I am a computer scientist and bioinformatician working at the intersection of frontier AI and global health. My research develops algorithms and machine learning methods that turn complex genomic data into reliable, real-world tools for detecting pathogens, tracking outbreaks, and supporting public health decisions, and, increasingly, for making biological data usable by AI agents without sacrificing accuracy in high-stakes settings like outbreak response.
Over the course of my PhD I have worked across the full pipeline of computational pathogen surveillance, from low-level sequence algorithms to deployed public-health tools and, most recently, AI-agent infrastructure:
- Real-time sequence analysis : I developed and implemented an efficient indexing and alignment algorithm that can align and analyse sequences as they are being sequenced (project details).
- Deep learning for pathogen detection : I curated a fungi-hosts database and used ResNets to detect fungal pathogenic potential from short DNA samples (published paper, project details).
- Genomic surveillance at scale : I led the development of MpoxRadar, a worldwide MPXV genomic surveillance dashboard (published in Nucleic Acids Research), and have worked on modelling and predicting the spread of emerging diseases and their mutations, including spatio-temporal population-immunity methods presented at ICLR, ISMB/ECCB, and GLBIO (pre-print, project details).
- AI agents for science : Most recently, I was first author on gget virus, a deterministic retrieval layer that lets AI agents reliably access global viral sequence data, featured on Anthropic's science blog (pre-print).
This work has been shaped by international collaboration and a strong applied streak: a visiting-scientist project with the Sabeti Lab at the Broad Institute of MIT and Harvard, a research stay at IFAP in Brazil, a multi-institution early-warning-system project (DAKI-FWS) with partners including Fraunhofer HHI and the Robert Koch Institute, and several award-winning hackathon and datathon projects across Europe, most recently as a finalist at the 2026 AI×Bio Hackathon in Berlin. Alongside research, I founded Code Curious, a non-profit that has introduced over 1,600 people from underrepresented groups to programming. I enjoy not only building these tools but communicating their value; across teams, borders, and audiences.
Keywords:
Machine Learning, AI Agents for Science, Genomic Surveillance, Viral Sequence Retrieval, Epidemiology, Pathogenicity Prediction
