Institution profile

Institute of Communication & Computer Systems

Academic institutioneurope · gr
Official website
Research library5linked papers
Opportunities0open roles
Selected work

Representative Papers

H2: A Dual Hybrid Semantic Data Lake Architecture for Medical Data Harmonization with Human-In-the-Loop verified, LLM Driven Metadata Annotation System

Aug 08, 2026

This study addresses the challenges posed by the high heterogeneity of healthcare data and the lack of effective metadata management, which often degrade conventional data lakes into “data swamps,” impeding data interoperability and machine learning (ML) readiness. To overcome these limitations, the authors propose a dual-hybrid semantic data lake architecture that synergistically integrates the dynamic modeling capabilities of knowledge graphs with the metadata generation power of large language models (LLMs). A human-in-the-loop validation mechanism is incorporated to enable automated metadata annotation and high-level semantic alignment. This approach establishes, for the first time, semantic linkages within a data lake explicitly oriented toward ML operability, substantially enhancing the discoverability and computability of heterogeneous medical data while supporting intelligent recommendation of suitable ML methods.

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A Deployed Hybrid Vehicle-in-the-Loop Platform for Validating Cooperative Perception

Jul 15, 2026

This work addresses the absence of a verifiable physical-virtual hybrid platform capable of generating cooperative perception validation evidence compliant with European autonomous driving regulations. The authors present the first mixed vehicle-in-the-loop (ViL) platform integrating real vehicles with CARLA digital twins in a public-road testbed, where V2X communication pipelines couple ETSI CAM/CPM messages to enable runtime fusion into probabilistic occupancy grids. The platform facilitates multi-scenario cooperative perception evaluation and identifies localization noise as the dominant error source. Experimental results demonstrate that cooperative perception substantially extends field-of-view coverage and improves occupancy cell recall; however, under moderate-to-high localization noise, its associated uncertainty surpasses weather effects as the primary performance bottleneck.

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Beyond Line of Sight: Hybrid Validation of V2X Collective Perception in Complex Scenarios

Jul 01, 2026

This work addresses the limitations of single-vehicle perception in vehicle-to-everything (V2X) systems, where restricted sensor coverage hinders reliable cooperative awareness. To overcome this challenge, the authors propose a Bayesian fusion–based collaborative perception framework that integrates heterogeneous sensor data from multiple agents to construct interpretable probabilistic occupancy grids. The system’s performance is evaluated through a hybrid validation approach combining CARLA-based virtual simulation with real-vehicle-in-the-loop testing, ensuring reproducible and certifiable assessment. In a roundabout scenario, collaboration among six vehicles expands perceptual coverage by 260% and significantly improves occupancy grid recall from 0.82 (single-vehicle baseline) to 0.94, thereby substantially enhancing environmental awareness in occluded regions beyond line-of-sight.

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Recent publications

Latest Papers

H2: A Dual Hybrid Semantic Data Lake Architecture for Medical Data Harmonization with Human-In-the-Loop verified, LLM Driven Metadata Annotation System

Aug 08, 2026

This study addresses the challenges posed by the high heterogeneity of healthcare data and the lack of effective metadata management, which often degrade conventional data lakes into “data swamps,” impeding data interoperability and machine learning (ML) readiness. To overcome these limitations, the authors propose a dual-hybrid semantic data lake architecture that synergistically integrates the dynamic modeling capabilities of knowledge graphs with the metadata generation power of large language models (LLMs). A human-in-the-loop validation mechanism is incorporated to enable automated metadata annotation and high-level semantic alignment. This approach establishes, for the first time, semantic linkages within a data lake explicitly oriented toward ML operability, substantially enhancing the discoverability and computability of heterogeneous medical data while supporting intelligent recommendation of suitable ML methods.

0 citationsRead paper

A Deployed Hybrid Vehicle-in-the-Loop Platform for Validating Cooperative Perception

Jul 15, 2026

This work addresses the absence of a verifiable physical-virtual hybrid platform capable of generating cooperative perception validation evidence compliant with European autonomous driving regulations. The authors present the first mixed vehicle-in-the-loop (ViL) platform integrating real vehicles with CARLA digital twins in a public-road testbed, where V2X communication pipelines couple ETSI CAM/CPM messages to enable runtime fusion into probabilistic occupancy grids. The platform facilitates multi-scenario cooperative perception evaluation and identifies localization noise as the dominant error source. Experimental results demonstrate that cooperative perception substantially extends field-of-view coverage and improves occupancy cell recall; however, under moderate-to-high localization noise, its associated uncertainty surpasses weather effects as the primary performance bottleneck.

0 citationsRead paper

Beyond Line of Sight: Hybrid Validation of V2X Collective Perception in Complex Scenarios

Jul 01, 2026

This work addresses the limitations of single-vehicle perception in vehicle-to-everything (V2X) systems, where restricted sensor coverage hinders reliable cooperative awareness. To overcome this challenge, the authors propose a Bayesian fusion–based collaborative perception framework that integrates heterogeneous sensor data from multiple agents to construct interpretable probabilistic occupancy grids. The system’s performance is evaluated through a hybrid validation approach combining CARLA-based virtual simulation with real-vehicle-in-the-loop testing, ensuring reproducible and certifiable assessment. In a roundabout scenario, collaboration among six vehicles expands perceptual coverage by 260% and significantly improves occupancy grid recall from 0.82 (single-vehicle baseline) to 0.94, thereby substantially enhancing environmental awareness in occluded regions beyond line-of-sight.

0 citationsRead paper