Dr. Felicity Allen
Associate Director, Data Science and Machine Learning
Felicity is a leading data science practitioner with 20 years of experience developing machine learning methods for biotech industry and academia. She manages the computational group at ExEd, leading the development of Genetic Syntax Engine and related data science activities.
Bio
Felicity is a seasoned computational engineer with extensive experience across industry and academia. She obtained a Masters in Biomedical Engineering from Australia, and a PhD in Computing Science from Canada, focusing on machine learning for protein sequence and small molecule measurements. During her 1851 Postdoctoral Fellowship at the Wellcome Sanger Institute, she developed Bayesian models for CRISPR/Cas screens, and predictive methods for CRISPR/Cas9-induced mutations. This influential latter work was published in Nature Biotechnology. Before her role at ExpressionEdits, Felicity also held industry positions in analysing sequential data from cochlear implants as an engineer, and in integrative analysis of -omics datasets to identify drug targets as a Principal Scientist at Genomics Plc.
Felicity is a leading data science practitioner with 20 years of experience developing machine learning methods for biotech industry and academia. She manages the computational group at ExEd, leading the development of Genetic Syntax Engine and related data science activities.
Bio
Felicity is a seasoned computational engineer with extensive experience across industry and academia. She obtained a Masters in Biomedical Engineering from Australia, and a PhD in Computing Science from Canada, focusing on machine learning for protein sequence and small molecule measurements. During her 1851 Postdoctoral Fellowship at the Wellcome Sanger Institute, she developed Bayesian models for CRISPR/Cas screens, and predictive methods for CRISPR/Cas9-induced mutations. This influential latter work was published in Nature Biotechnology. Before her role at ExpressionEdits, Felicity also held industry positions in analysing sequential data from cochlear implants as an engineer, and in integrative analysis of -omics datasets to identify drug targets as a Principal Scientist at Genomics Plc.
Felicity is a leading data science practitioner with 20 years of experience developing machine learning methods for biotech industry and academia. She manages the computational group at ExEd, leading the development of Genetic Syntax Engine and related data science activities.
Bio
Felicity is a seasoned computational engineer with extensive experience across industry and academia. She obtained a Masters in Biomedical Engineering from Australia, and a PhD in Computing Science from Canada, focusing on machine learning for protein sequence and small molecule measurements. During her 1851 Postdoctoral Fellowship at the Wellcome Sanger Institute, she developed Bayesian models for CRISPR/Cas screens, and predictive methods for CRISPR/Cas9-induced mutations. This influential latter work was published in Nature Biotechnology. Before her role at ExpressionEdits, Felicity also held industry positions in analysing sequential data from cochlear implants as an engineer, and in integrative analysis of -omics datasets to identify drug targets as a Principal Scientist at Genomics Plc.
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