Suyan Xu

My headshot

Hi! Suyan Xu here, I am an incoming Masters student at Carnegie Mellon University, majoring in Mobile and Internet of Things (IoT) Engineering, and I have obtained a bachelors degree in Compuer Science from The Hong Kong Polytechnic University.

I like taking coffee breaks and coding (obviously). This website is a mini personal portfolio that I've been developing using React.js and Next.js. So far it's mainly a blog but I envision it to be so much more.

More functionalities coming soon!

Also, if you know any 2021 summer internship opportunities, let me know!!

Some other facts!
  1. 1. software engineer
  2. 2. I like security too
  3. 3. vGHC 2020 INI scholar, "see" you there!
  4. 4. everything mint green, except my code editor, which is always dark
  5. 5. personality: INTP
  6.  That's introverted, intuitive, thinking, and prospecting

Bienvenue!

The more I study, the more insatiable do I feel my genius for it to be. - Ada Lovelace

Cover Image for Train Your First Model Using Azure Machine Learning Studio

Welcome to my tutorial/blog on training your first model using the Microsoft Azure Machine Learning Studio. We will be tackling the following questions:
1. What is the Microsoft Azure Machine Learning Studio?
2. How to create a workspace for Machine Learning Studio from Azure?
3. How to train a model in Machine Learning Studio?

Suyan Xu
Suyan Xu

More Stories

Cover Image for How to Host Your React Website: Beginners Full Tutorial

How to Host Your React Website: Beginners Full Tutorial

Hi, this summer I decided to build my own blog from scratch using React, and these series of tutorials will document the full process (while my blog framework is still under development). This is the first of a multi-series beginners tutorial and I hope you find it useful.

Suyan Xu
Suyan Xu

Work Experience

  • Jan. 2019 - Aug. 2019 | Hong Kong

    Deloitte China

    Risk Advisory Technology Risk Intern

    Conducted penetration tests, vulnerability assessments, and source code analysis using Kali Linux, in a team of four, on web-based applications from 3 financial institutions.
    Performed comprehensive Anti-Money Laundering (AML) data verification testing for a financial institution.
    Analyzed and summarized data protection and privacy regulations in the Asia-Pacific region.
    Researched in industrial cybersecurity solutions, and cloud computing regulatory compliance for 2 Hong Kong financial institutions and a major Chinese multinational conglomerate.

  • Jun. 2018 - Aug. 2018 | Sophia-Antipolis, France

    GridPocket

    Software Engineering Intern

    Developed a highly scalable Model-View-Controller (MVC) architecture mobile platform utilizing the React Native framework, in a team of three, to deliver value-added services.
    Implemented application UI components, feature controllers, and data stores using TypeScript.
    Deployed iOS and Android versions of the mobile application on Google Play and Apple Store, respectively.
    Configured the communication between an IoT device and the mobile application using RESTful APIs for data transfer and Wireshark for packet analyzing, to visualize household energy consumption in real-time.

  • Sep. 2018 - Jun. 2020 | Hong Kong

    Big Data-driven Airport Resource Management Engine and Application Tools

    Research Assistant at the Internet and Mobile Computing Laboratory

    Developed a web-based visualization system that enhances the airport's carousel utilization by 35%.
    Configured an Apache server with Flask as the back end web framework, due to its speed and exibility.
    Programmed the system front end using Vue.js, a lightweight and efficient JavaScript framework.
    Analyzed airport operational data using Python, to evaluate the performance of the visualization system.

  • Jun. 2019 - Jun. 2020 | Hong Kong

    Continuous Prediction of Flight Estimated Time of Arrival in Real-Time

    Capstone Project supervised by Chair Professor Jiannong Cao

    Performed data processing and data fusion on 1 million multi-source real-time data records from the airport.
    Designed and developed a novel multi-stage continuous flight Estimated Time of Arrival (ETA) prediction model, utilizing machine learning algorithms from open-source tools PyTorch and Scikit-learn. • Improved ETA mean absolute error by 47%, and increased ETA resolution up to 1 record per second.