Data Assistant

SHIH-YIN (JENNIFER) CHEN

ac02l7@r.postjobfree.com

http://www.linkedin.com/in/jennifer-shih-yin-chen

San Francisco, CA 94118

PROFESSIONAL EXPERIENCE

ALBEADO, Santa Clara, CA Mar 2017 to Present

Data Science Intern

• Predicted probability of hospital readmission and patients’ length of stay to reduce the cost from readmission.

• Researched ECG signal prediction and alarm detection to identify the probability of cardiovascular events.

• Assisted hospitals in providing healthcare in a more time- and cost-efficient manner. UNIVERSITY OF SAN FRANCISCO, San Francisco, CA

Research Assistant Mar 2017 to May 2017

• Developed code to utilize deep learning to predict disease from EHR data.

• Assisted with paper publication on the results.

Graduate Teaching Assistant – Bioinformatics/ Health Data Analytics Aug 2016 to May 2017

• Delivered a range of teaching and assessment activities directed towards graduate students and offered additional resources to promote their academic success.

• Utilized in Python and R programming to analyze and predict data trends. NATIONAL TAIWAN UNIVERSITY, Taipei, Taiwan

Graduate Teaching Assistant – Statistics Sep 2013 to June 2015

• Planned and evaluated courses, preparing statistics recitation classes for 70-students on a weekly basis. Applied statistical methods with R and SAS software. Academic Consultant Sep 2012 to June 2013

• Provided statistics consulting services to students and conducted data analysis for several projects. EDUCATION

Master of Science in Health Informatics May 2017

UNIVERSITY OF SAN FRANCISCO (USF), San Francisco, CA GPA: 3.94/ 4.0

• Key Courses: Clinical Decision Support and Health Data Analytics, Semantic Organization of Health Information and Data Standards, Statistical Computing for Biomedical Data Analytics, Bioinformatics, Temporal Data Analysis

Master of Science in Biometry June 2015

NATIONAL TAIWAN UNIVERSITY, Taipei, Taiwan GPA: 3.76/ 4.0

• Key Courses: Mathematical Statistics, Nonparametric Models, Applied Multivariate Quantitative Methods, Survival Analysis, Clinical Trials, Statistical Methods for Biotechnology Products, Secondary Health Data – Application and Practice

Bachelor of Science in Agronomy, Minor in Economics June 2013 NATIONAL TAIWAN UNIVERSITY, Taipei, Taiwan GPA: 3.63/ 4.0

• Biological Statistics Division

• Key Courses: Calculus, Statistics, Regression Analysis, Statistical Methods of Advanced Biometrics, Experimental Design, Introduction to Applied Mathematics, Statistical Computation and Analysis SELECTED PROJECTS

Differential Gene Expression in Breast Cancer, USF Feb 2017 – May 2017

• Explored differential gene expression of immuno-genes using breast cancer patients’ samples from the Cancer Gene Atlas (TCGA) database.

• Separated patients by their estrogen receptors (ER) status and discovered significant expression differences between two groups (ER+ and ER-) of patients for several immuno-genes, such as IL12RB2 and IL1F5. SHIH-YIN (JENNIFER) CHEN ac02l7@r.postjobfree.com

Health and Demographic Data Analysis using Deep Learning Oct 2016 – Dec 2016 USF (in conjunction with Influence Health)

• Applied deep learning using TensorFlow to determine the likelihood of an individual’s disease propensity for thyroid disorders.

• Compared the results from deep learning models with other machine learning algorithms using sensitivity, specificity, and accuracy with scikit-learn library.

• Used lift as a point of comparison, our models outperformed the random forest classifiers by up to 36.63%. ECG Signal Analysis using Mimic II Database, USF Sep 2016 – Dec 2016

• Applied time series analysis on the ECG signal using ARIMA model and Fourier transformation to perform the spectral analysis on the temporal data.

• Conducted wavelet analysis and machine learning algorithms such as Naïve Bayes, random forest, support vector machine, and arterial neural networks.

• Successfully detected 96.9% of the false alarms on ventricular tachycardia, and was able to identify 89.6% of the true alarms.

Software Artificial Pancreas (SAP) June 2016 – Aug 2016 USF (in conjunction with UCSF)

• Conducted preliminary investigation into various approached of machine learning and artificial intelligence in order to create a software model of the pancreas.

• Used time analysis, neural network, and Bayesian model to predict the next blood glucose measurement given blood glucose data, insulin records and other medication administration records, dietary intake, as well as other medical histories such as demographics and comorbidities. Master’s Thesis: A Study on Application of the Scaled Average Equivalence Test to Statistical Evaluation of Genetically Modified Products, NTU Sep 2014 – June 2015

• Researched and developed an improvement on the method of the evaluation of genetically modified food based on the current statistical method used by the European Union. HONORS AND AFFILIATIONS

• Academic Research that Changes the World from Here (USF) Apr 2017

• Secretary, Health Informatics Professionals and Students Association (USF) Mar 2017

• SONHP International Graduate Scholarship (USF) Aug 2015

• Excellent Teaching Assistant Award (NTU) Feb 2015 Expertise:

Exploratory analysis, predictive modeling, machine learning, data mining, data visualization, time-series analysis

Skills:

Proficient with Python, R, SAS, SQL, Java, Groovy, Tableau, Weka

Experience with designing & developing data mining solutions. E.g. Naïve Bayes, random forest, support vector machine, deep learning, scikit-learn, pandas, matplotlib, TensorFlow

Certified SAS Base Programmer

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