Dr Reza Shahamiri

BSc and MSc (Software Engineering), PhD (Computer Science)

Biography

Reza is an experienced deep learning software engineer with a vision to eliminate health inequalities using the advancements of computing and artificial intelligence technologies. His research is mainly on smart assistive technologies in which he builds intelligent software platforms and solutions to enable better support for those who suffer from mental or physical limitations and augment health care professionals with more sophisticated tools and equipment. He holds BE and ME qualifications in Software Engineering and a Ph.D. in Computer Science. He is currently a tenured Senior Lecturer in Software Engineering with the Department of Electrical, Computer, and Software Engineering, Faculty of Engineering, The University of Auckland, New Zealand. His research interest deals with developing novel, intelligent health care systems using deep learning technologies, speech and speaker identification, and software test oracle automation.

Research | Current

One of the aspects of his research deals with the applications of deep learning to further enable better health care systems. In this respect he has been involved in engineering deep learning software solutions to enable speech recognition technologies for the speech disorders, enabling autism screening using deep neural networks, etc. He has also been involved in creating a novel end-to-end deep learning technology for speaker identification. He utilizes different technologies and concepts such as supervised and unsupervised learning, transfer learning, ensemble learning, data augmentation, etc. to develop practical solutions that can be used in real life scenarios. In summary, his current research interests are:

  • Test Oracles
  • Development of novel, intelligent health care systems using deep learning technologies, such as:
    • Autism screening and AI based detection of ASD
    • Impaired Speech Recognition
    • Voice disorders therapy systems
  • Speaker Identification

Teaching | Current

COMPSYS 302: Design: Software Practice

SOFTENG 306: Software Engineering Design 2

SOFTENG 761: Advanced Agile and Lean Software Development

Postgraduate supervision

PhD:

  • Mengke (Claire) Shi, Universitty of Auckland, Thesis Title: Automatic Speech Technologies for Neurodegenerative Disease Diagnosis via Speech with Accents (Main Supervisor)
  • Hechen (Sunny) Wang, Universitty of Auckland, Thesis Title: Automatic Classification of Online User Feedback for SoftwareRequirements from Software Forums, Twitter and App StoreReviews (Co-Supervisor) 
  • Junbo Ma, Massey University, Thesis Title: Machine Learning and Audio Processing, Completed 2019 (Co-Supervisor)

Masters:

  • Siti Noor Hasanah Binti Ghazali. University of Malaya (Co-supervisor). Topic: Test Cases Prioritization using Risk-Based Testing Approach for Agile Methodology (2014-2016)
  • Muhammad Elrashid Yousif. University of Malaya (Co-supervisor). Topic: Automated Software Test Oracles using Support Vector Machines. Status: ongoing
  • Sepehr Kazemi, University of Malaya (Co-supervisor). Topic: Graph-based software testing (2014-2016)
  • Indiran Rajagopal, University of Malaya (Co-supervisor). Topic: On The Use Of Artificial Neural Networks Towards Speaker Recognition (2014-2016)

Distinctions/Honours

  • Winner of 2016 Manukau Institute of Technology Outstanding Achievement Award for excellence in teaching, research and programme development

Areas of expertise

  • Deep Learning and Neural Networks
  • Software Testing and Quality Assurance
  • Speech and Speaker Recognition

Committees/Professional groups/Services

  • Editorial Board, PLOS ONE, 2019 –current
  • Editorial Board, American Journal of Neural Networks and Applications, 2016 – 2017
  • Editorial Board, International Journal of Software Engineering 2019 - Current
  • Manukau Institute of Technology’s Research Committee, Member, 2019-2021
  • Faculty of Business and Information Technology Research Committee, Member, Manukau Institute of Technology, 2017
  • ICT Industry Advisory Board, Member, Manukau Institute of Technology, 2016-2019
  • School of Digital Technologies, Manukau Institute of Technology, Programme Committee, Member (2015-2019)
  • Member, IEEE (2013-2015)
  • Member, New Zealand Software Association (2015)
  • Committee Member, Malaysian Journal of Computer Science (2013-2015)
  • Committee Member, GlobalCIS’s International Conferences, 2016
  • Independent Scientific Expert, The Ministry of Education, Universities and Research, Italy
  • Technical Committee, 12th International Conference on Signal Processing Systems (ICSPS 2020)
  • Technical Committee, 2018 4th International Conference on Knowledge Engineering (ICKE 2018), Osaka, Japan
  • Technical Committee, 10th International Conference on Signal Processing Systems (ICSPS 2018)
  • Technical Committee, 9th International Conference on Signal Processing Systems (ICSPS 2017)
  • Programme Committee, 2018 second International Conference on Advances in Electronics, Computers and Communications (ICAECC 2018)
  • Programme Committee, 4th International Symposium on Big Data and Cloud Computing Challenges (ISBCC-2017)
  • Programme Committee, 2nd International Symposium on Big Data and Cloud Computing Challenges ISBCC (2015)
  • Programme Committee, 2014 International Conference On Advances in Electronics, Computers and Communications ICAECC-14
  • Programme Committee, 3rd International Symposium on Big Data and Cloud Computing Challenges, ISBCC (2016)
  • Member of Speech to Speech Group at Faculty of Computer Science and Information Technology, University of Malaya (Dec 2016 – Dec 2018)

Selected publications and creative works (Research Outputs)

As of 29 October 2020 there will be no automatic updating of 'selected publications and creative works' from Research Outputs. Please continue to keep your Research Outputs profile up to date.
  • Thabtah, F., Kamalov, F., Hammoud, S., & Shahamiri, S. R. (2020). Least Loss: A simplified filter method for feature selection. INFORMATION SCIENCES, 534, 1-15. 10.1016/j.ins.2020.05.017
  • Shahamiri, S. R., & Thabtah, F. (2020). An investigation towards speaker identification using a single-sound-frame. MULTIMEDIA TOOLS AND APPLICATIONS, 79 (41-42), 31265-31281. 10.1007/s11042-020-09580-4
  • Shahamiri, S. R., & Thabtah, F. (2020). Autism AI: a New Autism Screening System Based on Artificial Intelligence. COGNITIVE COMPUTATION, 12 (4), 766-777. 10.1007/s12559-020-09743-3
  • Tirumala, S. S., Shahamiri, S. R., Garhwal, A. S., & Wang, R. (2017). Speaker identification features extraction methods: A systematic review. Expert Systems with Applications, 90, 250-271. 10.1016/j.eswa.2017.08.015
  • Champiri, Z. D., Shahamiri, S. R., & Salim, S. S. B. (2015). A systematic review of scholar context-aware recommender systems. Expert Systems with Applications, 42 (3), 1743-1758. 10.1016/j.eswa.2014.09.017
  • Shahamiri, S. R., & Salim, S. S. B. (2014). A multi-views multi-learners approach towards dysarthric speech recognition using multi-nets artificial neural networks. IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society, 22 (5), 1053-1063. 10.1109/tnsre.2014.2309336
  • Shahamiri, S. R., & Binti Salim, S. S. (2014). Real-time frequency-based noise-robust Automatic Speech Recognition using Multi-Nets Artificial Neural Networks: A multi-views multi-learners approach. Neurocomputing, 129, 199-207. 10.1016/j.neucom.2013.09.040
  • Shahamiri, S. R., & Binti Salim, S. S. (2014). Artificial neural networks as speech recognisers for dysarthric speech: Identifying the best-performing set of MFCC parameters and studying a speaker-independent approach. Advanced Engineering Informatics, 28 (1), 102-110. 10.1016/j.aei.2014.01.001

Contact details

Alternative contact

Phone: +649 923 2431

Primary office location

ENGINEERING BLOCK 5 - Bldg 405
Level 6, Room 669
5 GRAFTON RD
AUCKLAND CENTRAL
AUCKLAND 1010
New Zealand

Social links

Web links