Associate Professor Fatemeh Vafaee

Associate Professor Fatemeh Vafaee

Associate Professor
Science
School of Biotech & Biomolecular Science

Professional Experience:

  • 2023 - Present: Associate Professor, School of Biotechnology and Biomolecular Sciences (BABS), UNSW Sydney
  • 2021 - Present: Deputy Director, UNSW Data Science Hub (uDASH), UNSW 
  • 2020 - Present: Theme Leader, Health Data Science, uDASH, UNSW
  • 2017 - 2022: Senior Lecturer, School of Biotechnology and Biomolecular Sciences (BABS), UNSW Sydney
  • 2013 - 2017: Research Fellow, Charles Perkins Centre, School of Mathematics and Statistics, University of Sydney
  • 2011 - 2013: Postdoctoral Research Associate, University of Toronto, University Health Network and Ontario Cancer Institute
  • 2007 - 2011: PhD Computer Science, Artificial Intelligence (AI), the University of Illinois in Chicago

Brief Bio and Research Contribution:

Dr Vafaee is the Deputy Director of UNSW Data Science Hub (uDASH) since 2021 and an A/Professor in Computational Biomedicine and Bioinformatics at the School of BABS. She received her PhD in Artificial Intelligence from the School of Computer Science at the University of Illinois at Chicago, USA (2011) followed by 2 multidisciplinary postdoctoral fellowships on computational biomedicine at the University of Toronto, University Health Network (2011 – 2012), and at the University of Sydney, Charles Perkins Centre (2013 – 2017).

Dr Vafaee has launched (2017) and leads AI-enhanced Biomedicine Laboratory at UNSW (www.VafaeeLab.com), collaboratively working on deploying advanced AI techniques to address various pressing biomedical problems. Relying on multidisciplinary expertise and cross-faculty collaborations, Dr Vafaee and her team are developing advanced machine-learning methods and deep-learning models that leverage large omics data to find hidden structures within them, account for complex interactions among the measurements, integrate heterogeneous data and make accurate predictions in different biomedical applications ranging from multi-omics biomarker discovery to single-cell multi-omics and drug repositioning.

Dr Vafaee has a strong track record of multidisciplinary research leadership and industrial engagement. Her research has attracted >$12.3M for over 12 research projects and industrial partnership grants, including prestigious schemes of Cooperative Research Centre Project (CRC-P, 2019), Medical Research Future Fund (MRFF, 2020, 2021), ARC Discovery (2021), and NHMRC Development (2021), and Next-Generation Graduate Program, CSIRO/Data61 (2022). She has co-authored over 50 publications (68% first/corresponding author) in prestigious venues—e.g., Nucleic Acids Research (IF:19.160)*, Briefing in Bioinformatics x3 (IF:13.994)*, IEEE Trans on Cybernetics (IF:19.118)*, Bioinformatics (IF:6.931)*, Artificial Intelligence Review x2 (IF:9.588)*, IEEE Journal of Biomedical and Health Informatics (IF:7.021), Precision Oncology (IF:10.123), Cell & Bioscience (IF:9.597)*, Cancer Science (IF:6.716)*, Nature Methods (IF:47.990), Nature Communications (IF:17.694), Alzheimer’s & Dementia (IF:16.655); * indicates the corresponding authorship—demonstrating her research leadership and substantive contribution in methodological changes.


Governance and Executive memberships:


Editorial Activities:

  • Associate Editor of Artificial Intelligence Review, 2017 – Now (IF: 9.588, top 5% in AI), handled 180+ manuscripts.
  • Editorial Board of Journal of Cancers, 2021 – Now (IF: 6.639),
  • Advisory Board of Journal of Patterns, by Cell Press, 2021 – Now
  • Reviewer of multiple top-tier journals and grant agencies – e.g., Briefing in Bioinformatics (IF: 13:994), Bioinformatics (IF: 6.937), Cancers (IF: 6.639), Therapeutic Advances in Medical Oncology (IF: 8.168), Artificial Intelligence Review (IF: 9.588), IEEE Trans on Neural Networks & Learning Systems (IF: 14.26). I also review funding agencies, e.g., ARC (DP and DECRA).

Areas of Research Projects:

1) Minimally invasive biomarker discovery for personalised medicine and precision therapy: Recent advances in high-throughput technologies have provided a wealth of genomics, transcriptomics, and proteomics data to decipher disease mechanisms in a holistic and integrative manner. Such a plethora of -omics data has opened new avenues for translational medical research and has particularly facilitated the discovery of novel biomarkers for complex diseases such as cancers. My research lab – in close collaboration with experimentalists, clinicians, and oncologists – is adopting an innovative multi-disciplinary approach to tackle one of the biggest challenges of personalised cancer medicine, which is to identify robust and reproducible biomarkers in a minimally invasive way.  We are integrating multiple data sources, network and temporal information using advanced machine learning approaches to better understand the molecular complexity underpinning pathogenesis and to identify novel, precise and reproducible blood-based biomarkers for disease early detection, diagnosis, prognosis and drug responses, paving the way for personalised medicine.

Examples of publications: (Ebrahimkhani et al., Molecular Neurobiology, 2020), (Colvin et al. Cancer Science, 2020), (Vafaee et al., Systems Biology and Applications, 2018),  (Ebrahimkhani et al., Precision Oncology, 2018)

2) Single-cell sequencing data analysis and integration: Cellular heterogeneity is one of the main clinical drivers of the current inefficiency in treating cancer and other complex diseases as molecular-based prescriptions or personalised medicine have often relied on bulk pro/filing of cell populations, masking intercellular variations that are functionally and clinically important. In recent years, however, there has been an increasing effort to shift the focus from bulk to single-cell profiling. Single-cell sequencing will have a major global impact on precision medicine by detecting rare disease-associated cells and identifying cell-type-specific biomarkers and therapeutic targets. Single cells, however, make ‘big data’, provoking substantial analytical challenges to decipher underlying biological and clinical insights. Hence, there is an emerging demand for scalable yet accurate analysis pipelines for rapidly increasing single-cell sequencing data. 

Examples of publications: (Koch et al., Briefings in Bioinformatics, 2021), (Zandavi et al., NAR, doi.org/10.1093/nar/gkac436), (Zandavi et al., Artificial intelligence Review, doi: 10.1007/s10462-022-10357-4)

3) Computational drug repositioning and network pharmacology: Repositioning existing drugs for new indications is an innovative drug development strategy offering the possibility of reduced cost, time and risk as several phases of de-novo drug discovery can be bypassed for repositioning candidates. Biopharmaceutical companies have recognised the advantages of repositioning, and investment in the area is dramatically increasing. With the rapid advancement of high-throughput technologies and the explosion of various biological and medical data, computational drug repositioning has become an increasingly powerful approach to systematically identify potential repositioning candidates. My lab is the only group at UNSW, and one of the few across Australia, advancing the field of computational drug repositioning. We are developing computational tools and databases which integrate massive amounts of biological, pharmacological and biomedical information related to compounds into advanced machine learning or network-based models to predict accurate repositioning candidates.

Examples of publications: (Azad et al, Briefings in Bioinformatics, 2020), (Azad et al, Patterns, 2021)

Phone
+61-2-9065 2699
Location
School of Biotechnology and Biomolecular Sciences Room 2110 Level 2 East Bioscience South E26
  • Journal articles | 2024
    Besharatifard M; Vafaee F, 2024, 'A review on graph neural networks for predicting synergistic drug combinations', Artificial Intelligence Review, 57, http://dx.doi.org/10.1007/s10462-023-10669-z
    Journal articles | 2024
    Li D; Heffernan K; Koch FC; Peake DA; Pascovici D; David M; Kehelpannala C; Mann GB; Speakman D; Hurrell J; Preston S; Vafaee F; Batarseh A, 2024, 'Discovery of Plasma Lipids as Potential Biomarkers Distinguishing Breast Cancer Patients from Healthy Controls', International Journal of Molecular Sciences, 25, http://dx.doi.org/10.3390/ijms252111559
    Journal articles | 2024
    Lim A; Kehelpannala C; Vafaee F; Koch F; Pascovici D; Li D; Heffernan K; Lamoury G; Batarseh A; Mann B, 2024, 'Abstract PO4-07-02: Development of an Artificial Intelligence-based breast cancer detection model using Plasma Lipidomic Signature', Cancer Research, 84, http://dx.doi.org/10.1158/1538-7445.sabcs23-po4-07-02
    Journal articles | 2024
    Qayyum A; Benzinou A; Razzak I; Mazher M; Nguyen TT; Puig D; Vafaee F, 2024, '3D-IncNet: Head and Neck (H&N) Primary Tumors Segmentation and Survival Prediction', IEEE Journal of Biomedical and Health Informatics, 28, pp. 1185 - 1194, http://dx.doi.org/10.1109/JBHI.2022.3219445
    Journal articles | 2024
    Thoms JAI; Koch FC; Raei A; Subramanian S; Wong JWH; Vafaee F; Pimanda JE, 2024, 'BloodChIP Xtra: an expanded database of comparative genome-wide transcription factor binding and gene-expression profiles in healthy human stem/progenitor subsets and leukemic cells', Nucleic Acids Research, 52, pp. D1131 - D1137, http://dx.doi.org/10.1093/nar/gkad918
    Journal articles | 2024
    Zandavi SM; Kim C; Goodwin T; Thilakanathan C; Bostanara M; Akon AC; Al Mouiee D; Barisic S; Majeed A; Kemp W; Chu F; Smith M; Collins K; Wong VWS; Wong GLH; Behary J; Roberts SK; Ng KKC; Vafaee F; Zekry A, 2024, 'AI-powered prediction of HCC recurrence after surgical resection: Personalised intervention opportunities using patient-specific risk factors', Liver International, 44, pp. 2724 - 2737, http://dx.doi.org/10.1111/liv.16050
    Journal articles | 2023
    Ahmadzada T; Vijayan A; Vafaee F; Azimi A; Reid G; Clarke S; Kao S; Grau GE; Hosseini-Beheshti E, 2023, 'Small and Large Extracellular Vesicles Derived from Pleural Mesothelioma Cell Lines Offer Biomarker Potential', Cancers, 15, http://dx.doi.org/10.3390/cancers15082364
    Journal articles | 2023
    Batarseh AM; Vafaee F; Hosseini-Beheshti E; Safarchi A; Chen A; Cohen A; Juillard A; Hunt NH; Mariani M; Mitchell T; Grau GER, 2023, 'Investigation of Plasma-Derived Lipidome Profiles in Experimental Cerebral Malaria in a Mouse Model Study', International Journal of Molecular Sciences, 24, http://dx.doi.org/10.3390/ijms24010501
    Journal articles | 2023
    Choi WWY; Sánchez C; Li JJ; Dinarvand M; Adomat H; Ghaffari M; Khoja L; Vafaee F; Joshua AM; Chi KN; Guns EST; Hosseini-Beheshti E, 2023, 'Extracellular vesicles from biological fluids as potential markers in castration resistant prostate cancer', Journal of Cancer Research and Clinical Oncology, 149, pp. 4701 - 4717, http://dx.doi.org/10.1007/s00432-022-04391-6
    Journal articles | 2023
    Gano C; Fatima S; Failes T; Arndt G; Sajinovic M; Mahns D; Saedisomeolia A; Coorssen J; Bucci J; DeSouza P; Vafaee F; Scott K, 2023, 'Anti-cancer potential of synergistic phytochemical combinations is influenced by the genetic profiles of prostate cancer cell lines', Frontiers in Nutrition, http://dx.doi.org/10.3389/fnut.2023.1119274
    Journal articles | 2023
    Gunawan I; Vafaee F; Meijering E; Lock JG, 2023, 'An introduction to representation learning for single-cell data analysis', Cell Reports Methods, 3, http://dx.doi.org/10.1016/j.crmeth.2023.100547
    Journal articles | 2023
    Khazaal A; Zandavi SM; Smolnikov A; Fatima S; Vafaee F, 2023, 'Pan-Cancer Analysis Reveals Functional Similarity of Three lncRNAs across Multiple Tumors', International Journal of Molecular Sciences, 24, http://dx.doi.org/10.3390/ijms24054796
    Journal articles | 2023
    Mandal A; Priyam S; Chan HH; Gouveia BM; Guitera P; Song Y; Baker MAB; Vafaee F, 2023, 'Computer-Aided Diagnosis of Melanoma Subtypes Using Reflectance Confocal Images', Cancers, 15, http://dx.doi.org/10.3390/cancers15051428
    Journal articles | 2023
    Safari F; Kehelpannala C; Safarchi A; Batarseh AM; Vafaee F, 2023, 'Biomarker Reproducibility Challenge: A Review of Non-Nucleotide Biomarker Discovery Protocols from Body Fluids in Breast Cancer Diagnosis', Cancers, 15, pp. 2780, http://dx.doi.org/10.3390/cancers15102780
    Journal articles | 2023
    Subramanian S; Thoms JAI; Huang Y; Cornejo-Páramo P; Koch FC; Jacquelin S; Shen S; Song E; Joshi S; Brownlee C; Woll PS; Chacon-Fajardo D; Beck D; Curtis DJ; Yehson K; Antonenas V; O'Brien T; Trickett A; Powell JA; Lewis ID; Pitson SM; Gandhi MK; Lane SW; Vafaee F; Wong ES; Göttgens B; Alinejad-Rokny H; Wong JWH; Pimanda JE, 2023, 'Genome-wide transcription factor–binding maps reveal cell-specific changes in the regulatory architecture of human HSPCs', Blood, 142, pp. 1448 - 1462, http://dx.doi.org/10.1182/blood.2023021120
    Journal articles | 2023
    Zandavi SM; Liu D; Chung V; Anaissi A; Vafaee F, 2023, 'Fotomics: fourier transform-based omics imagification for deep learning-based cell-identity mapping using single-cell omics profiles', Artificial Intelligence Review, 56, pp. 7263 - 7278, http://dx.doi.org/10.1007/s10462-022-10357-4
    Journal articles | 2022
    Dinarvand M; Koch FC; Mouiee DA; Vuong K; Vijayan A; Tanzim AF; Azad AKM; Penesyan A; Castaño-Rodríguez N; Vafaee F, 2022, 'dRNASb: a systems biology approach to decipher dynamics of host-pathogen interactions using temporal dual RNA-seq data', Microbial Genomics, 8, http://dx.doi.org/10.1099/mgen.0.000862
    Journal articles | 2022
    Fatima S; Ma Y; Safrachi A; Haider S; Spring KJ; Vafaee F; Scott KF; Roberts TL; Becker TM; de Souza P, 2022, 'Harnessing Liquid Biopsies to Guide Immune Checkpoint Inhibitor Therapy', Cancers, 14, http://dx.doi.org/10.3390/cancers14071669
    Journal articles | 2022
    Vijayan A; Fatima S; Sowmya A; Vafaee F, 2022, 'Blood-based transcriptomic signature panel identification for cancer diagnosis: Benchmarking of feature extraction methods', Briefings in Bioinformatics, 23, http://dx.doi.org/10.1093/bib/bbac315
    Journal articles | 2022
    Zandavi SM; Koch FC; Vijayan A; Zanini F; Mora FV; Ortega DG; Vafaee F, 2022, 'Disentangling single-cell omics representation with a power spectral density-based feature extraction', Nucleic Acids Research, 50, pp. 5482 - 5492, http://dx.doi.org/10.1093/nar/gkac436
    Journal articles | 2021
    Azad AKM; Dinarvand M; Nematollahi A; Swift J; Lutze-Mann L; Vafaee F, 2021, 'A comprehensive integrated drug similarity resource for in-silico drug repositioning and beyond', Briefings in Bioinformatics, 22, http://dx.doi.org/10.1093/bib/bbaa126
    Journal articles | 2021
    Azad AKM; Fatima S; Capraro A; Waters SA; Vafaee F, 2021, 'Integrative resource for network-based investigation of COVID-19 combinatorial drug repositioning and mechanism of action', Patterns, 2, pp. 100325, http://dx.doi.org/10.1016/j.patter.2021.100325
    Journal articles | 2021
    Capraro A; Wong S; Adhikari A; Allan K; Patel H; Zhong L; Raftery M; Jaffe A; Yeang M; Aggarwal A; Wu L; Pandzic E; Whan R; Turville S; Vittorio O; Bull R; Kaakoush N; Rawlinson W; Tedla N; Vafaee F; Waters S, 2021, 'Ageing impairs the airway epithelium defence response to SARS-CoV-2', , http://dx.doi.org/10.1101/2021.04.05.437453
    Journal articles | 2021
    Koch FC; Sutton GJ; Voineagu I; Vafaee F, 2021, 'Supervised application of internal validation measures to benchmark dimensionality reduction methods in scRNA-seq data', Briefings in Bioinformatics, 22, http://dx.doi.org/10.1093/bib/bbab304
    Journal articles | 2021
    Safarchi A; Fatima S; Ayati Z; Vafaee F, 2021, 'An update on novel approaches for diagnosis and treatment of SARS-CoV-2 infection', Cell and Bioscience, 11, http://dx.doi.org/10.1186/s13578-021-00674-6
    Journal articles | 2021
    Scott KF; Mann TJ; Fatima S; Sajinovic M; Razdan A; Kim RR; Cooper A; Roohullah A; Bryant KJ; Gamage KK; Harman DG; Vafaee F; Graham GG; Church WB; Russell PJ; Dong Q; de Souza P, 2021, 'Human group iia phospholipase A2 —three decades on from its discovery', Molecules, 26, http://dx.doi.org/10.3390/molecules26237267
    Journal articles | 2021
    Shahriari S; Hossein Rashidi T; Azad AKM; Vafaee F, 2021, 'COVIDSpread: real-time prediction of COVID-19 spread based on time-series modelling', F1000Research, 10, http://dx.doi.org/10.12688/f1000research.73969.1
    Journal articles | 2021
    Zandavi SM; Rashidi TH; Vafaee F, 2021, 'Dynamic Hybrid Model to Forecast the Spread of COVID-19 Using LSTM and Behavioral Models Under Uncertainty', IEEE Transactions on Cybernetics, http://dx.doi.org/10.1109/TCYB.2021.3120967
    Journal articles | 2020
    Azad AKM; Fatima S; Vafaee F, 2020, 'An Integrative Resource for Network-Based Investigation of COVID-19 Combinatorial Drug Repositioning and Mechanism of Action', , http://dx.doi.org/10.26434/chemrxiv.13271096.v1
    Journal articles | 2020
    Bayati M; Rabiee HR; Mehrbod M; Vafaee F; Ebrahimi D; Forrest ARR; Alinejad-Rokny H, 2020, 'CANCERSIGN: a user-friendly and robust tool for identification and classification of mutational signatures and patterns in cancer genomes', Scientific Reports, 10, pp. 1286, http://dx.doi.org/10.1038/s41598-020-58107-2
    Journal articles | 2020
    Colvin EK; Howell VM; Mok SC; Samimi G; Vafaee F, 2020, 'Expression of long noncoding RNAs in cancer-associated fibroblasts linked to patient survival in ovarian cancer', Cancer Science, 111, pp. 1805 - 1817, http://dx.doi.org/10.1111/cas.14350
    Journal articles | 2020
    Dinarvand M; Spain MP; Vafaee F, 2020, 'Pharmacodynamic Functions of Synthetic Derivatives for Treatment of Methicillin-Resistant Staphylococcus aureus (MRSA) and Mycobacterium tuberculosis', Frontiers in Microbiology, 11, http://dx.doi.org/10.3389/fmicb.2020.551189
    Journal articles | 2020
    Ebrahimkhani S; Beadnall HN; Wang C; Suter CM; Barnett MH; Buckland ME; Vafaee F, 2020, 'Serum Exosome MicroRNAs Predict Multiple Sclerosis Disease Activity after Fingolimod Treatment', Molecular Neurobiology, 57, pp. 1245 - 1258, http://dx.doi.org/10.1007/s12035-019-01792-6
    Journal articles | 2020
    Walsh K; Voineagu MA; Vafaee F; Voineagu I, 2020, 'TDAview: An online visualization tool for topological data analysis', Bioinformatics, 36, pp. 4805 - 4809, http://dx.doi.org/10.1093/bioinformatics/btaa600
    Journal articles | 2019
    Su Z; Burchfield JG; Yang P; Humphrey SJ; Yang G; Francis D; Yasmin S; Shin SY; Norris DM; Kearney AL; Astore MA; Scavuzzo J; Fisher-Wellman KH; Wang QP; Parker BL; Neely GG; Vafaee F; Chiu J; Yeo R; Hogg PJ; Fazakerley DJ; Nguyen LK; Kuyucak S; James DE, 2019, 'Global redox proteome and phosphoproteome analysis reveals redox switch in Akt', Nature Communications, 10, http://dx.doi.org/10.1038/s41467-019-13114-4
    Journal articles | 2019
    Wong MWK; Braidy N; Pickford R; Vafaee F; Crawford J; Muenchhoff J; Schofield P; Attia J; Brodaty H; Sachdev P; Poljak A, 2019, 'Plasma lipidome variation during the second half of the human lifespan is associated with age and sex but minimally with BMI', PLoS ONE, 14, pp. e0214141, http://dx.doi.org/10.1371/journal.pone.0214141
    Journal articles | 2018
    Chaudhuri R; Krycer JR; Fazakerley DJ; Fisher-Wellman KH; Su Z; Hoehn KL; Yang JYH; Kuncic Z; Vafaee F; James DE, 2018, 'The transcriptional response to oxidative stress is part of, but not sufficient for, insulin resistance in adipocytes', Scientific Reports, 8, pp. 1774, http://dx.doi.org/10.1038/s41598-018-20104-x
    Journal articles | 2018
    Contaldi C; Vafaee F; Nelson P, 2018, 'Bayesian network hybrid learning using an elite-guided genetic algorithm', Artificial Intelligence Review, pp. 1 - 1, http://dx.doi.org/10.1007/s10462-018-9615-5
    Journal articles | 2018
    Ebrahimkhani S; Vafaee F; Hallal S; Wei H; Lee MYT; Young PE; Satgunaseelan L; Beadnall H; Barnett MH; Shivalingam B; Suter CM; Buckland ME; Kaufman KL, 2018, 'Deep sequencing of circulating exosomal microRNA allows non-invasive glioblastoma diagnosis', npj Precision Oncology, 2, http://dx.doi.org/10.1038/s41698-018-0071-0
    Journal articles | 2018
    Vafaee F; Dashti H; Alinejad-Rokny H, 2018, 'Transcriptomic Data Normalization', Encyclopedia of Bioinformatics and Computational Biology, Elsevier, http://dx.doi.org/10.1016/B978-0-12-809633-8.20209-4
    Journal articles | 2018
    Vafaee F; Diakos C; Kirschner M; Reid G; Michael M; Horvath LISA; Alinejad-Rokny H; Cheng ZJ; Kuncic Z; Clarke S, 2018, 'A data-driven, knowledge-based approach to biomarker discovery: application to circulating microRNA markers of colorectal cancer prognosis', npj Systems Biology and Applications, 4, pp. 20 - 20, http://dx.doi.org/10.1038/s41540-018-0056-1
    Journal articles | 2017
    Domanova W; Krycer JR; Chaudhuri R; Yang P; Vafaee F; Fazakerley DJ; Humphrey SJ; James DE; Kuncic Z, 2017, 'Erratum: Unraveling kinase activation dynamics using kinase-substrate relationships from temporal large-scale phosphoproteomics studies (PLoS ONE (2016) 11: 6 (e0157763) DOI: 10.1371/journal.pone.0157763)', PLoS ONE, 12, pp. e0185871, http://dx.doi.org/10.1371/journal.pone.0185871
    Journal articles | 2017
    Ebrahimkhani S; Vafaee F; Young PE; Hur SSJ; Hawke S; Devenney E; Beadnall H; Barnett MH; Suter CM; Buckland ME, 2017, 'Exosomal microRNA signatures in multiple sclerosis reflect disease status', Scientific Reports, 7, pp. 14293, http://dx.doi.org/10.1038/s41598-017-14301-3
    Journal articles | 2017
    Vafaee F; Colvin EK; Mok SC; Howell VM; Samimi G, 2017, 'Functional prediction of long non-coding RNAs in ovarian cancer-Associated fibroblasts indicate a potential role in metastasis', Scientific Reports, 7, pp. 10374, http://dx.doi.org/10.1038/s41598-017-10869-y
    Journal articles | 2016
    Domanova W; Krycer J; Chaudhuri R; Yang P; Vafaee F; Fazakerley D; Humphrey S; James D; Kuncic Z, 2016, 'Unraveling kinase activation dynamics using kinase-substrate relationships from temporal Large-Scale phosphoproteomics studies', PLoS ONE, 11, pp. e0157763, http://dx.doi.org/10.1371/journal.pone.0157763
    Journal articles | 2016
    Parker NR; Hudson AL; Khong P; Parkinson JF; Dwight T; Ikin RJ; Zhu Y; Cheng ZJ; Vafaee F; Chen J; Wheeler HR; Howell VM, 2016, 'Intratumoral heterogeneity identified at the epigenetic, genetic and transcriptional level in glioblastoma', Scientific Reports, 6, http://dx.doi.org/10.1038/srep22477
    Journal articles | 2016
    Rollo JL; Banihashemi N; Vafaee F; Crawford JW; Kuncic Z; Holsinger RMD, 2016, 'Unraveling the mechanistic complexity of Alzheimer's disease through systems biology', Alzheimer's and Dementia, 12, pp. 708 - 718, http://dx.doi.org/10.1016/j.jalz.2015.10.010
    Journal articles | 2016
    Vafaee F; Krycer JR; Ma X; Burykin T; James DE; Kuncic Z, 2016, 'ORTI: An open-access Repository of transcriptional interactions for interrogating mammalian gene expression data', PLoS ONE, 11, pp. e0164535, http://dx.doi.org/10.1371/journal.pone.0164535
    Journal articles | 2016
    Vafaee F, 2016, 'Using multi-objective optimization to identify dynamical network biomarkers as early-warning signals of complex diseases', Scientific Reports, 6, http://dx.doi.org/10.1038/srep22023
    Journal articles | 2016
    Wilkins K; Hassan M; Francescatto M; Jespersen J; Parra RG; Cuypers B; DeBlasio D; Junge A; Jigisha A; Rahman F; Laenen G; Willems S; Thorrez L; Moreau Y; Raju N; Chothani SP; Ramakrishnan C; Sekijima M; Gromiha MM; Slator PJ; Burroughs NJ; Szałaj P; Tang Z; Michalski P; Luo O; Li X; Ruan Y; Plewczynski D; Fiscon G; Weitschek E; Ciccozzi M; Bertolazzi P; Felici G; Cuypers B; Meysman P; Vanaerschot M; Berg M; Imamura H; Dujardin J-C; Laukens K; Domanova W; Krycer JR; Chaudhuri R; Yang P; Vafaee F; Fazakerley DJ; Humphrey SJ; James DE; Kuncic Z, 2016, 'Highlights from the 11th ISCB Student Council Symposium 2015. Dublin, Ireland. 10 July 2015.', BMC Bioinformatics, 17 Suppl 3, pp. 95, http://dx.doi.org/10.1186/s12859-016-0901-4
    Journal articles | 2014
    Kotlyar M; Pastrello C; Pivetta F; Lo Sardo A; Cumbaa C; Li H; Naranian T; Niu Y; Ding Z; Vafaee F; Broackes-Carter F; Petschnigg J; Mills GB; Jurisicova A; Stagljar I; Maestro R; Jurisica I, 2014, 'In silico prediction of physical protein interactions and characterization of interactome orphans', Nature Methods, 12, pp. 79 - 84, http://dx.doi.org/10.1038/nmeth.3178
    Journal articles | 2013
    Vafaee F; Rosu D; Broackes-Carter F; Jurisica I, 2013, 'Novel semantic similarity measure improves an integrative approach to predicting gene functional associations.', BMC systems biology, 7, pp. 22, http://dx.doi.org/10.1186/1752-0509-7-22
    Journal articles | 2008
    Vafaee F; Nelson PC; Zhou C; Xiao W, 2008, 'Dynamic adaptation of genetic operators' probabilities', Studies in Computational Intelligence, 129, pp. 159 - 168, http://dx.doi.org/10.1007/978-3-540-78987-1_15
  • Working Papers | 2021
    Vafaee F; Gallego-Ortega D; Zanini F; Zandavi SM; Koch F; Valdes Mora F, 2021, Disentangling single-cell omics representation with a power spectral density-based feature extraction, Cold Spring Harbor Laboratory, http://dx.doi.org10.1101/2021.10.25.465657
  • Preprints | 2024
    Aminzadeh F; Wu J; He J; Saberi M; Vafaee F, 2024, Single-Cell Data Integration and Cell Type Annotation through Contrastive Adversarial Open-set Domain Adaptation, http://dx.doi.org/10.1101/2024.10.04.616599
    Preprints | 2024
    Lock J; Gunawan I; Kohane F; Nguyen K; Zheng Y; Neumann D; Vafaee F; Meijering E, 2024, Seeing more with less: Extensible Immunofluorescence (ExIF) accessibly generates high-plexity datasets by integrating standard 4-plex imaging data, http://dx.doi.org/10.21203/rs.3.rs-4872456/v1
    Preprints | 2024
    Su Z; Fang M; Smolnikov A; Dinger M; Oates E; Vafaee F, 2024, Multifaceted Representation of Genes via Deep Learning of Gene Expression Networks, http://dx.doi.org/10.1101/2024.03.07.583777
    Preprints | 2024
    Su Z; Fang M; Smolnikov A; Vafaee F; Dinger M; Oates E, 2024, Genes in Humans and Mice: Insights from Deep learning of 777K Bulk Transcriptomes, http://dx.doi.org/10.1101/2024.04.01.587517
    Preprints | 2023
    Besharatifard M; Vafaee F, 2023, A Review on Graph Neural Networks for Predicting Synergistic Drug Combinations, http://dx.doi.org/10.21203/rs.3.rs-3318384/v1
    Preprints | 2023
    Subramanian S; Subramanian S; Thoms JAI; Huang Y; Cornejo P; Koch F; Jacquelin S; Shen S; Song E; Joshi S; Brownlee C; Woll P; Fajardo DC; Beck D; Curtis D; Yehson K; Antonenas V; Brien TO; Trickett A; Powell J; Lewis I; Pitson S; Gandhi M; Lane S; Vafaee F; Wong E; Göttgens B; Rokny HA; Wong JWH; Pimanda J, 2023, Cell Type-Specific Regulation by a Heptad of Transcription Factors in Human Hematopoietic Stem and Progenitor Cells, http://dx.doi.org/10.1101/2023.04.18.537282
    Preprints | 2022
    Anaissi A; Zandavi SM; Suleiman B; Alyassine W; Braytee A; Vafaee F, 2022, A Benchmark of Pre-processing Effect on Single Cell RNA Sequencing Integration Methods, http://dx.doi.org/10.21203/rs.3.rs-2249309/v1
    Preprints | 2022
    Choi WY; Sánchez C; Li JJ; Dinarvand M; Adomat H; Ghaffari M; Khoja L; Vafaee F; Joshua AM; Chi KN; Guns EST; Hosseini-Beheshti E, 2022, Extracellular vesicles from biological fluids as potential biomarkers for prostate cancer, http://dx.doi.org/10.21203/rs.3.rs-1948091/v1
    Preprints | 2022
    Dinarvand M; Kock F; Al Mouiee D; Vuong K; Vijayan A; Tanzim AF; Azad AKM; Penesyan A; Castaño-Rodríguez N; Vafaee F, 2022, dSeqSb: A systems biology approach to decipher dynamics of host-pathogen interactions using temporal dual RNA-seq data, http://dx.doi.org/10.1101/2022.02.28.482417
    Preprints | 2022
    Khazaal A; Zandavi SM; Smolnikov A; Fatima S; Vafaee F, 2022, Pan-cancer Analyses reveal functional similarities of three lncRNAs across multiple tumors, http://dx.doi.org/10.1101/2022.03.14.22272396
    Preprints | 2022
    Liu D; Zandavi SM; Chung V; Anaissi A; Vafaee F, 2022, Omics Imagification: Transforming High-throughput Molecular Representation of a Cell into an Image, http://dx.doi.org/10.21203/rs.3.rs-1919175/v1
    Preprints | 2022
    Mandal A; Priyam S; Chan HH; Gouveia BM; Guitera P; Song Y; Baker MAB; Vafaee F, 2022, Computer-aided diagnosis of reflectance confocal images to differentiate between lentigo maligna (LM) and atypical intraepidermal melanocytic proliferation (AIMP), , http://dx.doi.org/10.1101/2022.05.10.491423
    Preprints | 2022
    Vijayan A; Fatima S; Sowmya A; Vafaee F, 2022, Blood-based transcriptomic signature panel identification for cancer diagnosis: Benchmarking of feature extraction methods, http://dx.doi.org/10.1101/2022.03.13.483368
    Preprints | 2022
    Zandavi SM; Liu D; Chung V; Anaissi A; Vafaee F, 2022, Fotomics: Fourier transform-based omics imagification for deep learning-based cell-identity mapping using single-cell omics profiles, http://dx.doi.org/10.1101/2022.07.08.499309
    Preprints | 2021
    Azad AKM; Fatima S; Capraro A; Waters SA; Vafaee F, 2021, An Integrative Resource for Network-Based Investigation of COVID-19 Combinatorial Drug Repositioning and Mechanism of Action, , http://dx.doi.org/10.26434/chemrxiv-2021-tk6rt-v2
    Preprints | 2021
    Azad AKM; Fatima S; Capraro A; Waters SA; Vafaee F, 2021, An Integrative Resource for Network-Based Investigation of COVID-19 Combinatorial Drug Repositioning and Mechanism of Action, , http://dx.doi.org/10.33774/chemrxiv-2021-tk6rt-v2
    Preprints | 2021
    Safarchi A; Fatima S; Ayati Z; Vafaee F, 2021, An Update on Novel Approaches for Diagnosis and Treatment of SARS-CoV-2 Infection, http://dx.doi.org/10.31219/osf.io/xg6z5
    Conference Abstracts | 2021
    de St Groth BF; McGuire H; Kao S; McNeil C; Hersey P; Boyer M; Vafaee F; Choi C; Kwong C-TJ, 2021, 'Predictive immune signatures for cancer immunotherapy - From bench to bedside', in ASIA-PACIFIC JOURNAL OF CLINICAL ONCOLOGY, WILEY, Vol. 17, pp. 69 - 70, https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000693805000133&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=891bb5ab6ba270e68a29b250adbe88d1
    Conference Papers | 2020
    Alizadeh F; Jazayeriy H; Jazayeri O; Vafaee F, 2020, 'SMIA: a simple way for inference of admixed population ancestors', in 2020 10h International Conference on Computer and Knowledge Engineering, ICCKE 2020, pp. 540 - 543, http://dx.doi.org/10.1109/ICCKE50421.2020.9303686
    Preprints | 2020
    Azad AKM; Dinarvand M; Nematollahi A; Swift J; Lutze-Mann L; Vafaee F, 2020, A Comprehensive Integrated Drug Similarity Resource for In-Silico Drug Repositioning and Beyond, , http://dx.doi.org/10.26434/chemrxiv.12376505
    Preprints | 2020
    Azad AKM; Dinarvand M; Nematollahi A; Swift J; Lutze-Mann L; Vafaee F, 2020, A Comprehensive Integrated Drug Similarity Resource for In-Silico Drug Repositioning and Beyond, , http://dx.doi.org/10.26434/chemrxiv.12376505.v1
    Preprints | 2020
    Azad AKM; Fatima S; Vafaee F, 2020, An Integrative Resource for Network-Based Investigation of COVID-19 Combinatorial Drug Repositioning and Mechanism of Action, , http://dx.doi.org/10.26434/chemrxiv.13271096
    Preprints | 2020
    Batarseh AM; Vafaee F; Hosseini-Beheshti E; Chen A; Cohen A; Juillard A; Hunt NH; Mariani M; Mitchell T; Raymond Grau GE, 2020, Lipidome profiles of plasma microvesicles differ in experimental cerebral malaria, compared to malaria without neurological complications, , http://dx.doi.org/10.1101/2020.07.28.224170
    Preprints | 2020
    Koch F; Sutton G; Voineagu I; Vafaee F, 2020, Supervised Application of Internal Validation Measures to Benchmark Dimensionality Reduction Methods in scRNA-seq Data, http://dx.doi.org/10.1101/2020.10.29.361451
    Preprints | 2020
    Rashidi TH; Shahriari S; Azad AKM; Vafaee F, 2020, Real-time time-series modelling for prediction of COVID-19 spread and intervention assessment, , http://dx.doi.org/10.1101/2020.04.24.20078923
    Preprints | 2020
    Zandavi SM; Rashidi TH; Vafaee F, 2020, Forecasting the Spread of Covid-19 Under Control Scenarios Using LSTM and Dynamic Behavioral Models, http://dx.doi.org/10.48550/arxiv.2005.12270
    Conference Papers | 2019
    Colvin EK; Howell VM; Mok SC; Samimi G; Vafaee F, 2019, 'Abstract TMIM-067: EXPRESSION OF LNCRNAS IN OVARIAN CANCER-ASSOCIATED FIBROBLASTS IS ASSOCIATED WITH PATIENT SURVIVAL', in Clinical Cancer Research, American Association for Cancer Research (AACR), presented at Abstracts: 12th Biennial Ovarian Cancer Research Symposium; September 13-15, 2018; Seattle, Washington, http://dx.doi.org/10.1158/1557-3265.ovcasymp18-tmim-067
    Preprints | 2018
    Bayati M; Rabiee HR; Mehrbod M; Vafaee F; Ebrahimi D; Forrest A; Alinejad-Rokny H, 2018, CANCERSIGN: a user-friendly and robust tool for identification and classification of mutational signatures and patterns in cancer genomes, http://dx.doi.org/10.1101/424960
    Conference Abstracts | 2018
    Colvin EK; Howell VM; Mok SC; Samimi G; Vafaee F, 2018, 'EXPRESSION OF LNCRNAS IN OVARIAN CANCER-ASSOCIATED FIBROBLASTS IS ASSOCIATED WITH PATIENT SURVIVAL', in CLINICAL CANCER RESEARCH, AMER ASSOC CANCER RESEARCH, WA, Seattle, Vol. 25, pp. 154 - 154, presented at 12th Rivkin-Centre Biennial Ovarian Cancer Research Symposium, WA, Seattle, 13 September 2018 - 15 September 2018, https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000497337700092&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=891bb5ab6ba270e68a29b250adbe88d1
    Preprints | 2018
    Ebrahimkhani S; Vafaee F; Hallal S; Wei H; Lee MYT; Young PE; Satgunaseelan L; Shivalingam B; Suter CM; Buckland ME; Kaufman KL, 2018, Deep sequencing of circulating exosomal microRNA allows non-invasive glioblastoma diagnosis, http://dx.doi.org/10.1101/342154
    Conference Papers | 2017
    Contaldi, C ; Vafaee F; Nelson, PC , 2017, 'The role of crossover operator in bayesian network structure learning performance: a comprehensive comparative study and new insights', ACM New York, NY, USA ©2017, Berlin, Germany, pp. 769 - 776, presented at in GECCO 2017 - Proceedings of the 2017 Genetic and Evolutionary Computation Conference, Berlin, Germany, 15 July 2017 - 19 July 2017, http://dx.doi.org/10.1145/3071178.3071240
    Conference Papers | 2017
    Ebrahimkhani S; Vafaee F; Barnett MH; Suter CM; Buckland ME, 2017, 'Exosomal microRNA signatures in multiple sclerosis reflect disease status', in MULTIPLE SCLEROSIS JOURNAL, SAGE PUBLICATIONS LTD, AUSTRALIA, MS Res Australia, Sydney, pp. NP17 - NP17, presented at Progress in MS Research Conference, AUSTRALIA, MS Res Australia, Sydney, 11 October 2017 - 13 October 2017, https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000414783200046&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=891bb5ab6ba270e68a29b250adbe88d1
    Conference Abstracts | 2015
    Colvin EK; Vafaee F; Mok SC; Howell VM; Samimi G, 2015, 'Differential expression of long non-coding RNAs in ovarian cancer-associated fibroblasts versus normal ovarian fibroblasts', in CANCER RESEARCH, AMER ASSOC CANCER RESEARCH, PA, Philadelphia, Vol. 75, presented at 106th Annual Meeting of the American-Association-for-Cancer-Research (AACR), PA, Philadelphia, 18 April 2015 - 22 April 2015, http://dx.doi.org/10.1158/1538-7445.AM2015-2885
    Conference Papers | 2015
    Domanova W; Krycer JR; Chaudhuri R; Yang P; Vafaee F; Fazakerley DJ; Humphrey SJ; James DE; Kuncic Z, 2015, 'Unravelling signal coordination from large scale phosphorylation kinetic data', in BMC BIOINFORMATICS, BIOMED CENTRAL LTD, IRELAND, Dublin, pp. 208 - 209, presented at 11th ISCB-Student-Council Symposium held in conjunction with the Intelligent Systems for Molecular Biology (ISMB) Conference / European Conference on Computational Biology (ECCB), IRELAND, Dublin, 10 July 2015, https://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000371886800009&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=891bb5ab6ba270e68a29b250adbe88d1
    Conference Papers | 2015
    Parker NR; Hudson AL; Khong P; Parkinson JF; Ikin R; Cheng ZJ; Vafaee F; Wheeler HR; Howell VM, 2015, 'Intratumoral heterogeneity of DNA repair pathways in glioblastoma', in CANCER RESEARCH, AMER ASSOC CANCER RESEARCH, DC, Washington, presented at AACR Special Conference on Advances in Brain Cancer Research, DC, Washington, 27 May 2015 - 30 May 2015, http://dx.doi.org/10.1158/1538-7445.BRAIN15-B39
    Conference Papers | 2014
    Vafaee F; Turán G; Nelson PC; Berger-Wolf TY, 2014, 'Among-site rate variation: Adaptation of genetic algorithm mutation rates at each single site', in GECCO 2014 - Proceedings of the 2014 Genetic and Evolutionary Computation Conference, pp. 863 - 870, http://dx.doi.org/10.1145/2576768.2598216
    Conference Papers | 2014
    Vafaee F; Turán G; Nelson PC; Berger-Wolf TY, 2014, 'Balancing the exploration and exploitation in an adaptive diversity guided genetic algorithm', in Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014, pp. 2570 - 2577, http://dx.doi.org/10.1109/CEC.2014.6900257
    Conference Papers | 2014
    Vafaee F, 2014, 'Learning the structure of large-scale Bayesian Networks using genetic algorithm', in GECCO 2014 - Proceedings of the 2014 Genetic and Evolutionary Computation Conference, pp. 855 - 862, http://dx.doi.org/10.1145/2576768.2598223
    Conference Papers | 2010
    Vafaee F; Nelson PC, 2010, 'An explorative and exploitative mutation scheme', in 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010, http://dx.doi.org/10.1109/CEC.2010.5586142
    Conference Papers | 2010
    Vafaee F; Turán G; Nelson PC, 2010, 'Optimizing genetic operator rates using a Markov chain model of Genetic Algorithms', in Proceedings of the 12th Annual Genetic and Evolutionary Computation Conference, GECCO '10, pp. 721 - 728, http://dx.doi.org/10.1145/1830483.1830613
    Conference Papers | 2009
    Vafaee F; Nelson PC, 2009, 'A genetic algorithm that incorporates an adaptive mutation based on an evolutionary model', in 8th International Conference on Machine Learning and Applications, ICMLA 2009, pp. 101 - 107, http://dx.doi.org/10.1109/ICMLA.2009.101
    Conference Papers | 2009
    Vafaee F; Nelson PC, 2009, 'Self-adaptation of genetic operator probabilities using differential evolution', in SASO 2009 - 3rd IEEE International Conference on Self-Adaptive and Self-Organizing Systems, pp. 274 - 275, http://dx.doi.org/10.1109/SASO.2009.13
    Conference Papers | 2009
    Xu B; Vafaee F; Wolfson O, 2009, 'In-network query processing in mobile P2P databases', in GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems, pp. 207 - 216, http://dx.doi.org/10.1145/1653771.1653802
    Conference Papers | 2008
    Vafaee F; Xiao W; Nelson PC; Zhou C, 2008, 'Adaptively evolving probabilities of genetic operators', in Proceedings - 7th International Conference on Machine Learning and Applications, ICMLA 2008, pp. 292 - 299, http://dx.doi.org/10.1109/ICMLA.2008.45

My research has attracted a total value of $12.3M (unapportioned) in research and industry-based competitive funding schemes as Chief Investigator and $1.1M as Associate Investigator (NHMRC Ideas, APP2012848). These include Category 1 grants in which I play major leadership roles (listed below). I have also led or contributed to securing > $400K from 8 UNSW seed funding schemes (2019 – 2022), not detailed here.

  • ARC Discovery (by Jai & Vafaee), DP220101938 (2022 – 2024, $575K, CIB), Role: Chief Investigator, Machine Learning and Bioinformatics Lead. Determining how small RNA sequences and structure defines function in bacteria. I lead the machine learning and system biology analyses of the study.
  • Next-Generation Graduate Program, CSIRO/Data61 (2023 – 2026, $1.7M, CIA), Role: Lead CI; leading a multidisciplinary team of 19 Investigators across 3 universities (UNSW, UTS, MQU) and 6 Industries (Metasense GenieUs, 23Strands, Trajan, Evidentli, Surround) to train a cohort of HDRs in AI-integrated BioMed technologies.
  • MRFF EPCDR Improving Diagnosis in Cancers with Low Survival Rates, APP2008996 (2021 – 2024, $4M, CIC), Role: Chief Investigator, Artificial Intelligence and Bioinformatics Lead; I am the main contributor to this multi-state, multi-institute interdisciplinary project and receive support for a postdoc and RA salary for four years. Title: Microbial-based biomarkers powered by AI for early detection of liver cancer in Australia.
  • MRFF Mental Health Pharmacogenomics, APP1200000 (2020 – 2023, $2.95M, CIJ). Role: Chief Investigator, Artificial Intelligence Lead; I lead the development of an AI model integrating clinical, pharmacogenomics, and neuroimaging data. Title: An Australian Multicentre Double-Blinded Randomised Controlled Trial of Genotype-guided versus Standard Psychotropic Therapy in Moderately-to-Severely Depressed Patients.
  • NHMRC Development Grant, APP2014538 (2020 – 2024, $564K, CIE). Role: Chief Investigator, Bioinformatics Lead; Title: Developing a novel blood test that accurately predicts response to checkpoint therapy.
  • Cooperative Research Centres Project, CRCPSIX000222 (2019 – 2022, $2.15M). Role: Chief Investigator, Artificial Intelligence Lead. Title: Smart Sensor and Deep Learning Behavioural Engine for Personalised Health Monitoring. This CRC-P project is in collaboration with Nutromics Pty Ltd and has a major AI component that I lead, i.e., developing models to predict an individual’s next dietary-relevant action and postprandial glucose level.
  • Mark Hughes Foundation Brain Cancer Innovation Project Grant, HMRI1151 (2019 – 2021, $150K; CIA), Role: Lead Investigator. Title: Combining artificial intelligence and genomics to non-invasively monitor glioblastoma patients and predict tumour recurrence. This project was in collaboration with UToronto, Canada.  
  • Vertex Innovation Fund (2018 – 2020, 157K Euro, equivalent to $250 AUD), Role: Key Investigator and Bioinformatics Lead. Title: Exosomal Biomarkers for Early Prediction of Cystic Fibrosis Related Diabetes

  • 2021. Women in AI Australia and New Zealand Award Finalist: WAI recognises the most innovative women across the Australian and New Zealand AI communities. I was selected as one of the 3 women in the AI in Health category.
  • 2021. UNSW Academic Women in Leadership Program in recognition of strong leadership contributions.
  • 2020. Georgina Sweet Award for Women in Quantitative Biomedical Science Finalist. I ranked among the top 8% in this nationally competitive award primarily targeted at mid-career women in quantitative biomedicine who made substantial research impact and leadership contributions.
  • 2019. UNSW Science Visiting Research Fellowship ($6K)
  • 2019. Featured by the UNSW Faculty of Science Capability Statement in Health Science and UNSW Capability Statement in Biomedical Research for outstanding research in biomedical data science.
  • 2009. Grace Hopper Celebration of Women in Computing Award ($1K), National Science Foundation, USA

My Research Supervision

  • Abir Kazaal (Primary Supervisor) co-supervision with Dr Emily Oates at the School of BABS, UNSW
  • Daniel Al Mouiee (Primary Supervisor) co-supervision with A/Prof Lois Holloway at Ingham Institute for Applied Medical Research
  • Fatemeh Safari (Primary Supervisor, Prospective) co-supervision with Dr Shafagh Waters at UNSW School of Biomedical Sciences
  • Mona Abedini  (Primary Supervisor, Prospective) co-supervision with Dr Hamid Rokny at UNSW School of Biomedical Engineering 
  • Daniel Martinez Formoso (Joint Supervisor) co-supervision with Dr Lindsay Wu at the School of Medical Science, UNSW
  • Jack Clarke (Secondary Supervisor) co-supervision with Dr Emily Wong at the School of BABS, UNSW