Menu

Menu controller icon
Staff profile image
Postdoctoral Researcher

Omer Ali

ORCID: 0000-0002-0114-0457

Qualifications:
  • PhD in Electrical Engineering (Universiti Sains Malaysia) - 2023
  • MSc in Communications Engineering (University of Manchester) - 2008
  • BSc in Computers Systems Engineering (Bahaudin Zakariya University Pakistan) - 2006

Personal Summary

Omer Ali is a Postdoctoral Researcher currently working on the Zero Waste (ZeroW) and DIVINE projects at Walton Institute. His current research is to investigate the application of Machine Learning techniques to achieve real-time analytics from Agriculture and Food space data pipelines. In addition, Omer is interested in the integration of lightweight Machine Learning algorithms for modern IoT devices towards future digitally-enabled smart cities. Furthermore, some of his previous work revolved around the design of Wireless Sensor Network (WSN) based systems for remote sensing and early warning critical alerts. Omer also investigated the application of cross-layer techniques to improve the battery utilisation of WSN and IoT devices to enhance their overall device lifetime.

Publications

“Recent advances in dynamic modeling and control studies of biomass gasification for production of hydrogen rich syngas” – (RSC Advances) https://pubs.rsc.org/en/content/articlehtml/2023/ra/d3ra01219k

“On-line WSN SoC estimation using Gaussian Process Regression: An Adaptive Machine Learning approach” – (Alexandria Engineering Journal) https://www.sciencedirect.com/science/article/pii/S1110016822001636

“Battery characterisation for wireless sensor network applications to investigate the effect of load on surface temperatures” – (Royal Society Open Science) https://royalsocietypublishing.org/doi/full/10.1098/rsos.210870

“A Comprehensive Review of Internet of Things: Technology Stack, Middlewares, and Fog/Edge Computing Interface” – (MDPI Sensors) https://www.mdpi.com/1424-8220/22/3/995

“Energy Efficient Scheme for Wireless Sensor Networks based on CONTIKIMAC Protocol” – (JESTEC) https://jestec.taylors.edu.my/Vol%2016%20Issue%206%20December%20%202021/16_6_23.pdf

“A Machine Learning Approach for Early COVID-19 Symptoms Identification” – (Computers, Materials, & Continua) https://www.techscience.com/cmc/v70n2/44657

“Emerging IoT domains, current standings, and open research challenges: a review” – (PeerJ Computer Science) https://peerj.com/articles/cs-659/

“Early COVID-19 symptoms identification using hybrid unsupervised machine learning techniques” – (Computers, Materials, & Continua) https://www.techscience.com/cmc/v69n1/42777

“Adaptive clear channel assessment (A-CCA): energy efficient method to improve wireless sensor networks (WSNs) operations “- (AEU – International Journal of Electronics and Communications) https://www.sciencedirect.com/science/article/pii/S1434841120328077

“Internet of things security: Modelling smart industrial thermostat for threat vectors and common vulnerabilities” – (Springer – Intelligent Manufacturing and Mechatronics) https://link.springer.com/chapter/10.1007/978-981-16-0866-7_14

“Bringing intelligence to IoT edge: Machine learning based smart city image classification using Microsoft azure IoT and custom vision” – (IOP Science) https://iopscience.iop.org/article/10.1088/1742-6596/1529/4/042076

Conferences and Seminars

“Estimation of Battery State-of-Charge using Feedforward Neural Networks” – (ECTICON 2022 Thailand) https://ieeexplore.ieee.org/document/9795401

“Elliptic Curve Cryptography based Security on MQTT System for Smart Home Application” – (ECTICON 2022 Thailand) https://ieeexplore.ieee.org/document/9795478

“A MAC protocol for energy efficient wireless communication leveraging wake-up estimations on sender data” – (ECTICON 2020 Thailand) https://ieeexplore.ieee.org/document/9158110

“Analysis of OFDM Parameters using Cyclostationary Spectrum Sensing in Cognitive Radio” – (INMIC 2011 Pakistan) https://ieeexplore.ieee.org/abstract/document/6151492