Yuxiang Bao, Natural Language Processing (NLP) Developer in Medford, MA, United States
Yuxiang Bao

Natural Language Processing (NLP) Developer in Medford, MA, United States

Member since August 28, 2019
Having studied advanced machine learning (ML) theory for the past three years, it’s safe to say Yuxiang knows ML quite well and he's delivered multiple projects using cutting-edge ML algorithms and tools. While at school, he also spent two years researching NLP. With a solid knowledge base in ML and NLP, hands-on experience, and exemplary communication skills—both written and verbal—Yuxiang will add value to your project.
Yuxiang is now available for hire




Medford, MA, United States



Preferred Environment

Jupyter Notebook, GitHub, Git, Windows, Linux

The most amazing...

...project I've worked on was a sentiment analysis system which featured extraction on both semantic and syntax information and aspect relationships.


  • Machine Learning Engineer

    2018 - 2018
    • Built a crawler that collected the labels of a given phone number from a search engine's semi-open database. It processed millions of call detail records from tens of thousands of applicants for a subprime loan using Pandas.
    • Manually selected features and classifiers with different imbalance dataset handle tricks to build a risk classification system and achieved 72% precision.
    • Proposed an info-flow model based on a call detail record.
    • Applied a model on a random-walk-based graphic neural network implemented by TensorFlow and Keras which is faster than a DNN approach based on the Tucker decomposition and achieved similar metrics, including a 76% F1-score and with 78% precision.
    Technologies: Scikit-learn, Keras, Selenium, Spark, TensorFlow, Python
  • Research Assistant

    2015 - 2017
    Tsinghua University
    • Collected reviews using Selenium from Amazon and applied a feature-extraction algorithm to find sentiment words and corresponding aspect words.
    • Transformed raw reviews into VSM and built a binary sentiment analysis system and achieved 88% accuracy.
    • Collected FAQs from an eCommerce website using Python.
    • Extracted the subject, predicate, and object from the questions and answers.
    • Built an automatic question-answering system based on similarity and applied it to an iBen robot.
    Technologies: Natural Language Processing (NLP)


  • Sentiment Analysis System

    I used BERT and Kindle reviews to build a classifier to distinguish incoming text into categories: positive, mixed, and negative. I also modified the BERT model by changing the loss function to focal loss to fit the imbalance of the dataset and achieved a 75% macro F1-score.


  • Languages

    Python 3, Java, JavaScript, Python, C++, Scala, SQL
  • Libraries/APIs

    TensorFlow, Keras, Scikit-learn, React, PyTorch, Node.js, Stanford NLP
  • Other

    Natural Language Processing (NLP), Machine Learning
  • Frameworks

    Express.js, Hadoop, Spark, Selenium, Angular, Django, Flask, Spring Boot
  • Tools

    Amazon EBS, Git, GitHub
  • Platforms

    Linux, Android, Jupyter Notebook, Windows
  • Storage

    MySQL, MongoDB, Apache Hive


  • Master's Degree in Computer Science
    2017 - 2019
    Worcester Polytechnic Institute - Worcester, MA, USA
  • Bachelor's Degree in Computer Science
    2013 - 2017
    Beijing Institute of Technology - Beijing, China

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