Dennis Wang helms SICS’ Bioinformatics platform, which integrates expertise in computer science with biology and mathematics to support analytics with large and/or multi-dimensional data. Additionally, he holds the Academy of Medical Sciences Professorship (Chair in Data Science) at Imperial College London.
Wang’s research focuses on translating patterns in the human genome into actionable information that accelerates the development of treatments for complex diseases. Specialising in big data analysis, drug development (small molecules and biologics), algorithmic development, software design, web service development, genomic profiling, and statistical inference, his experience includes applying machine learning and statistical approaches to identify patterns from large genomic data sets and providing clinically actionable biomarkers to drug development teams.
Having worked in both academia and industry, Wang enjoys mentoring junior bioinformaticians and clinicians wanting to apply genomics to patient care and marrying research and teaching to promote data driven approaches for personalising medicines. Among his most significant projects are a crowd-sourcing machine learning challenge to predict drug combinations involving partners from pharma and technology industries; improving whole genome sequencing methods for the diagnosis of complex diseases, such as dementia, motor neurone disease and COVID-19; and developing computational methods for integrating omics data from patients to advance precision medicine for treating lung cancer and pulmonary hypertension.
He has received numerous awards, including the EPSRC Healthcare Technologies grant in 2021, the Rosetrees Seedcorn Award and Academy of Medical Sciences Springboard Award in 2019, the MRC Proximity to Discovery Award in 2017, and the AstraZeneca Innovative Medicines Award in 2016.
Wang obtained his Bachelor of Science in Computer Science, Microbiology and Immunology from The University of British Columbia, and both his Master of Philosophy in Computational Biology and PhD in Biostatistics from the University of Cambridge.
Find out more about him here.
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