My research centers around precision diagnostics of fungal pathogens using various PCR techniques, metabarcoding, and metagenomics. During my Master’s degree at University of Debrecen (Hungary) I worked on oenological studies leading to the identification and strain selection of economically important wine yeasts from Hungary. This project with industry academia partnership culminated in the selection of region specific, fit-for-purpose yeast strains. Further, during my doctoral research University of Debrecen, I studied molecular taxonomy and sequence-based species/strain of plant pathogenic fungi in combination with traditional phenotypic identifications. I planned and conducted in vivo and in vitro experiments for studying wide range of plant diseases and physiology. designed and conducted complex research projects in genetics, phylogenetics, molecular taxonomy, biotechnology, microbiology, biocontrol studies. As a postdoctoral fellow at the Westmead Institute for Medical Research Institute, I worked on the identification of human and animal pathogenic fungi. I led and coordinated an international consortium of mycological laboratories to generate high quality DNA barcodes leading to the establishment of the first quality-controlled dual DNA barcode database for clinically relevant fungi. This ever-growing database created a paradigm shift in mycological diagnosis, from inaccurate and time-consuming morphological/biochemical identification to an objective sequence-based identification, drastically reducing turnaround time to < 48h (the critical clinical cut-off point for successful initiations of targeted antifungal therapy). This database is now widely utilized by scientists and clinicians in 131 countries. As Senior Research Fellow, my research focused on the adaptation and incorporation of new sequencing technologies for routine diagnosis of fungal pathogens. I pioneered the Nanopore sequencing based fungal identification in clinical setting in Australia. I assessed the ability of unbiased, genome-wide, long-read, metagenomics sequencing using the first portable, real-time sequencing machine to identify human fungal pathogens directly from respiratory tract specimens and to characterize the associated mycobiome. To this end, I successfully applied next generation sequencing-based metagenomics to describe fungal biodiversity both in the clinics and various environments. In 2021, I co-led a study to inferring species compositions of complex fungal communities from long- and short-read sequence data. Our unique study provided an in-depth comparative analysis of different sequencing technologies and bioinformatic pipelines as well as generated draft genome assemblies. As lecturer and research group leader at Curtin University, I led the Molecular Mycology Lab. I conducted research in the field of precision diagnostic, NGS, genomics, and big data to address the global rise of fungal infections. I established and standardised long-read sequencing protocols for clinical metagenomics. Recently, I conducted large-scale data mining using cloud computing in the largest sequence database to track down the origin and spread of emerging pathogens. My research demonstrated for the first time the untapped potential of big data available in public databases to answer questions about disease reservoirs, as well as the potential of this data to enable the prediction of disease outbreaks.