Dr Md Zakir Hossain

PhD in Computer Science, RSCS, ANU.
Postdoctoral Fellow (Level A), RSCS, ANU.
ANU College of Business and Economics and ANU College of Engineering and Computer Science
T: +61 2 612 56188

Areas of expertise

  • Signal Processing 090609
  • Neurosciences 1109
  • Cognitive Sciences 1702
  • Computer Human Interaction 080602
  • Pattern Recognition And Data Mining 080109
  • Data Communications 100504

Research interests

  • Affective Computing
  • Machine Learning 
  • Human Physiology 
  • Signal Processing 
  • Medical Internet Research 
  • Human-Computer Interaction 

Biography

Md Zakir Hossain received the BSc degree in 2011 and the MSc degree in 2014 in Electrical and Electronic Engineering from Khulna University of Engineering & Technology (KUET) in Bangladesh. He served as a Lecturer in the University of Information Technology and Science, Bangladesh for six months in 2012. Later on, he joined as a Lecturer at KUET in 2012 and upgraded his position into Assistant Professor in 2014. He started PhD in the Research School of Computer Science (RSCS) at the Australian National University (ANU) in 2015 and was conferred the degree on 19 July 2019. He has been working as a tutor with ANU College of Engineering and Computer Science (CECS) and as a Research Assistant with RSCS and ANU College of Business and Economics. Currently, he is serving as a Postdoctoral Fellow (Level A) within the CECS and Our Health in Our Hands (OHIOH) project. 

Researcher's projects

  • Our Health in Our Hands: Big Data Program - http://www.anu.edu.au/research/research-initiatives/our-health-in-our-hands
  • Facial Expression Analysis
  • Investigating Differences between Two Visualisations (Circular and Organisational)
  • Differentiating between Real and Posed Smiles from Observers' Physiology 
  • CCA (Canonical Correlation Analysis) network for biomedical data analysis
  • Establishment of High Voltage Lab in KUET 

Available student projects

  • Innovative Machine Intelligence and Cybersecurity Solutions to Safeguard the Patient Information Associated with a New Generation of Medical Devices - https://cecs.anu.edu.au/research/student-research-projects/innovative-machine-intelligence-and-cybersecurity-solutions

Current student projects

  • Machine Learning for Cognitive Load Detection via E4 Empatica
  • Machine Learning to Classify Impact of Music Listening
  • Driving Simulator and Participants’ Physiology
  • Emotion Detection using 3D Computer Vision Model

Past student projects

  • Eye gaze for face recognition with lying psychology
  • Machine Learning for Classifying Angry Faces
  • Biofeedback Tools for Online Stress Detection
  • Machine Learning to Classify Smiling Faces
  • Study on Transformer Internal Faults Analysis
  • Transformer Internal Faults’ Detection using Neural Network
  • Localization of FACTS devices for optimal power flow

Publications

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Updated:  15 November 2019 / Responsible Officer:  Director (Research Services Division) / Page Contact:  Researchers