Data Machine

Juan L. Kehoe, Ph.D.

Phone: 301-***-**** E-Mail: ***********@*****.*** or *****@****.***

Website: https://www.linkedin.com/in/juanluo001

Summary

A master student in the Department of Information Systems at University of Maryland, Baltimore County (UMBC) with Ph.D. degree in Biochemistry and Molecular Biology pursuing a career in data science. Specialties: data science, data mining, machine learning, data analytics, text analytics, data visualization, big data, big data analytics

Education

University of Maryland Baltimore County

M.S., Information System, 2014 – Expected May 2017 GPA: 3.72

China Agricultural University

Ph.D., Biochemistry and Molecular Biology, 2003 - 2008 China Agricultural University

B.A., Animal Science, 1999 - 2003

Technical Skills

Machine Learning: linear regression, logistic regression, random forest, decision tree (CART), support vector machine (SVM), Naïve Bayes, XGBoost

Programming Language: R, Python, SQL, PySpark, Java Software: Shiny, Amazon AWS EC2, Gephi, Tableau, Oracle iSQL*Plus Selected courses:

• UMBC: Database Management Systems, Social Media Application and Analytics, Healthcare Informatics, Enterprisewide Computing

• MOOC: Tackling the Challenges of Big Data, Data Science Specialization, The Analytics Edge, Introduction to Big Data with Apache Spark, Scalable Machine Learning

Projects

Kaggle competitions March 2015 – Present

• Joined teams or worked individually on Kaggle.com to solve real life data problems. 2

• Performed classification and regression analysis using random forest, decision tree, SVM, and XGBoost in R and Python.

• Highest ranking 14%.

• Projects website: https://www.kaggle.com/juan001 Database design for an online cellphone store September - December 2015

• Designed a database for an online cellphone store by using Oracle PL/SQL.

• Customers will be able to register, check the price and availability of phones, order phones and check the status of the orders using this system.

Fake review identification August - December 2015

• Joined Dr. Dongsong Zhang’s team in UMBC to identify fake online reviews.

• Worked with team members to get data from online review websites, such as dianping.com, using Scrapy in Python.

• Built prediction models by using decision tree (CART), random forest, support vector machine (SVM), Naïve Bayes methods in R.

JHU Data Science Hackathon September 2015

• Joined a team to build a Shiny app to predict the crowd in National Aquarium.

• Worked with team members to get data from Instagram, Yelp, Flickr and Facebook.

• Built a prediction model by using random forest in R.

• Implemented the prediction model in shiny app.

• Work managed and published on GitHub: https://github.com/Juan0001/crowdattraction Data Science Capstone July 2015 – August 2015

• Built a model to do text prediction in English and published the predictor model as a shiny application.

• N-gram and stupid backoff algorithms were used to build the text prediction model by using R.

• Used R presentation to brief introduce model building and the shiny app.

• R presentation: http://rpubs.com/Juan/WordPredictionApp

• Shiny app: https://juanluo.shinyapps.io/Word_Prediction_App Experiences

Postdoc at University of Maryland, College Park January 2009 – January 2013

• Research experiences: experiment design, sample collection, performing experiments, data analysis, troubleshooting

• Management experience: mentoring master and Ph.D. students, and junior post-docs

• Report and writing experience: presenting progresses and results, writing manuscripts for publications

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