David Ascher

Lab Head

John-Luis Moretti


Douglas Pires

Baker Institute and School of Computing and Information Systems

Thanh-Binh Nguyen

Research Officer

Research interests: computational biology, particularly, the integrative study of proteomics, protein structures, and their functions, virtual screening.

Alex de Sa

Research Officer

Research Interests: Automated and semi-automated learning

Carlos Rodrigues

Research Officer

Research interests: Protein-protein interactions, Machine learning, Deep learning, Web development

Stephanie Portelli

Research Officer

Research interests: drug resistance in infectious and non-infectious diseases

Yoochan Myung

PhD Candidate

Project: Using graph-based signatures to guide antibody engineering and epitope identification.

Raghad Al-Jarf

PhD Candidate

Project: Using machine learning to improve our understanding, and personalizing treatment of cancer.

Saba Ifkhar

PhD Candidate

Project: Exploring cardiotoxicity risk factors.

Bruna Moreira

PhD Candidate

Project: Machine Learning models applied to Vaccine Design and Immunotherapies

Korawich Uthayopas

PhD Candidate

Project: Predicting non-coding RNA disease associations

Joao Velloso

PhD Candidate

Project: Computational guided GPCR engineering and drug development.

Emily Yunzhuo Zhou

PhD Candidate

Project: Developing structure-based deep learning methods to predict mutation effects on proteins

Qisheng Pan

PhD Candidate

Project: Accurate characterisation of the functional effects of protein coding mutations

Joicymara Xavier

PhD Candidate

Project: Investigation of the interaction between multiple mutations on protein stability and function.

Ouli Xie

PhD Candidate

Project: investigation into constraints in penicillin-binding protein mutations in group A and C/G Streptococcus and predicting resistance associated mutations using genomic surveillance data

Ke Meng


Genevieve Clarke


Michael Harper


Michael Milton


Kenny Lam


Project: Predicting and optimising small-molecule pharmacokinetic properties using deep learning

Zachary O'Brien


Project: Application of statistical and machine learning analysis of ICU data to improve patient outcomes

Tammy Pharksuwan


Azadeh Alavi

Research interests: Application of machine learning to clinical data. Image based machine learning.

Malancha Karmakar

Project: Integrating structural and epidemiological modelling to identify which Tuberculosis resistance mutations are likely to arise in a population.

Moshe Olshansky

Research interests: Statistical analysis of 'omic data

Michael Silk

Project: Using population genetic diversity to characterise the mutational tolerance of a given gene, to identify pathogenic variants and structurally and functionally important regions of the protein.

Marialena Michanetzi

Marialena did her Masters of Bioinformatics project with us in 2017-2018, looking at the structural characterisation of Mycobacterium tuberculosis streptomycin resistance variants in gidB.

Jiazhen Hu

Project: Detecting Abnormal Heart Sounds using Image Representations

Mi-Chi Lee

Mi-Chi did her Masters of IT with us in 2019, combining machine learning with phenotypic screening to improve drug development.

Wesley Lam

Project: Predicting activity of small molecules against neglected tropical diseases

Yangyang Long

Project: Building small molecule toxicity predictors

Lee Nguyen

Project: Mapping the role of PTM's in genetic diseases

Yixuan Zhang

Project: Predicting druggable targets

Mengyuan Shen

Project: Predicting the pathogenicity and patient outcomes of BRCA1/2 mutations.

Catherine Song

Project: Structure guided prediction of VHL disease outcomes

Parth Trehan

Project: Using machine and deep learning to process medical imaging data. Building new tools for improved automated analysis and diagnosis from medical images.

Ted Airey

Structural characterisation of ALS disease mutations to predict disease progression.

Elston D'Souza

Project: Identification and characterisation of proteins under different selective pressures between ethnic populations.

Noa Levi

Sophia Muller-Dott

Amanda Albanaz

Amanda did her undergraduate and Masters of Bioinformatics with us 2016-2018 looking at the structural characterisation of ALS disease mutations to predict disease progression. She is now pursuing her PhD at the University of Ostrava, Czech Republic.

Aaron Barnard

Aaron did his undergraduate project with us in 2018 looking at mapping population variation in malaria. He is now studying medicine at Melbourne University.

Vittoria Cicaloni

Vittoria joined us in 2019 to work on the structural analysis of genetic disease causing variants. She is now completing her PhD research programme at the University of Siena.

Anna Visibelli

Anna joined us in 2019 to work on an automatic modelling pipeline. She is now completing her PhD research programme at the University of Siena.

Anjali Garg

Anjalia completed her summer internship in the group in 2019. She developed a method to predict antimicrobial peptide activity. She is now looking forward to starting her PhD in the US.

Hardik Parate

Hardik worked with the group in 2019 to develop a method to map the drugability of protein surfaces.

Lucy Barr

Megan Pat

Project: Predicting drug resistant mutations in Abl