Dr Mojtaba Lotfaliany specialises in the field of biostatistics. His career began as a medical student, working as a volunteer research assistant. He decided to follow this passion by starting a PhD at the University of Melbourne, focussing on how we can predict different diseases in the future.
Tell us about your passion for this research
I guess my passion for statistics comes from my will to make sense of the world. For me, mathematics is closely linked with ontology and epistemology. Statistics is where the world of math – absolute logic – meets the “real world,” where there is always an element of change, uncertainty, and indefinability.
Currently, I am working as a biostatistician/methodologist at IMPACT, providing statistical support to a wide range of students and staff in different aspects of their research on a daily basis. I’m also pursuing my own research, focussing on how novel artificial intelligence methods can help us predict different diseases, especially cardiovascular and mental disorders.
I guess my desire to understand the world and myself is the main driver for choosing a career in academia.
Working as a statistician allows me to delve into a scientific knowledge creation process, dealing with concepts such as interpretation, interference, uncertainty, possibilities, and contingencies. It is interesting for me to see how we can derive ‘universal’ rules from ‘particular’ observations. It becomes even more fun when we can use machine learning techniques to teach machines to do this process themselves.
How do you think about the impact of the research you’re conducting?
I think the main impact is improving the quality of research conducted at IMPACT, through helping others to optimise their methodologies and enabling them to conduct their research faster and better.
Moreover, by learning new techniques in statistics, I enable IMPACT researchers to use novel methods in their research and ask questions that were not possible before.
For example, by using novel artificial intelligence, we developed models that can predict depression in older adults with high precision, an achievement with high impacts in prevention of depression in aged populations. We have also been running emulations for randomised clinical trials using observational studies, enabling us to study the effect of different medications on preventing cancer.
In what ways are you building knowledge with other researchers?
I am so lucky that my job demands collaboration with a wide range of researchers from different disciplines. It gives me a unique opportunity to enjoy knowing new people, working with different groups, being exposed to different working cultures, and seeing the world through different perspectives.
My collaborations range from one-on-one consultations to collaborating within large international consortiums. Similarly, my role in each collaboration is different.
Sometimes I lead, sometimes I need to help students find their way, and sometimes I just need to be an empathic friend who listens and provides words of encouragement.
What were some of your 2024 highlights?
2024 was a productive year for me. I led or contributed to 17 publications and several conference proceedings. Moreover, I collaborated in seven different funding acquisition applications, one of which was successful: A 2023 MRFF Childhood Mental Health Research Grant.
Beyond that, two PhD students who I supervised completed and submitted their theses. I am also happy to say that one of my previous PhD students got the Alfred Deakin Postdoctoral Fellowship.
I should also acknowledge here the connections that were created, the moments of laughter enjoyed, and the profound friendships made as the most important highlights of 2024.
What is next?
For me, the answer is simple: repetition with difference. Answering each research question creates new knowledge, but at the same time, creates new research questions similar to the original one but not identical to it. That is why it is called “re-search”. So, in each iteration, I contribute to the evolution of human knowledge and thought.
