Lilla Irwin
Students
Honours Student
Lilla is an Honours student at the University of New South Wales supervised by Prof Marc Wilkins.
She recently completed her undergraduate degree in Advanced Science with a Major in Genetics and a Minor in Behavioural Economics. Her Honours project focuses on identifying conserved post-translational modifications on ribosomal proteins across a variety of species including Yeast, Human and Arabidopsis.
Junita Christine Soewongsono
Students
Masters by coursework student
Christine is currently a Master’s by coursework student who majors in Applied Mathematics and Mathematical Biology at the School of Mathematics and Statistics of The University of Melbourne. Her research focus will be mainly chemical reaction networks and their properties.
She is completing her research project under the supervision of Professor Robyn Araujo and will also be working with Robyn’s PhD students and research fellows during her studies. Christine completed her Bachelor’s degree in Mathematics (2025) in Nusa Cendana University in Indonesia. Her undergraduate thesis was about graph theory that enabled her to derive structural properties of graphs given an operation, i.e. edge comb products.
Jie Min Lee
Students
PhD Candidate
Jie Min is a PhD student at Monash University, supervised Trevor Lithgow and KJ Goh. Her project aims to investigate how translocation and assembly module (TAM) influences outer membrane proteins (OMPs) biogenesis in Klebsiella pneumoniae.
Jie Min completed a Bachelor’s degree with Honours in Microbiology at Universiti Malaya, Malaysia, where she researched the characterisation of carbapenem-resistant bacteria in environmental water sources. Following graduation, she worked as a research assistant at National University of Singapore, focusing on the proteomics platform in the core facility.
MohammadJavad Vaez
Students
PhD Candidate
Javad is a PhD student at the University of Melbourne working on brain biochemistry. Specifically, his research focuses on bridging chemical reaction networks and neural networks. His work aims to help pave the way for chemical and biological computing, as well as brain-inspired AI.
Javad holds two bachelor’s degrees in Computer Engineering (Hardware) and Mathematics from the University of Isfahan. This interdisciplinary background sparked his interest in unconventional computing methods. He later earned a Master of Computer Science from the University of Tehran, specializing in Artificial Intelligence.
Josh Rottenberry
Students
Masters by Research
Josh is a MPhil student at QUT, supervised by Professor Matthew Simpson and Associate Professor Pascal Buenzli. His research project focuses on advancing likelihood-based optimisation methods with applications to stem cell expansion.
He completed his Bachelors in Mathematics (Applied and Computational Mathematics) at QUT. Throughout his undergraduate studies, he gained research experience using partial differential equations to model biological invasion processes.
Ethan Mitchell
Students
PhD Candidate
Ethan is a PhD student at the University of New South Wales, supervised by Professor Adelle Coster and Professor Erik Meijering. His research focuses on combining mathematical modelling and machine learning techniques to develop model-based deep learning methods for studying biological processes.
Jack Fewtrell
Students
Masters by Research
Jack is a MPhil student at QUT, supervised by Professor Christopher Drovandi and Dr David Warne. His research project focuses on advancing Sequential Monte Carlo methods with applications to central carbon metabolism.
He completed his Bachelors in Mathematics (Statistics) and Information Technology (Computer Science) at QUT. Throughout his undergraduate studies, he gained research experience in Computational Bayesian Statistics.
Bo Ya Looi
Students
PhD Candidate
Bo Ya is a PhD student at Monash University, supervised Michael J. McDonald and Trevor Lithgow. Her project focuses on bacteria defence systems and how phage interactions influence antibiotic resistance and bacterial fitness.
She completed a Bachelor’s with Honours in Biotechnology and worked on postbiotic alternatives for a multi-drug resistant Pseudomonas aeruginosa strain.
Parag Gandhi
Students
Masters by Research
Parag is a quantitative researcher and data specialist with training in mathematics, molecular biology, and engineering.
He completed a BSc (1997) with a double major in Mathematics and Molecular Biology at University of Newcastle, and a BE (Hons) in Bioprocess Engineering at UNSW (2000), with a strong interest in the applied mathematics of bioreactor and process design. He is currently undertaking part-time MSc research at UNSW.
His research interest is in integrating multi-omics measurements with bioreactor process data to identify drivers of yield and variability in yeast bioprocesses, and to build predictive and interpretable models that support strain and process optimisation. His current work involves sourcing multi-omics datasets, applying rigorous quality control and cleaning, and preparing integrated, normalised features for downstream analysis. He plans to extend this with modern machine-learning methods (e.g., graph neural networks and variational autoencoders).
He also brings over 20 years of industry experience building reproducible analytical workflows and large-scale data pipelines across complex, heterogeneous datasets. His industry experience helps him manage complex datasets, build quick prototypes, and scale them into reliable, reproducible analyses.
Lilith Flint
Students
PhD Candidate
Lilith is a PhD student at the University of Melbourne, supervised by Prof. Malcolm McConville, Prof. Jennifer Flegg, and Dr. Eleanor Saunders.
Her research interests include metabolism, parasitology, and fluxomics. Lilith’s PhD project consists of analysing the central carbon
metabolism of the parasite Leishmania spp. from a fluxomics perspective. Before beginning her PhD, Lilith completed her Bachelor’s in Biochemistry/Chemistry at the University of Melbourne, and her Honors with the McConville Laboratory. Her work is a combination of laboratory experiments, data analysis, and programming.