Xingsi Zhong


I have four years of industrial working experience as a software engineer. My work involves cloud system design, implementation, and time-series data analysis. I developed an auto-scaling platform to support millions of users around the world. I have reviewed 14 papers, published 11 papers, and received more than 300 citations.


  • Languages: Proficient: Python, MySQL, InfluxQL; Prior experience: C++, C
  • Public Cloud: AWS, GCP, Aliyun
  • Libraries: boto3,, scapy, numpy, pandas, PyTorch
  • Software and Tools: Perforce, Git, Wireshark
  • Other Skills: Traffic Analysis, Time Series Analysis, Time Series Prediction, Machine Learning


    Senior Staff Software Engineer - Palo Alto Networks
    May 2020 - Present
  • Auto-Scale Platform - The new platform supports auto-scale service for multiple PA Mobile Device Services in more than 10k locations for more than 20m unique users. The platform offers flexible methods to adapt new scaling algorithms and schedules and can automatically resolve conflicts between different decision factors. The platform has been proven capable of handling usage explosion and tolerating system instabilities since 2020.
  • Usage Prediction - Designed and implemented an online prediction algorithm that automatically learns and predict usage pattern. The prediction guides auto-scale service in advance to better prepare for upcoming events.
  • IP Managment System - Designed and implemented an IP resource management system and an allow-list status feedback API. The system manages and pre-allocates IPs based on customer usage prediction and will only utilize the IPs that the customers have confirmed through the API.
  • Staff Engineer - Palo Alto Networks
    Nov 2018 - Apr 2020
  • Mobile Device Service Capacity Auto-Scale - Design and re-architectured the Global Protect Mobile Gateway auto-scale module. The new design reduced the communication and computation overhead and boosted the designed capacity by more than 1500 times. The new module successfully supported the dramatically increased load during the COVID-19 "work from home" transient period.
  • Instance Upgrade Workflow - Involved in designing and developing an orchestration workflow that performs upgrades to firewall instances.


    Ph.D. in Computer Engineering
    The Holcombe Department of Electrical and Computer Engineering, Clemson University, USA
    Graduated in Aug 2018
    M.S. in Computer Science
    Department of Computer Science, University of Texas-Pan American, USA
    Graduated in Aug 2013
    B.S. in Information and Computational Science
    College of Mathematics, Jilin University, China
    Graduated in June 2010

    FEATURED PUBLICATIONS(11 publications in total as of June 2018)

    Denial of service attack on tie-line bias control in a power system with pv plant
    X Zhong, I Jayawardene, GK Venayagamoorthy, R Brooks
    IEEE Transactions on Emerging Topics in Computational Intelligence
    Stealthy malware traffic-Not as innocent as it looks
    X Zhong, Y Fu, L Yu, R Brooks, GK Venayagamoorthy
    10th International Conference on Malicious and Unwanted Software
    Side-channels in electric power synchrophasor network data traffic
    X Zhong, P Arunagirinathan, A Ahmadi, R Brooks, GK Venayagamoorthy
    10th Annual Cyber and Information Security Research Conference