Seattle, Washington, United States
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About

TECHNICAL SKILLS
Currently working at Authentication Area: SAML, Oauth2.0, OpenID…

Activity

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Experience & Education

  • Tableau Software

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Courses

  • Cloud Computing

    15619

  • Distributed System

    95702

  • Java Smart Phone

    18641

  • Web Application

    15637

Projects

  • Input Text Predictor

    • Built input text predictor (top five most probable phrases) based on user input log analysis result
    • Utilized Hadoop MapReduce to generate N-Gram model from over 3GB text corpus
    • Designed and developed a schema in HBase to store the words appearing after phrases and their probabilities

  • Nano-Blogging Site

    • Built a Nano-Blogging site based on Django (Model-View-Controller framework) using python
    • Implemented user registration and authentication, email integration for user verification, asynchronous post, fuzzy search, photo upload and quasi-real-time updates using Twitter Bootstrap, Ajax, SQLite

  • Cloud Storage on AWS

    • Implemented and evaluated strong and eventual consistency models for a distributed key-value store
    • Explored the advantages and disadvantages of replicating over different geographical locations
    • Extended a distributed key-value store with sharding or replication schemes in real-world scenarios

  • Twitter Big Data Analytics

    • Established a whole front-end, web service and back-end framework for client query on AWS
    • Analyzed sentimental score and performed the text censoring of Twitter text using AWS Hadoop MapReduce
    • Deployed MySQL and HBase databases with a large data set(~1TB) to build a REST-based web service capable of handling a high load (~ tens of thousands of requests per second)

  • Finance Manager (Android Application)

    • Helped the user control income and expenses to potentialize the savings
    • Supported user to customize type of expenses, accounts
    • Implemented reporting mechanisms including saving the moment and GPS

  • Body Movement Detection Support Vector Machine

    • Two set of data were given and in each set of data includes bio-signal data and label, an SVM solver was implemented to maximize the classification margin
    • Newton Method, Interior point method and backtracking line search were implemented to achieve the SVM
    • For each set of data, this SVM can achieve an average accuracy of 95.4% and 87.5%

  • Resource Scaling using AWS and Azure

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    • Programmatically control resources (scale in or scale out) in respond to the demands on AWS and Azure.
    • Configured and deployed Load Balancer along with scale set on AWS and Azure.
    • Developed and implemented LRU based strategy for caching user query results
    • Implemented automatic machine failure recovery on cloud

Languages

  • Chinese

    Native or bilingual proficiency

  • English

    Professional working proficiency

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