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I am a motivated graduate student with experience in scientific research and full-stack development. My area of expertise lies in data processing, modeling, management, and data mining algorithms. My passion is ensuring data security, particularly in communication for high-mobility applications like autonomous ground vehicles and autonomous aerial vehicles. I'm enthusiastic about using Blind Source Separation (BSS) and Machine Learning to pioneer advanced solutions for these unique challenges. My goal is to contribute to the advancement of secure communication systems, enabling a future where vehicular and aerial platforms excel.


Experiences

Graduate Teaching Assistant

Embry-Riddle Aeronautical University
Aug. 2023 - Present
  • Facilitated hands-on learning experiences for digital circuit lab, ensuring a safe and productive laboratory environment.
  • Continuously improved my ability to articulate complex concepts clearly and effectively, fostering my personal teaching growth while enhancing the learning experience for students.

Summer Researcher

Embry-Riddle Aeronautical University
May 2023 - Aug. 2023
  • Continued research on multi-agent system formation control with a focus on strategies for jamming areas.
  • Collaborated and interacted with research fellows from different fields to gain diverse perspectives on swarm robotics.
  • Preparing to publish my second conference paper at the IEEE Southeast Conference in April 2024, and my first journal paper at The Journal of Intelligent and Robotic Systems.

Summer Researcher

Embry-Riddle Aeronautical University
Jun. 2022 - Aug. 2022
  • Developed advanced skills in writing scientific papers and conducting research in the field of swarm robotics.
  • Gained hands-on programming experience with UAV simulations in MATLAB.
  • Publishing my first conference paper at the IEEE Southeast Conference in April 2023.

Publications

Published

  1. S. Peccoud, S. Xing, T. Yang and R. S. Stansbury, "Behavior-Based Communication-Aware Formation Control in Dynamic Multi-Agent Systems for Jamming Detection and Avoidance," SoutheastCon 2024, Atlanta, GA, USA, 2024, pp. 552-558, doi: 10.1109/SoutheastCon52093.2024.10500200.
  2. S. Xing, T. Yang, and H. Song, "Consensus-based Communication-aware Formation Control for a Dynamical Multi-agent System," SoutheastCon 2023, Orlando, FL, USA, 2023, pp. 60-67, doi: 10.1109/SoutheastCon51012.2023.10115199.

Preprint

  1. S. Xing, S. Peccoud, T. Yang, and R. Stansbury, "Robust Communication-Aware Jamming Detection and Avoidance for Distributed Multi-Agent Systems".
  2. R. Singh, I. Pellani, S. Peccoud, S. Xing, W. Reimer, Y. Liu, and etc,"Safety and Performance Assurance for Swarm UAV Operations: A Survey".

Projects

Swarm Squad: A simulation framework for multi-agent systems

  • Created a scalable multi-agent simulation framework with customizable behaviors.
  • Integrate various tools (such as SQLite and ZeroMQ) for metrics collection, and data visualizations.
  • Provided user support with a documentation and a portfolio website.

Robust Communication-Aware Jamming Detection and Avoidance

  • Implemented algorithms for swarm systems including particle swarm optimization (PSO) and path planning techniques.
  • Simulated swarm behaviors in 2D environments using Matlab.
  • Constructed robust swarm behaviors including jamming detection and avoidance for distributed multi-agent systems.

Behavior-based Communication-aware Formation Control

  • Engineered decentralized and distributed control algorithms resilient to jamming interference.
  • Modeled formations with diverse behaviors and parallelized their execution.
  • Evaluated the timing performance of our formation control strategies.

Wine Quality Modeling using Machine Learning

  • Developed machine learning models to predict the quality of wine based on its physicochemical properties.
  • Analyzed and visualized the relationships between different variables using ggplot2, dplyr, and caret libraries.
  • Implemented various regression models achieving over 80% accuracy in predicting wine quality.

Consensus-based Communication-aware Formation Control

  • Developed more effective UAV management and organizations.
  • Estimates the desired separation with acceptable accuracy among UAVs.
  • Ensure consensus between aircraft with optimal communication quality.