Mingran Cao
Data Scientist @LabGenius Therapeutics
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WORK HISTORY
Data Scientist @LabGenius Therapeutics
Enabled data-driven target selection by integrating large-scale public RNA-seq and scRNA-seq datasets, assessing target fitness, co-expression patterns, and logical (AND/OR) relationships critical for therapeutic specificity.•Contributed to the design and optimization of next-generation T-cell engager assets that demonstrated significant tumour-reduction in in vivo models, supporting their advancement toward clinical trials.
EDUCATION
Hangzhou Foreign Languages School
High School Diploma
University of Cambridge
Undergraduate, Neuroscience
UCL
Doctor of Philosophy - PhD, Systems Neuroscience
ABOUT MINGRAN CAO
I am a researcher in drug discovery focused on applying machine learning to complex biological systems, with an emphasis on translating computational insights into therapeutic design. Currently, I am a Data Scientist in the Machine Learning team at LabGenius, where I work on Bayesian optimisation and AI-driven approaches to improve the design of next-generation immunology therapeutics, including T cell engagers (TCEs) and antibody–drug conjugates (ADCs). My work contributes to scaling experimental design and increasing the efficiency of biologics discovery pipelines. Previously, I was Data Science Lead at Conduit Bio, an AI-native biotech startup focused on target discovery using knowledge graphs and computational biology. I joined in April 2023 and was promoted to Lead within three months, where I helped shape the company’s data science strategy and early technical direction. I recently completed my PhD in Systems Neuroscience at University College London, based at the Francis Crick Institute. My research combined computational and experimental approaches to study innate behaviour. I have published in leading venues including Nature, Science, and NeurIPS, and was supported by competitive fellowships such as the Boehringer Ingelheim Fonds PhD Fellowship.My core competencies include machine learning, data analysis, and PyTorch. I am particularly interested in applying computational methods to complex biological systems, especially those related to the brain and immune system.
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