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MUHAMMAD AWAIS

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    Biography

    He is a Biomedical and Electrical Engineer working in the domain of data mining, internet of things, 5G/6g Communication Technologies, Industry 4.0, data analytics, signal processing, application based machine 1learning and deep learning to develop ICT (Information and communication Technologies) based systems for remote sensing, digital health and industry 4.0. He received the B.S. electronic engineering degree from Mohammad Ali Jinnah University, Pakistan, M.S. degree in electrical and electronic engineering from Universiti Teknologi PETRONAS, Malaysia and PhD in Biomedical, Electrical and System Engineering from University of Bologna, Italy. He previously worked as research fellow in University of Hull, UK; University of Leeds, UK and University of Bologna, Italy. He is member of Institute of Electrical and Electronic Engineers (IEEE), the IEEE Engineering in Medicine and Biology Society (EMBS). 

    Education/Academic qualification

    PhD Biomedical Electrical and System Engineering, PhD, University of Bologna

    1 Nov 201431 Oct 2030

    Award Date: 4 May 2018

    Electrical and Electronic Engineering, MRes, Universiti Teknologi Petronas

    11 Dec 201119 Aug 2014

    Award Date: 19 Oct 2014

    Electronic and Telecommunication Engineering , BSc, Mohammad Ali Jinnah University, Karachi, Pakistan

    20 Aug 200619 Aug 2019

    Award Date: 1 Dec 2010

    Other positions

    Research Fellow in Data Analytics and Machine Learning, University of Hull

    1 Nov 201920 Jul 2020

    Research Fellow in Signal Processing and Machine Learning, University of Leeds

    30 Sep 201830 Oct 2019

    Research Associate in Digital Health and AI, University of Bologna

    1 Nov 201731 Aug 2018

    Visiting Research Fellow, Norwegian University of Science and Technology

    1 Sep 201530 Nov 2015

    Junior Lecturer, Mohammad Ali Jinnah University, Karachi, Pakistan

    1 Sep 201030 Nov 2011

    Keywords

    • T Technology
    • Applied Machine Learning
    • Digital and Smart Health
    • Internet of Things
    • 5G/6G Communication
    • Industry 4.0

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