Marliana Tri Widyastuti
Marliana Tri Widyastuti is a PhD student in the Sydney Institute of Agriculture
My PhD focuses on developing innovative methods to accurately map and monitor environmental conditions, building on my masters research where I created an interactive, AI-powered real-time soil moisture map for Tasmania.
I was drawn to this field because advanced approaches can help to improve how we understand and manage environmental issues, and tackle real-world environmental challenges. This PhD gives me the opportunity to pursue this passion further and apply it to more complex challenges.
My fascination with soil science began with understanding how soils support ecosystems and agriculture, which led me to study environmental modelling at Bogor Agricultural University in Indonesia.
These experiences became the foundation for my current PhD, where I’m currently in my first year. I’m designing the methodology and beginning to collect data that will help me expand the analytical methods I’ve already used, so that I can monitor other key soil properties beyond just moisture levels.
I found that the University of Sydney stood out for its expertise in interdisciplinary research, combining environmental science with data analytics, geospatial technologies, and applied modelling. Professor Minasny’s leadership in digital soil mapping and innovative modelling approaches perfectly aligned with my interests, making him an ideal supervisor for both my masters and my PhD.
The workload is intense but rewarding, with a good balance between independence and support. I’ve found great networks through my research group and faculty workshops, which have helped me grow technically and professionally. Overall, I genuinely enjoy the collaborative and innovative environment at the University of Sydney.
I’ve been surprised at how transferable AI techniques are across different environmental datasets, and how much interdisciplinary collaboration is needed – from remote sensing to field validation. It’s exciting to see new insights emerge that weren’t visible with traditional methods.
After I’ve completed my PhD, I’d like to continue bridging soil science and AI-powered models, either in academia by developing new tools and methods, or in applied settings where these technologies can support farmers and land managers with real-time soil information.
I wanted to become a supervisor because I like to share my knowledge and experience with students, and at the same time, learn from the new ideas that they bring.
Professor Budiman Minasny
Professor Budiman Minasny
Professor Budiman Minasny is a Professor in soil-landscape modelling in the Faculty of Science and Leader of the Soil, Carbon, and Water research theme at the Sydney Institute of Agriculture. He is a member of the Sydney Southeast Asia Centre and Net Zero Institute.
I am a soil scientist with a particular interest in understanding how soil changes from place to place and how it changes with time.
To do that, we build models at scale, integrating spectroscopy, remote sensing, and AI, creating cost-effective and scalable pipelines for predicting and monitoring soil properties. We aim to provide cost-effective digital techniques that enable soil to be rapidly and precisely measured and mapped, from the surface down to the profile at any scale, from the paddock to across the globe.
The aim is to secure soil for our future.
I have supervised and co-supervised 18 PhD students so far. I wanted to become a supervisor because I like to share my knowledge and experience with students, and at the same time, learn from the new ideas that they bring.
It is a pleasure to guide young scientists to solve problems by growing their skills and confidence. Seeing them grow as the next generation of scientific leaders is rewarding.
Marliana’s research proposal interested me because we know that we can build models that predict soil moisture and demonstrate that it works, but we want to go further than an academic exercise. How can people actually use this information in their daily decisions? We want to bridge the gap between modelling and application by developing systems that deliver real-time, accessible, and actionable information for end users. Marliana’s proposal showed that she understood the dual academic and practical needs of agricultural science.
Marliana has impressed me with her dedication and eagerness to learn. She works hard, approaches new challenges with determination, and is never afraid to take on tasks outside her comfort zone. She trials new approaches and persists through difficulties with a strong commitment to her growth as a researcher.
It has been a pleasure working with Marliana on her Tasmanian soil map. Scaling up the model to deliver a real-time map was a mammoth task, yet she tackled every challenge with persistence and creativity. She worked through each glitch, always striving to make the system function effectively, and the result is a tool that continues to be used to understand farm conditions today.
My key advice to Marliana, and all other research students, is to be curious and critical, keep asking questions, explore new ideas, and push boundaries.