Computer Science Software Developer

Ruijie(Sherry) Xi

*** ******* ******, ********, ********** ********@****.*** 302-***-****

EDUCATION

University of Delaware Newark, DE

Master of Engineering 09/2015 - 05/2017

Major: Computer Science

GPA: 3.60

University of Harbin Institute of Technology

Bachelor of Engineering Harbin, China

Major: Computer Science 09/2011 - 07/2015

GPA: 3.80

Skills

Languages Java(proficient), J2EE, SQL, C++, C#

Web CSS, HTML, D3

Courses Computer Networking, NLP, Artificial intelligence, Algorithms, Bioinformatics, Compiler construction EXPERIENCE

Cloudamize

Software Developer Jun 2016 – July 2016

• Maintained companies’ information which using Cloudamize platform, gathered component description using SQL queries and migrated resources to the cloud by deep-learning and big data technologies.

• Participated in creating the technology platform that can automate cloud infrastructure data collection and analysis. Course Project

Stock Market QA System Sept 2016 – Oct 2016

• Produced a question answering system with technologies in Java, the system can read a file with more than 1000 questions and give answers about rate of a stock from articles.

• Libraries in Java like Stanford NER was used to label sequences of words in a text to extract features, and models were trained with Stanford POS tagger to reflect the underlying treebank that models have been built from.

• Implemented Lucene Apache query parser and analyzer for decomposing over 5000 query syntax and extracting index terms.

Letter Prediction in a Scanning-based AAC System Oct 2016 – Nov 2016

• Used Java to develop a scanning-based AAC system with 10-gram model and memorization to predict letters with users’ desire when typing.

• Improved more than 30% accuracy by using add-one smoothing method and extended the record at each time when one customer is using it to make the model dynamically. Sentiment Analysis Nov 2016 – Dec 2016

• Predicted if a review if positive or negative from more than 10,000 reviews of different social network.

• Imported data from Amazon Product Reviews, Twitter Posts, Movie Reviews with same core sentiment lexicons (positive and negative).

• Implemented sentiment analyze with Java to calculate the attribute values for each instance.

• Used classifiers like Logistic Regression, Naïve Bayes and LibSVM with Weka to generate sentiment prediction analysis.

• Changed lexicons, classifiers and dataset to improve the prediction accuracy up to 85%. Compiler Construction Sep 2016 – Dec 2016

• Wrote a compiler with Java called Meggy Java Compiler, and compiled it to the assembly language for the ATmega328p microcontroller in the Meggy Jr RGB devices.

• Used JLex and JavaCup tools for generating the lexer and parser, used abstract tree to build symbol table for type checking. Finally, the compiler can implement classes, variable, arrays, assignments and methods in a program. Malware Visualization Feb 2017 – May 2017

• Built a visualization analysis system for malware detection using D3.js to display all the malware features with different models, all the features were given in a file.

• Trained data from more than 11000 samples by Random Forest model, Decision Tree model, and Randomized Lasso model.

• Changed parameters in these models and improved about 10% in prediction accuracy.

• Generated random feature values and average values which are belong to different malware families to give users a gauge to tweak feature values.

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