Ms. Laifan Pei is a rising researcher in complex networks, hyperspectral image processing, and visibility graph-based texture analysis. Currently pursuing her Ph.D. at the China University of Geosciences (Wuhan), she has made significant contributions to unsupervised feature extraction, visibility-based image representation, and UAV path planning algorithms. Her interdisciplinary research spans computer vision, nonlinear time series, and multilayer network analysis. With multiple SCI- and EI-indexed publications, involvement in national research projects, and distinguished service as a peer reviewer and developer community author, she exemplifies research excellence in artificial intelligence and data-driven image science.

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Education 🎓📚

• Ph.D. in Computer Science (2022–Present)
  China University of Geosciences (Wuhan), China
  Focus: Hyperspectral image analysis, complex network theory, graph-based learning

• M.Eng. in Computer Science (2019–2022)
  Wuhan Textile University
  Courses: Big Data Processing, Advanced Software Engineering, Database Management

• B.Sc. in Computer Science (2015–2019)
  Wuhan Textile University

Professional Experience 🧑‍🏫💼

• Academic Reviewer
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024

• Outstanding Author
  Tencent Cloud Developer Community (TCDC), 2015–2025

• Committee Member & Paper Reviewer
  Hubei Society for Industrial and Applied Mathematics (HBSIAM), 2021

Laifan has participated in cutting-edge national projects funded by the National Natural Science Foundation of China (NSFC) and led institutional initiatives on visibility graph algorithms for image classification. She is proficient in Python and MATLAB with a strong command of both Windows and Linux environments for research deployment and data science applications.

Research Interest 🔬📈

• Visibility Graphs in Image and Texture Classification

• Hyperspectral Image Analysis & Feature Extraction

• Complex Network Models in Time Series & Epidemic Spread

• UAV Path Planning Algorithms (AI + Robotics)

• Multiview Graph Convolutional Networks

• Evolutionary Algorithms for Remote Sensing

Publications Top Noted

• Pei, L., Liu, J., Cai, Z.
  Unsupervised Feature Extraction for Hyperspectral Imagery using High-Order Networks
  Infrared Physics & Technology, 2025 – [SCI]

• Pei, L., Liu, J., Cai, Z.
  Complementary Horizontal Visibility Patches for Texture & RS Image Classification
  IWPR 2025, Elsevier – [EI]

• Pei, L., Liu, J., Cai, Z.
  From VG to CVG and ICVG: Algorithms and Applications
  AIP Advances, 2024 – [SCI]

• Pei, L., Li, Z., Liu, J.
  Texture Classification via Image (Natural & Horizontal) Visibility Graphs
  Chaos, 2021 – [SCI]

• Gong, J., Pei, L., Zhou, X., et al.
  UAV Swarm Round-Up via Adaptive Genetic Algorithm
  China Automation Congress (CAC), 2024 – [EI]

• Chen, S., Pei, L., Zhou, X., et al.
  Coverage Path Planning for UAVs with Dual-Stage GA
  CAC, 2024 – [EI]

• Li, Z., Pei, L., Liu, J., et al.
  Epidemic Spread on Multilayer Networks
  CCDC, 2021 – [EI]

Conclusion 🌟🎯

Ms. Laifan Pei is a highly deserving candidate for the Best Researcher Award in Computer Vision. Her technical contributions, academic service, and innovative focus on visibility graphs and remote sensing exemplify the qualities of a next-generation research leader in intelligent vision systems. With continued momentum in her Ph.D. and increasing academic influence, she is on track to become a prominent scholar in AI-driven image analysis.