Laifan Pei | Computer Vision | Best Researcher Award

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Ms. Laifan Pei | Computer Vision | Best Researcher Award

Laifan Pei at China University of Geosciences, China.

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.

Professional Profile ,

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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.

Mr. Zushuang Liang | Salient Object Detection | Best Researcher Award

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Mr. Zushuang Liang | Salient Object Detection | Best Researcher Award

Mr. Zushuang Liang, Harbin Institute of Technology, China

Mr. Zushuang Liang is a graduate student at the Harbin Institute of Technology, specializing in Computer Vision with a focus on Salient Object Detection and Graph Neural Networks (GNNs). His innovative research, including the development of a multi-scale graph attention network for video detection, holds promising applications in areas such as autonomous driving and surveillance. Additionally, Mr. Liang explores interdisciplinary work by integrating machine learning with music technology through piano polyphonic transcription, showcasing his versatility and contribution to both fields.

Professional Profile:

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Suitability for the Best Researcher Award:

Mr. Liang’s work is not only technically innovative but also highly impactful. His contributions to video salient object detection with applications that extend to fields like autonomous driving, surveillance, and multimedia retrieval make him a deserving candidate for the Best Researcher Award. His interdisciplinary approach, combining machine learning with music technology, further distinguishes him as a forward-thinking researcher.

Educational Background:

He earned his Bachelor’s Degree from the Harbin Institute of Technology and is currently pursuing a Master’s degree at the same institution, within the School of Electronics and Information Engineering.

Area of Specialization:

Mr. Zushuang Liang specializes in Computer Vision with a focus on Salient Object Detection and Graph Neural Networks (GNNs). His work revolves around enhancing video detection accuracy by applying innovative techniques in multi-scale graph attention networks.

Research & Contributions:

His pioneering research includes developing the multi-scale graph attention network for video salient object detection, with potential applications in autonomous driving and surveillance. Additionally, he bridges disciplines by working on piano polyphonic transcription, integrating machine learning with music technology.

Publication Top Notes:

Title: DAFE-MSGAT: Dual-Attention Feature Extraction and Multi-Scale Graph Attention Network for Polyphonic Piano Transcription
  • Year: 2024

 

 

Mr. Saket Kumar Singh | Computer Vision | Best Researcher Award

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Mr. Saket Kumar Singh | Computer Vision | Best Researcher Award

Mr. Saket Kumar Singh, Birla Institute of Technology, Mesra, Ranchi, India

Saket Kumar Singh, born on October 21, 1993, is a Project Research Scientist currently working on an ICMR-funded project titled “Explainable AI for Hypoxic Ischemic Encephalopathy Detection using ultrasound images in Jharkhand Neonates: A Deep Learning Approach.” He is pursuing a Ph.D. in Computer Science and Engineering at BIT MESRA, Ranchi, focusing on implementing deep learning methods for the early diagnosis of chronic diseases. Singh has over seven years of experience as an Assistant Professor, teaching AI, Machine Learning, and Data Science at various esteemed institutions in India, including the National Institute of Advanced Manufacturing Technology, AKG Engineering College, IMS Engineering College, Kanpur Institute of Technology, and Subhash Institute of Software Technology. He holds an MTech in Computer Science from BIT MESRA, where he graduated with distinction, and a B.E. in Computer Science & Engineering from NRI Institute of Information Science & Tech., Bhopal. Saket is recognized for his technical, experimental, and interpersonal skills, making significant contributions to curriculum development, student mentoring, and organizing hackathons. He has a strong passion for technology and research, with numerous publications and project presentations to his name. Additionally, Saket has received several accolades in cultural and sports activities, showcasing his diverse talents and dedication to excellence.

🌐 Professional Profile:

 

ORCID

 

Academic Background 🎓📖

  • Ph.D. (Pursuing) in Computer Science and Engineering, BIT MESRA, Ranchi (2021 – Present)
    • Thesis Title: Implementation of Deep Learning Methods for early diagnosis of various chronic diseases
  • MTech in Computer Science, BIT MESRA, Ranchi (2013-2015)
    • Percentage: 80.8% (First Class with Distinction)
  • B.E. in Computer Science & Engineering, NRI Institute of Information Science & Technology, Bhopal (2009-2013)
    • Percentage: 67.25% (First Class)
  • Schooling at D.A.V. Public School, Bariatu, Ranchi
    • Class XII (2009): 71% (First Class)
    • Class X (2007): 84% (First Class)

Employment History 📅🏫

  • Assistant Professor, National Institute of Advanced Manufacturing Technology, Hatia, Ranchi (April 11, 2022 – April 10, 2023)
  • Assistant Professor, AKG Engineering College, Ghaziabad, Delhi NCR (July 9, 2018 – Dec 10, 2021)
  • Assistant Professor, IMS Engineering College, Ghaziabad, U.P. (July 19, 2017 – June 30, 2018)
  • Assistant Professor, Kanpur Institute of Technology, Kanpur, U.P. (January 18, 2016 – July 08, 2017)
  • Assistant Professor, Subhash Institute of Software Technology, Kanpur, U.P. (June 15, 2015 – January 17, 2016)

Roles & Responsibilities 📋

  • Collegewide Administrative Duties:
    • Syllabus Development for UG Course “Computer Engineering” and PG Course “Data Science”
    • Central ERP Coordinator at AKGEC
    • Initiated and Managed YouTube News Channel for AKGEC
    • Conducted Inter-College Hackathon and Coding Contests
  • Departmental & General Duties:
    • Delivering lectures and supervising labs
    • Departmental Student Attendance Management
    • Recruitment and mentoring students for competitions and projects
  • Academic Activities:
    • Delivered courses on AI, ML, and DL
    • Provided training under DST sponsored projects
    • Conducted hackathons and coding contests
    • Presented papers at national conferences

Courses Taught 📘👨‍🏫

  • BTech Classes: Operating Systems, Theory of Automata and Formal Languages, Machine Learning, Computer Networks, Artificial Intelligence, Database Management System

Publication Top Notes:

Convergence of various computer-aided systems for breast tumor diagnosis: a comparative insight

DNA sequence based data classification technique