Burak Kantarci

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Full Professor

University of Ottawa

Canada

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About

Burak Kantarci is a Full Professor at the University of Ottawa, Canada. His research interests encompass intelligent applications of Web 3.0 and the Metaverse, autonomous vehicles, and machine learning techniques. Recent publications explore user acceptance factors for autonomous delivery systems, multi-sensor fusion in vehicles, and optimization strategies in 5G edge computing.

Recent Grants

Grant: Close

Context-aware anomaly detection in Internet of Biometric Things (IoBT)

Open Date: 2015-06-01

Close Date: 2016-05-01

Grant: Close

Wireless Internet of Things Lab

Open Date: 2015-06-01

Close Date: 2017-05-01

Grant: Close

CRII:SaTC: Energy Efficient Participatory Data Collection Schemes and Context-Aware Incentives for Trustworthy Crowdsensing via Mobile Social Networks

Open Date: 2015-04-01

Close Date: 2017-03-01

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Collaborators (4)

Anna Maria Vegni

Professor of the course "Telecommunication Networks Laboratory"

Università degli Studi di Roma La Sapienza

ITALY

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MURAT SIMSEK

Senior Research Associate, Entrepreneurship in Residence, Part-time Professor

University of Ottawa

CANADA

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Hussein T. Mouftah

University of Ottawa

CANADA

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Lucas Carvalho Cordeiro

The University of Manchester

UNITED KINGDOM

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Burak Kantarci

Research Interests

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About

Recent Grants

Articles (20)

Introduction to the Special Issue on Intelligent Applications of Web 3.0 and Metaverse for Connected Autonomous Vehicles

A comparative review of user acceptance factors for drones and sidewalk robots in autonomous last mile delivery

Machine Learning-Driven Truck–Drone Collaborative Delivery for Time- and Energy-Efficient Last-Mile Deliveries

Intelligent multi-sensor fusion and anomaly detection in vehicles via deep learning

Joint Optimization of Completion Ratio and Latency of Offloaded Tasks With Multiple Priority Levels in 5G Edge

Rethinking detection based table structure recognition for visually rich document images

Active RIS-NOMA Uplink in URLLC, Jamming Mitigation via Surrogate and Deep Learning

DT-DDNN: A Physical Layer Security Attack Detector in 5G RF Domain for CAVs

Deep Fusion Intelligence: Enhancing 5G Security Against Over-the-Air Attacks

FLARE: Flying Learning Agents for Resource Efficiency in Next-Gen UAV Networks

Edge Learning for 6G-Enabled Internet of Things: A Comprehensive Survey of Vulnerabilities, Datasets, and Defenses

TableStrRec: framework for table structure recognition in data sheet images

AI-enabled cluster head selection through modified density based clustering in Aeronautical Ad Hoc Networks

Practical Byzantine Fault Tolerance Based Robustness for Mobile Crowdsensing

Utility-Aware Legitimacy Detection of Mobile Crowdsensing Tasks via Knowledge-Based Self Organizing Feature Map

Data Instrumentation From IoT Network Traffic as Support for Security Management

Machine Learning-Enabled IoT Security: Open Issues and Challenges Under Advanced Persistent Threats

2DF-IDS: Decentralized and differentially private federated learning-based intrusion detection system for industrial IoT

Use of Mobile Crowdsensing in Disaster Management: A Systematic Review, Challenges, and Open Issues

A Continuous Actor–Critic Deep Q-Learning-Enabled Deployment of UAV Base Stations: Toward 6G Small Cells in the Skies of Smart Cities

Collaborators (4)

Anna Maria Vegni

MURAT SIMSEK

Hussein T. Mouftah

Lucas Carvalho Cordeiro

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