Data Assistant

Location:

Posted:

September 11, 2014

Kuixi ZHU

Email: ******@********.***; Phone: 917-***-****

Personal Profile

Solid background in disciplines of machine learning, data mining and statistical inference.

Experienced in programming in data-driven tasks using Java/Python/R etc.

Enthusiasm in solving problems creatively and efficiently.

Quick learner, self-starter and team player, with humble personality.

Education

[9/2012-6/2014], Master Degree, Major in Biomedical Informatics, Columbia University (GPA: 3.57)

[9/2007-6/2012], Bachelor Degree, Major in Bioinformatics, Harbin Medical University, China. (GPA: 3.54)

(*Academic Honors during education: Honored Graduate; Dean’s List for 6 semesters)

Completed Courses (including but not limited):

Statistical Machine Learning A Java/Python/C++ Programming A

Statistical Modeling for Data Analysis B+ Data Structure A

Bayesian Statistics B+ Database Theory and Programming A

Time Series Analysis A Natural Language Processing A

Pattern Recognition A Computational Genomics A

Random Process A Biological Sequence Analysis A

Optimal Algorithm A Biological Network Analysis B

Work Experience

Research Assistant, at Columbia University in the City of New York. [3/2013 – 5/2014]

Worked as data analyst and programmer and had independently finished some projects including but not limited:

Natural Language Processing: Semantic Analysis of Twitter Data. I conducted free-text data preprocessing,

tokenization, feature selection and classification with scikit-learn and nltk packages in Python.

Network Analysis & Mathematical Modeling: Breast Cancer Specific Network Study. I revised Random Forest

algorithm to infer the gene network from large numerical gene expression data and developed a novel method to predict

risky genes by applying Random Walker with Restart (RWR) algorithm on biological network and improved the

computing efficiency by transforming the data structure of sparse matrixes.

Software development& Algorithm Design: Ontology based Clinical Decision Support System App. I conducted

information retrieval to obtain patients’ symptom related data from electronic health records and employed Symptom

Ontology (SO) to construct a metric quantifying the similarity between diseases. I also coded the Clinical Decision

Support System App which allows users to input symptoms and then return diagnosis results.

Technology Summary

Programming Languages: Java, Python, R, MySQL, Perl, C++

Mathematics: Machine Learning, Data Mining, Statistical Modeling

Bioinformatics: Biological Network Analysis, Computational Genomics

Others: Natural Language Processing, Clinical Informatics, High Throughput Data Analysis