Trustworthy AI-based Performance Diagnosis Systems for Cloud Applications: A Review, ACM Computing Survey, 2025. This article systematically reviews trustworthiness requirements in AI-based performance diagnosis systems. We introduce trustworthiness requirements and extract six key requirements from a technical perspective, including data privacy, fairness, robustness, explainability, efficiency, and human intervention.
Our work evaluates and analyzes the performance and security of the quantum position verification task under real-world constraints, bringing this quantum network application one step closer to practical deployment.
This work was supported by the Dutch National Growth Fund (NGF), as part of the Quantum Delta NL program.
abstract: Preserving privacy in blockchain-based systems is crucial for ensuring anonymity and confidentiality during transactions. While cryptographic solutions can address on-chain privacy concerns, their implementation on blockchains may introduce performance overhead, which remains unclear to researchers and practitioners.
Data quality plays a vital role in scientific research and decision-making across industries. Thus it is crucial to incorporate the data quality control (DQC) process, which comprises various actions and operations to detect and correct data errors.
On Thursday 14 March, the Senior Teaching Qualification certificates were awarded during a festive ceremony. Dr. Zhiming Zhao from MNS together with the other fifteen UvA lecturers received the certificate.
The EU Horizon Europe project OSCARS (Open Science Clusters’ Action for Research & Society) has been successfully kicked off 13/March 2024 in Thessaloniki, Greece. Coordinated by CNRS (French National Centre for Scientific Research), the project aims to bring together European Research Infrastructures (RIs) organized into five “Science Clusters” along the ESFRI thematic research domains1.
The project has 18 partners from 8 countries and will last three years; the consortium includes five clusters of European research infrastructures, including environmental earth science, life science, particle physics, Photon and neutron, and social science.
Title: Ocean Data Quality Assessment through Outlier Detection-enhanced Active Learning
BLUECLOUD 2026 partner CNR, 29th Jan 2024
This work has been partially funded by the European Union’s Horizon research and innovation program by the CLARIFY (860627), BLUECLOUD 2026 (101094227), ENVRI-FAIR (824068) and ARTICONF (825134), by the LifeWatch ERIC, and by the NWO LTER-LIFE project.
Abstract:
A computational notebook search system called CNSVRE has been proposed to address shortcomings in existing solutions for Virtual Research Environments (VREs). Existing approaches lack focus on the specific information needs of scientific researchers and struggle with relevance evaluation due to the mixed nature of text and code in computational notebooks.