Noel Crespi

Professor, Head of Data Intelligence and Communication Engineering Lab. MSc Programme Director. Standardization Coordinator.

Institut Polytechnique de Paris

France

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Professor Noel Crespi is the Head of the Data Intelligence and Communication Engineering Lab at the Institut Polytechnique de Paris, France. He also serves as the MSc Programme Director and Standardization Coordinator. His research interests include adaptive anomaly detection in multivariate time series, digital twin smart cities, and access control in IoT networks, as evidenced by his recent publications. Professor Crespi's work addresses innovative challenges and solutions in sustainable urban development and cybersecurity within industrial applications.

Noel Crespi

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Articles (20)

Mixer-Transformer: adaptive anomaly detection with multivariate time series

Global perspectives on digital twin smart cities: Innovations, challenges, and pathways to a sustainable urban future

Distributed time-slotted channel hopping in IoT networks using multi-agent bernoulli bandits

DPS-IIoT: Non-interactive zero-knowledge proof-inspired access control towards information-centric Industrial Internet of Things

Leveraging ensemble deep models and llm for visual polysemy and word sense disambiguation

Hyper-IIoT: A Smart Contract-inspired Access Control Scheme for Resource-constrained Industrial Internet of Things

Security in Transformer Visual Trackers: A Case Study on the Adversarial Robustness of Two Models

Security in Transformer Visual Trackers: A Case Study on the Adversarial Robustness of Two Models

Data enrichment toolchain: A use-case for correlation analysis of air quality, traffic, and meteorological metrics in Madrid’s smart city

Offensive language detection in low resource languages: A use case of Persian language

IMC-NLT: Incomplete multi-view clustering by NMF and low-rank tensor

Widening Blockchain Technology toward Access Control for Service Provisioning in Cellular Networks

IMC-NLT: Incomplete multi-view clustering by NMF and low-rank tensor

COVAD: Content-oriented video anomaly detection using a self-attention based deep learning model

A blockchain-based secure storage and access control scheme for supply chain finance

Low-latency Dimensional Expansion and Anomaly Detection empowered Secure IoT Network

Video anomaly detection with NTCN-ML: A novel TCN for multi-instance learning

Towards Enabling Fault Tolerance and Reliable Green Communications in Next-Generation Wireless Systems

Exploiting Digital Twins as Enablers for Synthetic Sensing

Survey on the Use of Machine Learning for Quality of Transmission Estimation in Optical Transport Networks

Collaborators (5)

Xiaodi Huang

Faraz Malik Awan

Kashif Qureshi

Joaquin Garcia-Alfaro

Luis Sanchez

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