About us

Co-founder & CEO

Cecy has a degree in Biological Sciences from Oxford University and an MSc in ML from Imperial College London, specialising in graph-based biological modelling. At Biographica, Cecy leads strategy and business development, leveraging prior experience in drug manufacturing and supply chain at GSK as well as market access strategy consulting for gene-editing technologies.

Co-founder & CTO

Dom holds Masters degrees in Maths and Stem Cell Biology, as well as a PhD in Computational Genomics, from Cambridge. In his PhD, and later as an ML researcher at Relation Therapeutics, Dom applied graph ML to target discovery. He leads platform development at Biographica, drawing inspiration from drug discovery to design efficient target discovery methods for crop gene-editing.

Lead Data Engineer

Dennis has an MSc in bioinformatics from TU Munich and 7+ years experience as a data engineer in biotech startups. At BenevolentAI, Dennis led a team integrating large bioinformatics datasets to support drug target discovery and portfolio suitability prediction. At Biographica, he draws on this experience to develop robust and scalable data infrastructure for our platform.

Principal Bioinformatician

Felix completed a PhD at Oxford in Interdisciplinary Bioscience and his Bachelors at the Technical University of Munich in Molecular Biotechnology. Before joining Biographica, he has experience working as a Research Scientist, Bioinformatician and Computational Biologist, developing automated and high-throughput protein complex prediction workflows.

Fractional General Counsel

Laura Westby is an experienced general counsel with a strong background in IP, strategic business advisory, and legal operations across multiple industries. Laura previously spent over 15 years at Syngenta, culminating as Associate General Counsel for Crop Protection. She holds a B.A. in Classics, Psychology, and Political Science from Gustavus Adolphus College and a J.D. from Mitchell-Hamline School of Law. At Biographica, she supports the company with legal strategy, IP protection, and operational guidance.

Computational Biologist

Vicky completed her PhD at Cambridge in Metabolic and Cardiovascular Disease and her Masters at Imperial in Biomedical Research. Before joining Biographica, she spent three years as a Post-Doc Research Fellow, integrating multi-omics datasets and machine learning methods to study molecular mechanisms of drug toxicity for early drug discovery. At Biographica, Vicky develops multi-omics and statistical genetics methods for target discovery and prioritisation.

Plant Scientist

Naama is a molecular biologist with a PhD specializing in cancer genetics, and a post doc in plant genetics. In previous roles, Naama spearheaded projects that incorporate genetic engineering, high-throughput sequencing, and computational tools to advance developmental research in plant genetics. Naama’s work has involved developing protocols across several model species to investigate plant development and organ regeneration.

Head of Operations

Liz joined Biographica from early-stage VC fund Kindred Capital, where she supported a portfolio of 60+ startups with strategic advice, access to networks, and founder-focused programs. With prior experience as a startup operator, she brings operational and strategic expertise in scaling early ventures. Liz holds a BA in Economics from the University of Virginia and an MBA from Cass Business School. At Biographica, she oversees operations, finance, and people, and helps drive company-wide strategy and execution.

Machine Learning Engineer

Jacob holds a Master’s degree and a PhD in Computer Science and Machine Learning at the University of Cambridge. His research focused on building dynamical models of genetic regulation using data from high-throughput sequencing protocols. Before Biographica, he worked as a machine learning contractor developing methods from evaluating combinatorial CRISPR gene-editing libraries to building antibiotic discovery pipelines using protein language models.

Data Engineer

Gabrielle studied Biochemistry at Imperial College London and holds an Masters in Health Data Science from University College London, where she focused on natural language processing in pathology. She previously worked at MSK.ai, building a healthcare analytics data platform in the musculoskeletal space. At Biographica, she develops robust pipelines to advance our data ecosystem for ML-driven discovery.

Operations Manager

Daria holds a BSc in Neuroscience from the University of Southampton and is an MSc in Bioscience Entrepreneurship from UCL. She previously worked as a Founder’s Associate at an early-stage healthcare startup, where she supported operations and prior to that, she worked at Johnson & Johnson. At Biographica, she manages core business operations supporting company-wide efficiency and execution.

Senior Experimental Scientist

Daai is a plant molecular biologist with extensive experience in plant molecular biology and genetics. She acquired her PhD in Biological Sciences from the University of Wollongong, Australia. As a postdoc at the Commonwealth Scientific and Industrial Research Organization (CSIRO) in Australia, she focused on improving gene silencing stability and efficiency in plants. Before joining Biographica, Daai did research on novel oxygen-sensing mechanisms in plants at the University of Oxford. At Biographica, the focus of her work is on validating plant gene cis-regulatory elements predicted using ML-based approaches.

Principal Experimental Scientist

Vladimir is a plant molecular biologist. He completed his PhD in Biological Sciences at the University of Cambridge. As a postdoctoral researcher at the Sainsbury Laboratory in Norwich, UK, he worked on the molecular mechanisms of plant disease resistance and, later, on genome editing technology and its applications in plants. Prior to joining Biographica, Vladimir led the Crop Transformation and Genome Editing Unit at Rothamsted Research. At Biographica, he leads the Experimental Biology team, focused on the validation of plant gene targets predicted using ML-based methods.