Dr Zakir Hossain

Research Fellow (CSIRO)

Dr Md Zakir Hossain’s current research focuses on developing biologically informed machine learning models through data integration and biological understanding for advancing analytical frontiers in areas with direct applications to animal and plant breeding. His research direction also leads to develop advance technologies for diagnosing and managing various human diseases including covid-19, multiple sclerosis, and diabetes. He is also interested in developing AI models for emotion recognition and affective computing.

Prior to joining the Biological Data Science Institute (BDSI) at ANU and Machine Learning & Artificial Intelligence Future Science Platforms (MLAI FSP) at CSIRO in January 2021, he served as a postdoctoral research fellow in Centre for Health Informatics (CHI) at Macquarie University, Sydney. During that time, he helped in developing AI models for diagnosing COVID-19 securely from acoustics signals. From November 2018 to November 2020, he served as a postdoctoral / research fellow and lecturer at OHIOH (Our Health in Our Hands) Grand Challenge and Research School of Computer Science (RSCS), ANU. During this fellowship, he focused on building predictive models for people living with multiple sclerosis and/or diabetes. Zakir earned his PhD in computer science in July 2019 from ANU, with his research focused on developing machine learning models for human computing and cognitive science.

Zakir has taught over 20 university courses in different universities since started in January 2012, including the University of Information Technology & Sciences (UITS) and Khulna University of Engineering & Technology (KUET) in Bangladesh, University of Canberra and ANU. He is an Associate Fellow of Higher Education Academy (AFHEA), awarded by the UK Advanced Higher Education Academy.

More about Zakir can be found here

Research activities at CSIRO can be found here. 

Research interests

Research interests

  • Bioinformatics 
  • Computer Vision 
  • Machine Learning 
  • Human-Centred Computing 
  • Biological Computing 

Google Scholar

Available Student Projects

Research Activities and Scholarships

  • Qin, Z, Gedeon, T, Chen, L et al. 2018, 'Artificial Neural Networks Can Distinguish Genuine and Acted Anger by Synthesizing Pupillary Dilation Signals from Different Participants', 25th International Conference on Neural Information Processing, ICONIP 2018, ed. Cheng L., Leung A., Ozawa S., Springer, Cham, pp. 299-310.
  • HOSSAIN, M & Gedeon, T 2018, 'An Independent Approach to Training Classifiers on Physiological Data: An Example Using Smiles', 25th International Conference on Neural Information Processing, ICONIP 2018, ed. Cheng L., Leung A., Ozawa S., Springer, Cham, pp. 603-613.
  • HOSSAIN, M, Gedeon, T & Sankaranarayana, R 2018, 'Using temporal features of observers' physiological measures to distinguish between genuine and fake smiles [IN PRESS]', IEEE Transactions on Affective Computing, vol. online.
  • HOSSAIN, M, Gedeon, T & Islam, A 2018, 'Understanding two graphical visualizations from observer's pupillary responses and neural network', 30th Australian Conference on Computer-Human Interaction, OzCHI 2018, ed. A Morrison, G Buchanan, J Waycott et al, Association for Computing Machinery (ACM), New York, USA, pp. 215-218pp.
  • Hossain, M & Gedeon, T 2018, 'Observers' physiological measures in response to videos can be used to detect genuine smiles', International Journal of Human-Computer Studies, vol. 122, pp. 232-241.
  • Hossain, M, Gedeon, T, Caldwell, S et al 2018, 'Investigating differences in two visualisations from observer's fixations and saccades', 2018 Australasian Computer Science Week Multiconference, ACSW 2018, ACM, New York, NY, USA, pp. 1-4.
  • Zhu, X, Qin, Z, Gedeon, T et al 2018, 'Detecting the Doubt Effect and Subjective Beliefs Using Neural Networks and Observers' Pupillary Responses', 25th International Conference on Neural Information Processing, ICONIP 2018, ed. Cheng L., Leung A., Ozawa S., Springer, Cham, pp. 610-621.
  • HOSSAIN, M & Gedeon, T 2017, 'Discriminating real and posed smiles: Human and avatar smiles', 29th Australian Computer-Human Interaction Conference, OzCHI 2017, ed. Brereton M.Vyas D.So, ACM, New York, pp. 581-586.
  • HOSSAIN, M & Gedeon, T 2017, 'Classifying posed and real smiles from observers' peripheral physiology', 11th EAI International Conference on Pervasive Computing Technologies for Healthcare, PervasiveHealth 2017, ed. N Oliver and M Czerwinski, Association for Computing Machinery (ACM), New York, pp. 460-463pp.
  • Chen, L, Gedeon, T, Hossain, M et al 2017, 'Are you really angry? detecting emotion veracity as a proposed tool for interaction', 29th Australian Computer-Human Interaction Conference, OzCHI 2017, ed. Brereton M.Vyas D.So, ACM, New York, pp. 412-416pp.
  • Hossain, M & Gedeon, T 2017, 'Effect of Parameter Tuning at Distinguishing Between Real and Posed Smiles from Observers' Physiological Features', 24th International Conference on Neural Information Processing, ICONIP 2017, ed. Liu D., Xie S., Li Y., Zhao D., El-Alfy ES., Springer, TBC, pp. 839-850.
  • HOSSAIN, M, Gedeon, T, Sankaranarayana, R et al. 2016, 'Pupillary Responses of Asian Observers in Discriminating Real from Fake Smiles: A Preliminary Study', Measuring Behaviour 10th International Conference on Methods and Techniques in Behavioural Research, ed. A. Spink, G. Riedel, L. Zhou, L. Teekens, R. Albatal, C. Gurrin, Dublin City University, Dublin Ireland, pp. 170 - 176pp.
  • HOSSAIN, M, Gedeon, T & Sankaranarayana, R 2016, 'Observer's Galvanic Skin Response for Discriminating Real from Fake Smiles', Australasian Conference on Information Systems (ACIS 2016), Australasian Conference on Information Systems, Darlinghurst, pp. 8pp.
  • HOSSAIN, M, Kabir, M & Shahjahan, M 2016, 'A robust feature selection system with Colin's CCA network', Neurocomputing, vol. 173, no. 3, pp. 855-863.
  • Uddin, M, HOSSAIN, M, Ahmad, M et al. 2014, 'Effects of Caffeinated Beverage Consumption on Electrocardiographic Parameters among Healthy Adults', Modern Applied Science, vol. 8, no. 2, pp. 1913-1852.
  • HOSSAIN, M, Kabir, M & Shahjahan, M 2014, 'Feature selection of EEG data with neuro-statistical method', International Conference on Electrical Information and Communication Technology (EICT), IEEE, online, pp. 1-6.
  • Rahman, A, Alam, M, HOSSAIN, M et al. 2014, 'Localization of FACTS devices for optimal power flow using Genetic Algorithm', International Conference on Electrical Information and Communication Technology (EICT), IEEE, online, pp. 1-6.
  • Enamul Kabir, A, HOSSAIN, M, Rashid, M et al. 2014, 'Extraction of Inherent Frequency Components of Multiway EEG Data Using Two-Stage Neural Canonical Correlation Analysis', Modern Applied Science, vol. 8, no. 1, pp. 164-175.
  • Kabir, A, Hasan, H, Rashid, M et al. 2013, 'Resemblance of Rain Fall in Bangladesh with Correlation Dimension and Neural Network Learning', American Journal of Applied Sciences, vol. 10, no. 10, pp. 1172-1180.
  • Saleh, A, HOSSAIN, M, Rabin, M et al. 2013, 'A learning system for detecting transformer internal faults', 2013 International Conference on Informatics, Electronics and Vision (ICIEV) , IEEE, online, pp. 1-6.
  • HOSSAIN, M, Rabin, M, Uddin, A et al. 2013, 'Canonical correlation analysis with neural network for inter subject variability realization of EEG data', 2013 International Conference on Informatics, Electronics and Vision (ICIEV) , IEEE, online, pp. 1-5.