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I provide Bioinformatic support for a few research groups in the Cambridge Stem Cell Institute. For the most part I deal with the analysis of single cell sequencing data, storage management of such data and the deployment of data processing pipelines into HPC environments.

I am a PhD student at the MRC Biostatistics Unit, interested in applying machine learning techniques to biological data. I have worked on classification of cancer (sub)types using XGBoost models. I am currently working on trying to uncover biological details about the immune system using graph data and graph machine learning.

Qi received her PhD at the University of California, Los Angeles, where she developed computational methods to study alternative splicing and the evolution of HIV. Later she joined the UCLA Division of Dermatology to help identify the resistance mechanisms of targeted cancer therapies using computational tools. 
    
In 2011 she was awarded the Humboldt Research Fellowship to work in the Division of Theoretical Bioinformatics, and later the Division of Applied Bioinformatics, at the German Cancer Research Centre. There she worked on diverse bioinformatics projects with NGS data, such as studying genome-wide epigenetic regulation of cell differentiation, developing sequencing protocols and detecting somatic mutations from whole-genome sequencing data, as well as data integration and predictive modelling. 
    
Currently, she provides bioinformatics training and support to PhD students and postdoctoral researchers in the lab of Professor Beverley Glover.