Shuojiang Liu

1st Year Master’s Student 👤, Georgia Institute of Technology 🏫

Email 📠:

Short Biography 📸

Shuojiang Liu is a first-year master’s student at Georgia Institute of Technology (Georgia Tech) with a major in computational science and engineering.

Before joining Georgia Tech, he obtained his Bachelor of Engineering (Honors Engineering Program) degree from Xi’an Jiaotong University (XJTU), majoring in automation at Qian Xuesen Honors College (administrative) and School of Automation Science and Engineering (professional).

From December 2022 to June 2023, he exchanged at School of Computing (SoC) from National University of Singapore (NUS).

He was born on July 2nd, 2001 in Xi’an, China. (See quick facts about Shuojiang Liu)

Education 🏛️

Selected Research and Project Experience 🔭

  • Research Intern, National University of Singapore (NUS), Singapore

    • December 2022 ~ June 2023
    • Supervisor: Yi-Chieh Lee
    • Collaborator: Chen-Ting Chang
    • Theme: Psychologically Empathetic Intelligent Chatbot Development and Human-Computer Interaction Interface Design
  • Research Intern, Chinese University of Hong Kong (CUHK), China

    • July 2022 ~ September 2022
    • Supervisor: Yu Li
    • Theme: Development of Protein Multiple Structure Information retrieval Tools Based on Protein Structure Representation Learning
  • Short-Time Research Intern, Xi’an Jiaotong University (XJTU), China

    • May 2022 ~ November 2022
    • Supervisor: Liangjun Ke
    • Theme: Reinforcement Learning for Decision Making
  • Intern, National University of Singapore (NUS), Singapore

    • May 2022 ~ August 2022
    • Supervisor: Leong Hon Wai and Ng Yen Kaow
    • Theme: Community Detection for Time Series Data about the COVID-19 Pandemic Based on Ultra-Large Scale Complex Networks: Modeling, Analysis, and Visualization
  • Short-Time Research Mentorship Program, Xi’an Jiaotong University (XJTU), China

    • October 2021 ~ May 2022
    • Supervisor: Hongbin Pei
    • Theme: Comprehensive Research on Transportation and Molecular Network Optimization Based on Graph Neural Networks

Research Interests 💡

Efficient Machine Learning Methods, High-Performance Computing, Graph Neural Networks, Digital Image Processing, Computational Biology, Conversational Agents, Natural Language Processing…

Skills 🖥️


Toolchains/Libraries: CMake, OpenGL, OpenMP, MPI, CUDA, Protobuf…

IDEs: JetBrains CLion, Visual Studio, Arm Keil µVision IDE, Renesas CubeSuite+…


Python Libraries/Packages: PyTorch, PyTorch-Geometric, OpenCV, Scikit-Learn, Scikit-Image, Pillow, DEAP, Matplotlib, NumPy, Pandas, NetworkX, BioPython, OpenAI-Gym, Stable Baseline 3, Flask, OpenPose, Rasa, HuggingFace Transformers…

Verilog HDL:

Toolkits: Xilinx Vivado ML, Modelsim…

MATLAB, LabVIEW, Multisim, Proteus, Altium Designer, Wireshark, Inventor, Linux System and Network Programming, Gephi