2011 – 2014 Doctor of Philosophy (PhD) – Biomedical Engineering, Auckland University of Technology, Auckland, NZ.
2009 – 2010 Master of Engineering (ME) – Research (Hons) – Electrical and Electronics Engineering, Auckland University of Technology, Auckland, NZ.
2008 – 2009 Master of Engineering (ME St) – Studies (Hons) – Electrical and Electronics Engineering, Auckland University of Technology, Auckland, NZ.
2003 – 2007 Bachelor of Engineering (BE) (Hons) – Electrical and Electronics Engineering, JNTU University, India.
2017 SNOMED CT Foundation Course, SNOMED International
2015 Information Technology and Infrastructure Library® (ITIL®), ITIL, Auckland, NZ.
2012 Tertiary Teaching Certification, Auckland University of Technology, Auckland, NZ.
2007 Certified Automation Engineer, Prolific Systems and Technologies, India.
2007 Electrical, Computer Aided Design (ECAD), CADD Centre, India.
738015 Digital Signal Processing and its Applications
738027 Digital Signal Processing
737437 Biomedical Signal Processing
737438 Biomedical Instrumentation – I
705003 Engineering Computing
735313 Digital Device and Systems
DET 610 Electronic Communications
DET 600 Digital Systems
- IEEE – Engineering in Medicine and Biology Society (EMBS)
- HINZ – Health Informatics New Zealand
- IPENZ – The Institute of Professional Engineers New Zealand
Advisory Board Member
- International College of Auckland (ICA) – Engineering and Information Systems, Auckland, NZ
- Centre for Research and Innovation (CRI) – Industrial/ Applied research, Auckland, NZ
- Ntec Tertiary Group – Engineering Program, Auckland, NZ
- Medical Device and Sensors – National Group, NZ
- Health and Wellbeing Solutions – Centre for eHealth
Research, Innovation & Development
- Health IT system level measures; Quality matrix; Clinical decision support
- Remote patient monitoring (vital signs and bedside monitoring)
- Digital signal processing and its applications
- Medical Device Data and Big Data analysis
- Medical informatics and e-, m-Health
- Biomedical sensors/devices and decision support systems
- Fuzzy logic, machine learning and hybrid neural networks
- Wireless/wearable sensors and systems
- Smart patient monitoring and diagnosis systems
- Older adult healthcare and well-being