Meet our latest PhD Scholarship recipients

As part of the Monash Data Futures Institute’s (MDFI) initiative to support the next generation of AI and data science leaders, we are pleased to introduce our three newest recipients of MDFI PhD Scholarships.

They join our existing cohort of PhD students to accelerate our progress in addressing research problems using AI and data science, and to further our work in AI for social good.



Zachary Daus

Zachary Daus completed a BA in Philosophy at Macalester College in the United States of America and an MA in Research Philosophy at the University of Vienna in Austria. While studying in Austria, Zachary was also embedded in an interdisciplinary project at Joanneum Research that investigated the design of trust in human-robot interaction.

Zachary has already presented and published on topics such as responsible innovation, the ethics of human-robot interaction and polarisation on social media. In addition to his research interests, Zachary enjoys attending concerts, playing the piano and learning languages. He is currently tackling his first Slavic language: Croatian.

He also enjoys teaching language, having worked for two years as an assistant English Instructor in the Viennese Public School System prior to beginning his MA in Philosophy. He hopes to continue teaching as a graduate student at Monash.

As a recipient of the MDFI scholarship, Zachary is involved in an interdisciplinary project that is developing ethical approaches to the use of Artificial Intelligence in medicine, along with the Faculty of Arts and the Faculty of Medicine, Nursing & Health Sciences. Specifically, his PhD project aims to address how the medical treatment of epilepsy can utilise recent advancements in artificial intelligence while doing so in a way that is ethical and humane.



Mathew Lim

Mathew Lim completed a Bachelor of Computer Science (Honours) degree at Monash University, during which he explored ways to integrate law enforcement databases in collaboration with the Australian Federal Police. He then worked as a research officer at Monash Information Technology, where he was introduced to the field of ecological modelling.

Mathew likes being involved in projects that benefit society and nature. He chose his honours research project based on its potential to help law enforcement agencies investigate crime. He was drawn to his current research area by the possibility of making contributions to the good of ecosystems.

Mathew has interests in Java programming, software design and computer simulations, and has had the opportunity to indulge all three while working on computer programs that model ecological processes. He enjoys meeting students and researchers from different areas, and being a member of interdisciplinary teams that bring together people with IT and other backgrounds.

Mathew's PhD project involves developing software to analyse video tracking data from bee experiments, in collaboration with the Department of Data Science and AI in the Faculty of IT, and the School of Biological Sciences in the Faculty of Science. This software helps researchers to gain insights into bee behaviour by automatically and accurately measuring bee movement patterns in the data.



Kevin Liu

Kevin Liu completed his Bachelor of Engineering (Honours) at Monash University whilst achieving first class honours and winning two academic awards for being the highest achieving student in two separate undergraduate units. His honours thesis titled "Enhancing Turbulent Velocity Field Measurements via Scientific Machine Learning (SciML)", won the 3rd place at the 2022 American Institute of Aeronautics and Astronautics student conference.

Kevin’s introduction to the world of Machine Learning started in 2021, where he was part of a summer research program under the supervision of Professor Julio Soria, which eventually became his honours project in his final year.

In his spare time, he likes to watch movies and play video games with his friends.

As a MDFI scholarship recipient, he will be working on the development of Machine Learning frameworks for predicting bushfire dynamics - a cross-discipline PhD project along with the Department of Mechanical and Aerospace Engineering in the Faculty of Engineering, and the School of Mathematics in the Faculty of Science. This project aims to use AI/ML models to improve our understanding of bushfires, which will be increasingly important in the years to come.