Gagangeet Singh Aujla

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Assistant Professor of Computer Science

University of Durham

United Kingdom

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About

Dr. Gagangeet Singh Aujla is an Assistant Professor of Computer Science at Durham University, UK. His research focuses on advanced topics in healthcare IoT, edge AI frameworks, renewable energy networks, and software-defined networking for smart communities. Recent publications include works on deep learning applications for Alzheimer's care and scalable blockchain solutions for the Internet of Things.

Recent Grants

Grant: Close

PACE: Privacy-Aware Cloud Ecosystems

Open Date: 2018-08-01

Close Date: 2021-12-01

Grant: Close

QoS-aware Energy Management Scheme for Sustainable Data Centers using Renewable Energy Sources

Open Date: 2017-07-01

Close Date: 2019-06-01

Grant: Close

Smart Demand Response Framework for Load Optimization in an Electric Grid

Open Date: 2017-02-01

Close Date: 2018-01-01

Grant: Close

SDN-based Data Center Energy Managemenng System using RES and Electric Vehicles

Open Date: 2016-12-01

Close Date:

Grant: Close

SDN-based Data Center Energy Managemenng System using RES and Electric Vehicles

Open Date: 2016-12-01

Close Date:

Articles (21)

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2022

Collaborators (5)

Amritpal Singh

Northumbria University

UNITED KINGDOM

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Neeraj Kumar

Honorary Professor

USUHS/HJF

POLAND

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JING JIANG

Senior Lecturer

Northumbria University

UNITED KINGDOM

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Tomasz Szydlo

Akademia Górniczo-Hutnicza im Stanislawa Staszica w Krakowie

POLAND

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Omer Rana

UNITED KINGDOM

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Gagangeet Singh Aujla

Research Interests

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About

Recent Grants

Articles (21)

DeTrAs: deep learning-based healthcare framework for IoT-based assistance of Alzheimer patients

Two-Fold Strategy Toward Sustainable Renewable Energy Networks When Uncertainty Is Certain

A comprehensive survey on software‐defined networking for smart communities

Energy-Aware and Explainable Automated Machine Learning for Anomaly Detection in Healthcare IoT

Scalable and Reliable Data Framework for Sensor-Enabled Virtual Power Plant Digital Twin

SecureFlow: Knowledge and data-driven ensemble for intrusion detection and dynamic rule configuration in software-defined IoT environment

Federated-ANN-Based Critical Path Analysis and Health Recommendations for MapReduce Workflows in Consumer Electronics Applications

RootPath: Root Cause and Critical Path Analysis to Ensure Sustainable and Resilient Consumer-Centric Big Data Processing Under Fault Scenarios

Explainable Edge AI Framework for IoD-Assisted Aerial Surveillance in Extreme Scenarios

Trustworthy IAP: An Intelligent Applications Profiler to Investigate Vulnerabilities of Consumer Electronic Devices

Towards Scalable and Secure Blockchain in Internet of Things: A Preference-Driven Committee Member Auction Consensus Approach

Evolution from ancient medication to human‐centered Healthcare 4.0: A review on health care recommender systems

GDPR compliance verification through a user-centric blockchain approach in multi-cloud environment

Compliance Checking of Cloud Providers: Design and Implementation

Reinforcement Learning for Edge Device Selection Using Social Attribute Perception in Industry 4.0

Adaptive Recovery Mechanism for SDN Controllers in Edge-Cloud Supported FinTech Applications

Rendering Secure and Trustworthy Edge Intelligence in 5G-Enabled IIoT Using Proof of Learning Consensus Protocol

Health Monitoring and Diagnosis for Geo-Distributed Edge Ecosystem in Smart City

Dynamic bandwidth slicing for time-critical IoT data streams in the edge-cloud continuum

MapChain: A Blockchain-Based Verifiable Healthcare Service Management in IoT-Based Big Data Ecosystem

A distributed task orchestration scheme in collaborative vehicular cloud edge networks

Collaborators (5)

Amritpal Singh

Neeraj Kumar

JING JIANG

Tomasz Szydlo

Omer Rana

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