Long Le

Full Professor

Institut national de la recherche scientifique

Canada

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About

Long Le is a Full Professor at the Institut national de la recherche scientifique in Canada. His research interests encompass generative diffusion models, wildlife localization systems, electric vehicle charging strategies, and the application of blockchain within the metaverse. He has recently published articles focusing on machine learning techniques for energy efficiency and security applications in advanced networking environments.

Articles (18)

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2025

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2024

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2022

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2022

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2022

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2022

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2021

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2021

Collaborators (1)

Christof Roehrig

Professor

Fachhochschule Dortmund

GERMANY

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Long Le

Research Interests

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Contact this professor

About

Articles (18)

Attacks and Defenses for Generative Diffusion Models: A Comprehensive Survey

WSN-based wildlife localization framework in dense forests through optimization techniques

Machine-Learning-Assisted Transmission Power Control for LoRaWAN Considering Environments With High Signal- to -Noise Variation

Electric vehicle charging design: The factored action based reinforcement learning approach

Integrated Computation Offloading, UAV Trajectory Control, Edge-Cloud and Radio Resource Allocation in SAGIN

Blockchain-Empowered Metaverse: Decentralized Crowdsourcing and Marketplace for Trading Machine Learning Data and Models

Security for the Metaverse: Blockchain and Machine Learning Techniques for Intrusion Detection

Trust-Free Blockchain Framework for AI-Generated Content Trading and Management in Metaverse

Building energy management and Electric Vehicle charging considering battery degradation and random vehicles’ arrivals and departures

Machine-Learning-Based Combined Path Loss and Shadowing Model in LoRaWAN for Energy Efficiency Enhancement

Blockchain Meets Metaverse and Digital Asset Management: A Comprehensive Survey

MetaCIDS: Privacy-Preserving Collaborative Intrusion Detection for Metaverse based on Blockchain and Online Federated Learning

LoRaWAN Path Loss Measurements in an Urban Scenario including Environmental Effects

Multi-UAV Trajectory Control, Resource Allocation, and NOMA User Pairing for Uplink Energy Minimization

Integrated UAV Trajectory Control and Resource Allocation for UAV-Based Wireless Networks With Co-Channel Interference Management

UAV Placement and Resource Allocation for Intelligent Reflecting Surface Assisted UAV-Based Wireless Networks

Computation Offloading in MIMO Based Mobile Edge Computing Systems Under Perfect and Imperfect CSI Estimation

Resource Allocation, Trajectory Optimization, and Admission Control in UAV-Based Wireless Networks

Collaborators (1)

Christof Roehrig

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