Find a Data Champion

I work in cognitive neuroscience and neuroimaging, with a strong focus on research data management, reproducible analysis, and open science practices. Before training in cognitive neuroscience, I was educated in computer science and trained as a systems analyst, which continues to shape how I approach research data, workflows, and computational methods. In my current work, I focus on brain imaging data, including data organisation in BIDS (Brain Imaging Data Structure), preprocessing and analysis pipelines, and the development of practical training materials to support researchers in using modern computational tools and adopting good data practices.

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.