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Data Analysis

New York, New York, United States
December 01, 2017

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Xiuyue (Caitlin) Wang

*** *********** *****, *** **, New York, NY 10027●718-***-****●


Columbia University, Fu Foundation School of Engineering and Applied Science September 2016 - December 2017

• Master of Science in Biomedical Engineering, Cumulative GPA: 3.88/4.0

• Relevant coursework: Biostatistics, Data Science Industry, Machine Learning, Numerical Methods, Biomedical Design Xi’an Jiaotong University, School of Life Science and Technology September 2012 - June 2016

• Bachelor of Science in Biomedical Engineering and Bachelor of Arts in Finance, Cumulative GPA: 3.6/4.0, Major GPA: 3.7/4/0

• Relevant Coursework: Bioinstrumentation, Medical image processing, Medical signal processing, Bioinformatics

• Scholarships: Siyuan Scholarship for Academic Excellence (2013, 2014) University of Cambridge, Lucy Cavendish College – Exchange Program August 2014 –September 2014

• Relevant coursework: Imaging and Signal Processing Seminar, Real Estate Analysis Professional Experience

HealthyBytes – New York, US June 2017- August 2017 Internship: Data Scientist

• Built several machine learning models to predict health insurance reimbursement rate for dietitians based on python and figured out what features of contribute more to higher paid rate. Gave dietitian appropriate advice when they choose contracting company.

• Visualized the relationship between reimbursement rate and diabetes rate and policy detail due to different states using pyplot and R

• Built a web page using angular JS to help easily searching whether certain diagnose code and procedure code are covered in one specific health plan.

Philips Healthcare China – Suzhou, China June 2015- July 2015 Internship: Medical Device Research Development

• Researched on configuration of Mainstream Imaging Device including CT, MRI and Ultrasound and the main imaging principle. Project Experience

Machine Learning in computer vision – Sign Language Recognition January 2017 - May 2017 Columbia university - New York, NY

• Image processing: Detected skin area and got the feature map into a binary array. Package include opencv and tensorflow in python

• Classification: Tried svm and logistic regression, svm showed better performance.

• Web app: Using google cloud platform building a web app to online detecting the gesture and show the results. Machine Learning in Brain-Computer Interface - Classifying Imagined Movement September 2016 - December 2016 Columbia university - New York, NY

• Feature expansion: Generated CSP (Common Spatial pattern) filter by maximizing the variance of left hand imagined movements and minimizing the variance of right hand imagined movements. Applied CSP to raw data in this way to get discriminative features

• Classifier Algorithm: Used LDA(linear discriminate analysis) classifier and LASSO regularization to get the weight and then tested. We got 75% accuracy rate.

Medical Device Design – (Op Medical) Parallel Tube Manipulator September 2016 - May 2017 Columbia university - New York, NY

• Designed a new medical device that combines intubation and suction for contaminated airway together, which could effectively reduce time and effort for ER and anesthesiologist. Prototype modeling based on CAD, 3D-printing and laser cut.

• Conducted market research and built business model. (Website for our design group Application of EEG signal- ALS Home Automation September 2014 - January 2015 Xian Jiaotong University - Xian, China

• Applied Neurosky eSence algorithm to transform EEG signals into attention values

• Used these attention values obtained from ALS patients to control switch of electronic devices based on C++. Skills

• Programming: Python, SQL, R, Hadoop, Spark, Javascript, Matlab, Java, Bash,

• Software: Google cloud, tensorflow, SPSS, E-Prime, Neuroscan, Microsoft Suite, git

• Concepts: Data analysis, Machine Learning, Data Modeling, Deep Learning, Data Visualization, Image Processing, Probability and Statistics, Biomedical consulting and investing strategy, Medical device design and innovation strategy, Signal processing

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