I am currently a postdoctoral researcher at CSIRO, Australia. In this role, I lead the analysis of multiple projects, including developing Bayesian machine learning algorithms for predicting antimicrobial resistance, data management and website support (front and back end) for the HOTspots surveillance and response program (advisor: Teresa M Wozniak), developing machine learning algorithms for predicting infectious diseases using social media data and climate, syndromic surveillance of respiratory diseases. Notably, I have contributed to the National Australian Climate Service (NCRA) project on projecting the impact of log-term climate variations on communicable diseases in Australia. 

My work has been recognised at national level with an acknowledgement letter from Hon. Josh Wilson (Assistant Minister for Climate Change and Energy) and an award from the CSIRO Envirnment Research Director for contributing to the NCRA project. I have also been recognised by CSIRO for contributing to innovative technology to combat the next pandemic and Translational Digital Technology for AMR.

Previous notable positions include postdoctoral researcher at the School of Mathematics and Physics and the School of Public Health of The University of Queensland.  My advisors are A/Prof Yoni Nazarathy and Dr Amalie Dyda. My  research projects included: Safe Blues, AI4PAN, and ID-NET. 

I have also worked as a postdoctoral research at the School of Mathematical Sciences of Queensland University Technology and associate lecturer at the Maldives  National University. My advisors at QUT were Distinguished Prof Kerrie Mengersen and Prof Chris Drovandi.

I received my PhD in 2015 from The University of Queensland, in the area of probability & statistics, focused on epidemic modelling. My advisors being Prof Phil Pollett and Dr Ross McVinish. My current research focuses on epidemic modelling, digital health, disease outbreak prediction, and natural language processing. I have also worked on Bayesian inference of disease dynamics, and applied data science. 

My expertise is in epidemic modelling, applied probability, Bayesian statistics, data science, natural language processing and mathematical education.

Application areas of my work include modelling the spread of epidemics on a human network for limiting the  diseases through altered migration patterns, Bayesian modelling of within-host dengue dynamics, simulation of virtual epidemics using Artificial Intelligence,  modelling the spread of monkeypox, machine learning approach to modelling vaccine behaviour from social media, application of unsupervised learning to uncover trends in text data, Spatiotemporal Bayesian machine learning modelling of antimicrobial resistance,  Temporal machine learning modelling of climate and communicable diseases, and statistical modelling of respiratory diseases for syndromic surveillance, and educational game development.

I am currently enrolled in Graduate Certificate in Information Technology at the Queensland University of Technology.

Courses and  Workshops

I have been engaged with teaching courses  at The University of Queensland since 2010 . See full course list. The main areas of my teaching at UQ are:

• Data Science and Statistical Methods, and Practice: - this set of courses provide the fundamental techniques of data science, machine learning, statistical modelling and computation. Topics include linear models, generalised linear models, regularisation, Bayesian technique and process simulation, design thinking. Computational tools include Python, R, SQL, Hive, and Tableau.

• Mathematics for Data Science: - this course concern the mathematical background required for understanding data science, statistics, and machine learning algorithms. Topics include calculus, linear algebra, discrete mathematics, and probability. Mathematica is used for programming.

• Mathematics for Statistics: - this collection of courses deal the mathematical background required for understanding statistical inference, probability, and data analysis. Topics covered include, likelihood theory, confidence intervals, hypothesis tests, Bayesian inference, multivariate normal distribution, and general linear model inference. The programming language MATLAB is used for computation.

• Probability and Stochastic Process: - this suite of courses deal with the theory of probability and stochastic processes, the application of stochastic processes for modelling real world phenomena, and simulation methods. The programming language MATLAB is used for computation.

• Statistics for Health Science: - this set of courses deal with key research principles and approaches, designs and processes in health science as well as statistical modelling. Topics include qualitative and quantitative methods of data collection and analysis, linear models and generalised linear models. Computational tools include SPSS and R.

• Introduction to Statistics - this collection of courses concern with introductory statistics for data scientists, engineers, and the general sciences. The programming language R is used for computation.

• Introduction to Mathematics: - this suite of courses deal with the introductory mathematics for mathematicians, and the general science.

I have initiated and co-created the BRAG-Stan Workshop at Queensland University of Technology in 2019.

Selected Talks, Prizes, Awards, and Recognitions

• Acknowledgement letter from Hon Josh Wilson (Assistant Minister for Climate Change and Energy) and an award from CSIRO Environment Research Director for contributing to the National Climate Risk Assessment, 2025

• Mentioned by CSIRO Health & Biosecurity Research Director in weekly updates for contributing to innovative technologies for preventing next pandemic, 2025

• Digital Transformation award for contributing to advancing digital health solutions for antimicrobial resistance, 2024

• Mentioned in the Australian Society for Antimicrobials newsletter for an enlightened talk given at the Antimicrobials 2024 conference, 2024

• Safe Blues: Emulation of epidemics via virtual safe virus-like tokens. UQ-AI Workshop Day, 2021, Brisbane, Australia. [second prize, poster]

• Invited talk at QUT-ACEMS  Node Planning Day in 2019 . See slides of the talk

• Contributed talk at Bayes on the Beach Conference in 2019, showcasing the application of Bayesian statistical inference  in minimising  dengue severity within humans hosts using Stan probabilistic programming language. See slides of the talk

• ANZIAM prize for an outstanding talk presented at QANZIAM Conference in 2012.  See slides of the talk

• UQ-SMP prize for the best Mathematics poster presented at SMP poster day in 2011. Topic of the poster:  The Spread of an SIS epidemic in a network

Scholarships

• Young Statisticians Scholar travel scholarship for YSC-2019 conference. Statistics Society for Australia, 2029

• Australian Research Council for Center of Excellence for Mathematics and Statistics (ACEMS) PhD top-up scholarship, 2014-2015

• University of Queensland International Scholarship to pursue a PhD, 2010-2014

• University of Queensland Research Scholarship to pursue a PhD, 2010-2013

• MASCOS top-up scholarship to pursue a PhD, 2010-2013

• Maldives Government Higher Education Scholarship to pursue a MSc

• Brunei Government International Student Scholarship to pursue BSc 

Computer Language Skills

• Julia

• R

• Python

• Stan

• Matlab

• Mathematica

• Maple

• Java

• HTML

Licence and Accreditations

• Data Science Professional Certification, IBM, 2020. [certificate]

•  Machine Learning A-Z: hands on R and Python, Udemy, 2018. [certificate]

•  Big Data Analytics,  QUT, 2016. [certificate]

Family and Community Service 

My daughter, Iva,  husband, Ahmed, and myself do organise quite a bit of Maldivian community gatherings in Brisbane.