Qian Si

• Participated in a project, to develop data analysis methods which can be used in identifying biomarker candidates for early cancer detection. • Prepared detailed reports to convey complex subjects to seniors in group with a focus on implications and recommended actions. • Co-Created R package “rWMBAT” which builds a three level Bayesian Network mainly based on Naive Bayes classifier incorporate with classification modules, implements sampling techniques such as V-fold cross-validation,

of the KPIs (Key Performance Indicators), a range of analytical tools, and evolving assessment methods. • Responsible for recommending relevant best practice resources specific to each Guide's performance profile, identified and established scope and parameters of variables in order to define impact, outcome criteria, and measure-taking actions.

• Participated in Portfolio Analysis of Small Auto Business. • Investigated billing data and merged summarized billing data to Select Auto Modeling data set to check new attributes and build criteria for decision making. • Performed exploratory data analysis, focused on model preliminary analysis such as pivot table, model validation, univariate tab on potential use from new data resource. • Summarized findings into effective management reports. Interpreted results and gave updates to senior management.

Thesis： Enhancement of MS Signal Processing For Improved Cancer Biomarker Discovery Research was focused on developing statistical algorithms and creating data mining tools for computationally improved signal processing for mass spectrometry data.

Member of a Mass Spectra group composed of 7 people with different background. Responsible for the analysis of large-scale data to discover the intrinsic patterns: optimizing the data processing, transforming the raw data into a high quality representation.