Muhammad Asif Naeem
Muhammad Asif Naeem is a founder and director of the Data Science Research Group. He is a Senior Lecturer in School of Engineering, Computer and Mathematical Sciences, Auckland University of Technology. He received his PhD degree in Computer Science from The University of Auckland and have been awarded a best PhD thesis of the year. Before that he received his Master’s degree with distinction. He has about twelve years research, industrial and teaching experience. As an outcome of my research, he published one book and more than 30 peer reviewed journals, conferences and workshops papers including in IEEE, ACM, and Springer. He received best Faculty Teaching Award of 2015 at AUT. He is organising an IEEE workshop IWDM since 2013. His research areas include Big Data Management, Data Stream Processing, Stream Mining and Analytics, and Real-time Data Warehousing.
Home page: https://iwdm.aut.ac.nz/asif/
Russel Pears is interested in all aspects of Data Mining and Machine Learning. His research speciality is in Data Stream Mining where he has contributed novel methods for change detection and recurrent pattern capture. He is currently involved in a number of research projects in Data Stream mining, both in the theoretical aspects as well as solving problems for Industry/Research partners. One such project is finding patterns in electrical power systems that lead to spikes in frequency generation. Another project involves predicting the level of aftershock activity after the occurrence of a major earthquake.
Russel has published over 80 research articles in major conferences and journals and regularly reviews for major Journals in Data Mining/Machine Learning areas and sits on programme committees for major conferences.
Home page: https://www.aut.ac.nz/profiles/russel-pears
Dave Parry is an Associate Professor, Head of the department of computer science, academic leader for the master of health informatics programme and director of the AUT Radio frequency Identification (RFID) laboratory in the AUT School of Engineering, Computer and Mathematical Sciences. Dave is a member of the board of Health Informatics New Zealand and the RFID Pathfinder Group. Dave’s research interests include health informatics and ehealth along with pervasive computing and RFID. Most of Dave’s work is related to the use of computing devices and sensors in order to identify human activity automatically and link this to knowledge sources. Specific completed RFID projects include analysis of anaesthetist’s activity in operating theatres and the use of RFID bracelets to support community exercise programmes. Current projects include identification of knowledge sources in healthcare, drug administration tracking with ADHB, usability evaluation of mobile devices in healthcare, healthcare and the internet of things and fuzzy ontology approaches to the analysis of activity and clinical data.
Home page: https://www.aut.ac.nz/profiles/dave-parry
Boris' research interest is in application of Computational Intelligence (CI) and data analytics to advance sport science, rehabilitation, health and active life systems and technologies.
Boris’ research is focused on multi-disciplinary aspects of computational intelligence, data science and kinesiology for producing augmented coaching systems (ACS) to aid end-users to improve their motion control, skills, and technique. Furthermore, multi-disciplinary approaches in on- and off-line Human Motion Modelling and Analysis (HMMA) are developed independently to be compatible with recent and future technologies. The near future and next generation of ACS cover: computer vision, distributed computing, ubiquitous, wearable and functional rehabilitation devices; exergames; and virtual/immersive environments. The distinctive aspect of Boris' HMMA and ACS research is in enabling assessment/feedback automation that is based on similarity to expert insights and can be produced from data or generated models. In addition to applicability to various sport disciplines and rehabilitation systems, the developed artefacts from ACS and HMMA will also be transferable to future intelligent prosthetics, brain-machine interfaces, functional rehabilitation devices and exoskeleton control function.
Related areas of Boris’ interest also include: Video, image and signal processing, Computer Vision (CV), ubiquitous and wearable computing, data mining, machine learning, software engineering, human computer interaction, open source software integration, networking/data communication, embedded systems and multi-platform processing.
Home page: https://www.aut.ac.nz/profiles/boris-bacic
Parma Nand is a Senior Lecturer and researcher in the Department of Computer Science. He has a PhD in Artificial Intelligence in the area of Natural Language Processing and has several years of commercial software development experience. His main area of activity is text mining, however he has expertise in integrating text mining and structured data mining to achieve commercial and strategic objectives. Some of the previous completed projects are location mining from tweets, bullying detection and topic tracking in Tweet messages. Some of the current application projects underway are information extraction from annual reports for Matauranga Maori enhancement, information extraction from online sources for wine styles and TV serial/movie revenue prediction from pre-production information. Parma is also working on the linguistic and computational theories behind these text mining applications.
Google Scholar: https://scholar.google.com/citations?user=e4a55MEAAAAJ
Sarah Marshall is a Lecturer in the Department of Mathematical Sciences. She completed her PhD in Management Science on the application of deterministic and stochastic models to product recovery systems at the University of Edinburgh in 2012. Sarah worked in the Department of Management Science at the University of Strathclyde in Glasgow for three years before beginning her current position at AUT in 2014. She is a member of the Operations Research Society of New Zealand council and co-chair of the 2016 Joint NZSA/ORSNZ Conference. Sarah’s area of expertise is stochastic models and their application. She is currently involved in projects relating to warranty costs, product recovery and remanufacturing.
Farhaan is a lecturer in Department of IT and Software Engineering. Farhaan achieved his PhD in Information Systems from University of Auckland. He also holds BEng and MEng in Software with Honors from Massey University. Farhaan has a strong commercial R&D portfolio; he has been part of grants and fundings that total $2.3 million involving research projects in NZ, Australia and USA. He also served in strategic roles for technology companies in Auckland. Farhaan authored journal and conference papers on m-health and technology standards. Farhaan’s recent research projects involve contributing toward topical issues such as Ultra-Fast Broadband implementation in NZ, GPS assisted travel surveys in NZ, Real-time patient feedback in NZ health and disability sector, and conversion of paper-based manuscripts to interactive mobile apps.
Home page: https://www.aut.ac.nz/profiles/farhaan-mirza
Gerald Weber is Senior Lecturer in the Department of Computer Science at The University of Auckland. He joined The University of Auckland in 2003. Gerald holds a PhD from the FU Berlin.
He is information director of the Proceedings of the VLDB Endowment, and he has been program chair of several conferences. He is co-author of the book “Form-Oriented Analysis”, and of over 40 peer-reviewed publications. His research interests include Databases and Data Models, Human-Computer Interaction and Theory of Computation.
Home page: https://www.cs.auckland.ac.nz/people/g-weber
Imran Sarwar Bajwa
Imran Sarwar Bajwa is an Assistant Professor of Computer Science at The Islamia University of Bahawalpur, Pakistan. He has worked on various research projects in University of Birmingham, UK (2009-2012) and University of Coimbra, Portugal (2006-2007). His research interests are Natural Language Processing, Automated Software Modelling, Enterprise Computing, and Image Processing.
Home page: http://iub-pk.academia.edu/ImranSarwarBajwa
Dr Mahsa Mohaghegh
Dr Mahsa Mohaghegh is a computer engineer with a background in artificial intelligence and natural language processing. She obtained her PhD from Massey University with a thesis in Statistical Machine Translation.
Prior to joining AUT, Mahsa was a Senior Lecturer and Program Leader at Unitec, and also lead an outreach effort within the Department of Computing there. After being awarded Google’s Anita Borg Memorial Scholarship in 2012, Mahsa became involved with Google’s Computer Science for High Schools initiative, and successfully applied for Google funding to run these workshops in Auckland for the last 3 years.
Mahsa is also the founder and director of the women’s technology group She# - shesharp.co.nz, a platform aimed at promoting STEM to the next generation, and creating networking opportunities for tertiary students and industry professionals in the digital sector. Her passion for promoting careers in technology to young women has been recognised by a number of organisations, and resulted in her being awarded at the Westpac Women of Influence Awards.
Dr Nuttanan Wichitaksorn
Nate’s current specialization is Econometrics and Statistics with emphasis on Bayesian approach and applications in economics, finance, health science, and social science. His research interests also lie in the fields of computational statistics using Monte Carlo methods, financial analytics, skew distributions, copula modeling, robust quantile regression, and GPU-based parallel computation.
Before joining AUT, Nate has been a research fellow at Thailand Development Research Institute and was a Lecturer in Statistics at University of Canterbury, New Zealand where he is now an Adjunct Fellow. Prior to that, he obtained a PhD in Econometrics from University of Sydney, Australia, and two MAs in Economics from Rutgers University, USA, and Chulalongkorn University, Thailand.