ITx 2018 Speakers

Keynotes and Speakers for ITx 2018

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Ayesha Hakim


Dr. Ayesha Hakim is an Academic Staff Member at the Centre for Business, Information Technology, and Enterprises, WINTEC. Dr. Hakim has a Ph.D. in Computer Science that she obtained from Massey University in 2014.

She has well-defined industry as well as teaching experience in New Zealand and overseas. Before joining WINTEC, she was working as Research IT Specialist at the University of Auckland. After completing her Ph.D, she worked as IT Support Specialist at Massey Genome Services in Massey University and as Assistant Professor in Pakistan.

Her research interests include Affective Computing, Machine Learning, and Human Computer Interaction. She has expertise in full stack web development using HTML5, CSS, JavaScript, Typescript, Angular, RESTful APIs, PHP (Laravel), MySQL with hands on experience on open source Content Management Systems.

She demonstrates excellent learning and teaching capabilities combined with strong dedication and motivation.

Predicting and Improving the Recognition of Emotions

Wednesday 12:20pm - 12:50pm, CITRENZ Conference (CITRENZ 2 Room)

The technological world is moving towards more effective and friendly human computer interaction. A key factor of these emerging requirements is the ability of future systems to recognise human emotions, since emotional information is an important part of human-human communication and is therefore expected to be essential in natural and intelligent human-computer interaction. Extensive research has been done on emotion recognition using facial expressions, but all of these methods rely mainly on the results of some classifier based on the apparent expressions. However, the results of classifier may be badly affected by the noise including occlusions, inappropriate lighting conditions, sudden movement of head and body, talking, and other possible problems. In this paper, we propose a system using exponential moving averages and Markov chain to improve the classifier results and somewhat predict the future emotions by taking into account the current as well as previous emotions.