Hello and welcome!!
I am working as a Research Fellow within the Biological Data Science Institute (BDSI) at ANU and Machine Learning & Artificial Intelligence Future Science Platforms (MLAI FSP) at CSIRO, Canberra. Prior to joining here, I served as a Postdoctoral Research Fellow in the Australian Institute of Health Innovation (AIHI) at Macquarie University, Sydney. During that time, I helped in developing AI models for diagnosing COVID-19 securely from acoustics signals. From November 2018 to November 2020, I served as a Postdoctoral / Research Fellow and Lecturer at Our Health in Our Hands (OHIOH) project and the Research School of Computer Science (RSCS), ANU. During this fellowship, I focused on building predictive models for people living with multiple sclerosis and/or diabetes. My research area includes Machine Learning, Human-Centred Computing, Computer Vision, Biological Computing, and Bioinformatics.
In my PhD, I have proposed a new machine learning approach to distinguish between real and posed smiles from participants' emotional reactions to the two kinds of smiles. The emotional reactions are extracted from participants' physiological signals and classified using different machine learning classifiers. The participants' demographics data are also recorded and evaluated. The proposed idea has been implemented, and it has potential applications in affective computing, health informatics, human computiong, and so on.
I had also been working as a Human Centred Computing Support Officer at CECS, ANU. I conduct data mining and machine learning based research for distinguishing between two visualisations (organisational and circular). In this case, I used participants' pupillary responses and demographic data. It has potential application in affective computing and visualisations.
I was also working as a Research Assistant at the ANU College of Business and Economics. My role is to apply machine learning techniques for text mining and facial expression analysis in this case.
I obtained MSc and BSc degrees from the Department of Electrical and Electronic Engineering (EEE) at Khulna University of Engineering & Technology (KUET), Bangladesh. I appiled a novel and robust optimisation technique to select informative features from EEG signals and micro-array data during my MSc research. The technique is adopted based on two strategies, namely 'training with noisy features' and 'maximum correlation and minimum redundancies', called CCA Network. It has potential applications in health informatics, statistical machine learning, and data mining.
I have more than two and half years teaching experiences in two universities (Khulna University of Engineering & Technology and University of Information Technology and Sciences) at Bangladesh. I taught Power Systems, Electronics, Electrical, and Comunication engineering related courses.
I was also tutoring at CECS, ANU. Here, I invest my time for designing assignment, lab demostration, and conducting tutorials.
Moreover, I have been awarded several scholarships and awards for showing excellence in several areas.