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Dr Henner Kampwerth

Faculty: Engineering
Field of Research (FoR):
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Dr Henner Kampwerth is a Australian Renewable Energy Agency
Dr Aron Woldeghiorgis Michael

Faculty: Engineering
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Dr Aron Michael is Lecturer (Microsystems) with the School of Electrical Engineering and Telecommunications.  He has published more than 70 technical papers including books and book chapt
Dr Md Forhad Zaman

Faculty: UNSW Canberra at ADFA
Field of Research (FoR):

Forhad is a Research Associate with the School of Engineering and Information Technology, University of New South Wales (UNSW), Canberra. He received his Ph.D.
Dr Georgios Konstantinou

Faculty: Engineering
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I am a Lecturer in Energy Systems with the School of Electical Engineering and Telecommunications, UNSW Australia and coordinate the research work at the Real-Time Digital Simulation (RTS) laborato
Dr Beena Ahmed

Faculty: Engineering
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Dr. Beena Ahmed is a Senior Lecturer in Signal Processing with the School of Electrical Engineering and Telecommunications. She received her B.Sc.
Dr Sergey Varlamov

Faculty: Engineering
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Dr Sergey Varlamov is a Senior Research Fellow and the Deputy Director ARC Photovoltaics Centre of Excellence in the School of Photovoltaic and Renewable Energy Engineering.
Dr Rukmi Dutta

Faculty: Engineering
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Dr Rukmi Dutta is a senior lecturer in Energy System with the School of Electrical Engineering and Telecommunications. Her research interests include:
Dr Tuomo Ilmari Tanttu

Faculty: Engineering
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Dr Tuomo Tanttu is a post doc researcher at Andrew Dzurak's group. He received his PhD in 2016 at Aalto University in QCDLabs.
Associate Professor Torsten Lehmann

Faculty: Engineering
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Dr Torsten Lehmann is Associate Professor in Microelectronics with the School of Electrical Engineering and Telecommunications. His research interests include:
Estimating risk of falling in the elderly by monitoring daily activities

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This project aims to develop signal processing algorithms to extract features from inertial signals which correlate with current clinical measures of fall risk. The signals are acquired during normal unsupervised movement using a small waist-worn monitor.