jupyter notebooks, in the proceedings of international
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[Zenodo] 75.
Zhao, Z., Rong, C., Jaatun, M.G.: A Trustworthy Blockchain-based
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Z.: Decentralized workflow management on software defined infrastructure,
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[OA]. 78. Zhou, H., Ouyang, X., Zhao, Z.: ALLSTAR: A Blockchain Based Decentralized Ecosystem for
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D., Glaves, H.M., Bundke,
U., Zhao, Z.: ENVRI-FAIR -
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and Research. In: 2019 15th International Conference on eScience (eScience).
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S., Shi, Z., Liao, X., Gordiyenko, J.: Teaching
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[OA]. 84. Prodan, R., Saurabh, N., Zhao, Z.,
Orton-Johnson, K., Chakravorty, A., Karadimce, A., and Ulisses, A.:
ARTICONF: Towards a Smart Social Media Ecosystem in a Blockchain Federated
Environment, in the 7th Workshop on Large Scale Distributed Virtual
Environments, in the context of Euro-Par conference 2019, Gottingen, Germany
(2019) https://doi.org/10.1007/978-3-030-48340-1_32
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S., Rubia, C., and Zhao, Z.:
Co-located and Orchestrated Network Fabric (CONF): An Automated Cloud Virtual
Infrastructure for Social Network Applications. in the 7th Workshop on Large
Scale Distributed Virtual Environments, in the context of Euro-Par conference
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[OA] (Best student paper candidate). 87. Zhao,
Z., Liao, X., Martin, P.,
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D., Stocker, M., Goldfarb, D., Magagna, B.:
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[OA] Best presentation in the session. 91. Shi, Z., Zhou, H., Hu, Y., Jayachander,
S., de Laat, C., Zhao, Z.: Operating
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Sawtooth. In: 2019 18th International Symposium on Parallel and Distributed
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[OA] Best paper award. 93. Zhou, H., Koulouzis, S.,
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Chi, M., de Laat, C., Zhao, Z.: Empowering
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Zhou,
H., Taal, A., Koulouzis, S., Wang, J., Hu, Y.,
Suciu, G., Poenaru, V., de Laat, C., Zhao, Z.: Dynamic Real-Time
Infrastructure Planning and Deployment for Disaster Early Warning Systems.
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Zhou,
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Wang,
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Taherizadeh, S., Taylor, I., Jones, A., Zhao, Z., Stankovski, V.: A Network Edge Monitoring Approach for
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Hu,
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Zhao, Z., Belloum, A., Bubak, M., Hertzberger, B.:
Support for Cooperative Experiments in VL-e: From Scientific Workflows to
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reviewed abstracts and posters 166.
Andreas
Petzold, Ari Asmi, Rita Gomes, Katrin Seemeyer, Angeliki Adamaki, Alexander T Vermeulen, Daniele Bailo, Keith G Jeffery, Helen Glaves,
Zhiming Zhao, Markus Stocker, Margareta Hellström
(2021) Creating ENVRI-hub, the Open-Access Platform of the Environmental
Sciences Community in Europe, AGU [2021AGUFMIN53A..04P] 167.
Alex
Boyko, Siamak Farshidi, Zhiming
Zhao, State-of-the-art instance matching methods for knowledge graphs,
The Sixteenth International Workshop on Ontology Matching (OM-2021), in the
context of 20th International Semantic Web Conference ISWC-2021, online [OA] 168.
Spiros
Koulouzis, Yifang Shi, Yuandou Wan, Riccardo Bianchi, Daniel Kissling, Zhiming
Zhao (2021) Enabling LiDAR data processing as a service in a Jupyter environment, EGU 2021 [10.5194/egusphere-egu21-8294] 169.
Andreas
Petzold, Ari Asmi, Katrin Seemeyer,
Angeliki Adamaki, Alex
Vermeulen, Daniele Bailo, Keith Jeffery, Helen Glaves, Zhiming Zhao, Markus Stocker, Margareta Hellström (2021) Advancing the FAIRness
and Openness of Earth system science in Europe, EGU [10.5194/egusphere-egu21-8052] 170.
Xiaofeng Liao, Doron Goldfarb, Barbara Magagna,
Markus Stocker, Peter Thijsse, Dick Schaap, Zhiming
Zhao (2020) ENVRI knowledge base: A community knowledge base for
research, innovation and society, EGU,
April 2020 [10.5194/egusphere-egu2020-20708] 171.
Zhao, Z., Martin, P., Koulouzis, S.: (2019)
Optimizing environmental data services on federated Cloud and
e-Infrastructures, EGU, April 2019 [2019EGUGA..21.3683Z] 172.
Koulouzis, S., Carval, T., Martin, P., Grenier,
B., Chen, Y., Heikkinen, J., Zhao, Z.: Dynamic Optimization for
Time-critical Data Services: A Case Study in Euro-Argo Research
Infrastructure. 20th EGU General
Assembly, EGU2018, Proceedings from the conference held 4-13 April, 2018 in Vienna, Austria, p.16012. [2018EGUGA..2016012K] 173.
Abraham Nieva de la Hidalga,
Alex R Hardisty, Barbara Magagna, Paul W
Martin, Zhiming Zhao (2018) Use of the ENVRI Reference Model
to Support the Design of Environmental Research Infrastructures, 20th EGU
General Assembly, EGU2018, Proceedings from the conference held 4-13 April,
2018 in Vienna, Austria, p.18552 [2018EGUGA..2018552N] 174.
Kutsch, W. L.; Zhao, Z.; Hardisty,
A.; Hellström, M.; Chin, Y.; Magagna, B.; Asmi, A.; Papale,
D.; Pfeil, B.; Atkinson, M. (2017) Data interoperabilty between European Environmental
Research Infrastructures and their contribution to global data networks, AGU
2018, American Geophysical Union, Fall Meeting 2017, abstract
#IN44B-01. [2017AGUFMIN44B..01K] Technical
report and newsletters 175.
Zhao,
Z., Martin, P. Jeffery
K., (2017) VRE in the Data for Science Approach to Common Challenges in
ENVRIPLUS, ERCIM, Newsletter, April 2017 176.
Zhao,
Z. (2016) Data for
science: software and solutions for the environmental sciences, EGI Newsletter, January 2016. 177.
Zhao,
Z., (2015) Data for
Science theme: software and solutions to address common challenges facing
environmental research infrastructures, 1st ENVRIPLUS Newsletter, November 2015. 178.
Ghijsen, M.,
Ham, J. van der, Grosso, P., Dumitru, C., Zhu, H., Zhao, Z. & Laat,
C. de (2013). A
semantic-web approach for modeling computing
infrastructures.
(SNE technical report 2013-01). Amsterdam: Universiteit van
Amsterdam, System and Network Engineering. [Full
text] 179.
Hertzberger, L.O., Belleman,
R.G., Jansen, M.G., Zhao, Z., Hooft, P. van, Belloum, A.S.Z., Mirzadeh,
N., Yakali, H.H., Liere,
R. van, Nuallain, B.S., Verstoep, K., Groep, D.L.
& Bouwhuis, M.C. (2005). Recommendation
to VLeIT: Scientific workflow management
systems for the PoC r1. (Internal
report). Amsterdam: Informatics Institute. Supervised
PhD thesis 180.
Yang Hu (2019) Resource
Scheduling for Quality-Critical Applications on Cloud Infrastructure,
University of Amsterdam, [ISBN: 978-94-028-1713-3]. 181.
Huan Zhou (2019) Seamless
Infrastructure Programming and Control for Quality-critical Cloud
Applications, [ISBN: 978-94-028-1727-0] In
Chinese 182.
Zhao,
Z., Liao, X., Wang,
X., Ruan, C., Zhu, Y., Feng,
D. (2019), An Reference Model
approach for developing agriculture big data infrastructures, Journal of East
China Normal University (Natural Sc
2019 Vol.2019 (2): 77-96, [10.3969/j.issn.1000-5641.2019.02.009] 183.
Demchenko, Y., Zhao, Z., Grosso,
P., Wibisono, A., de Laat, C., (2013) 科研信息化基础 设施的大数据挑战 (Big Data Challenges for e-Science
Infrastructure) China
Science and Technology Resources Review, Vol.45 No.1 30-35,40 Jan. 2013. ISSN
1674-1544 [10.3772/j.issn.1674-1544.2013.01.006] |
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Update date: July 12, 2022