I am a seasoned bioinformatics scientist with more than 10 years of research experience and 25+ peer-reviewed publications. My work bridges high-throughput multi-omics (RNA-seq, proteomics, metabolomics) with machine learning and predictive modelling, with the goal of enhancing secondary metabolism and resilient trait development in crops, most recently within Rosa spp. In my role on a large scale, I have designed reproducible, efficient pipelines (using Python, R, Conda workflows, SLURM) for automated data processing, meta-analysis, and integrative modelling of thousands of omics datasets. I turn complex biological data into actionable insights for agronomic decision-making. As a consultant, I help agribusinesses and research programs apply data-driven, AI-enabled strategies to optimize crop quality, productivity, and sustainability. I translate systems-level bioinformatics into agronomic value, enabling smarter, more resilient crops and supply chains. At AgriWorldX, I bring not only advanced computational expertise but also a deep understanding of sustainable agriculture and innovation. I aim to partner with forward-thinking agrifood organizations to drive the transition towards intelligent, resilient, and environmentally responsible farming systems.