Welcome to My Portfolio! 👾

Hi! I’m Qilin Xu (许琪林), a National Scholarship recipient and passionate AI enthusiast, currently a Research Assistant at MARS Lab, Wuhan University.
On this site, I share my research projects, co-op experiences, and personal journey.

[Read my BIO here]

Education:

Research Areas:

  • Machine Learning
    • Multimodal Machine Learning
    • Pattern Recognition
    • exploring new algorithms for integrating multiple data sources in AI systems

Selected Honors & Awards:

  • Meritorious Winner in the MCM/ICM, May 2023
    (美国大学生数学建模竞赛 Meritorious 奖)
  • First Prize in National English Competition for College Students, Feb 2023
    (全国大学生英语竞赛特等奖)
  • National Scholarship, Oct 2022
    (国家奖学金, 1% in Chongqing University)

[Read my CV here]

Co-op: AI-Based Wildfire Detection System Design

Hubei State Grid Wuhan University of Technology Power

During my internship from May 2024 to August 2024 at Hubei State Grid Wuhan University of Technology Power Consulting Division, I had the opportunity to engage with cutting-edge technologies in digital grid solutions, intelligent energy, and extensive data operations. The company specializes in integrating digital technology into power grid solutions, providing intelligent energy, system integration, and comprehensive data analytics expertise. This internship allowed me to work on several impactful projects, significantly enhancing my technical and professional skills.

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Publication: Intelligent Power Grid Infrastructure Quality Detection Based on CBAM-ASFF-YOLOv4

Enhancing Power Grid Infrastructure Inspection with AI and Drones

In modern power grid infrastructure projects, ensuring the quality of construction is critical to maintaining safety and operational stability. Traditional manual inspections face significant challenges due to weather conditions, terrain, and the complexity of the environment. To address these challenges, intelligent detection methods utilizing drones and AI-based algorithms are gaining traction. This article presents a novel approach for grid infrastructure quality detection using CBAM-ASFF-YOLOv4, which integrates Adaptive Spatial Feature Fusion (ASFF) and Convolutional Block Attention Module (CBAM) with YOLOv4 to improve detection accuracy and speed.

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Co-op: Power System Analysis Intern

Tsinghua Sichuan Energy Internet Research Institute

During my internship at the Tsinghua Sichuan Energy Internet Research Institute from August to December 2023, I had the opportunity to contribute to a highly technical project focused on power system analysis, specifically examining the impact of large-scale renewable energy integration on system inertia and frequency. This experience greatly enhanced my algorithm development, simulation, and technical communication skills. It provided a deeper understanding of the intersection between AI and energy systems.

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Co-op: Energy consumption mode mining and exception identification

Electrical Engineering Lab, Chongqing University

During my first co-op at Chongqing University Electrical Engineering Lab from Janurary 2023 to April 2023, I had the opportunity to work on an exciting project involving energy consumption mode mining and exception identification of power users. My advisor is Professor Juan Yu. This experience gave me invaluable skills and insights that shaped my approach to machine learning and research. Here’s a detailed look at what I learned and accomplished during this co-op:

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Project: Identifying and Predicting Meteorologically Sensitive Loads

Student Research Traning Program (SRTP) at Chongqing University

From March 2021 to November 2023, I had the privilege of being a member of the Electrical Engineering Lab at Chongqing University, where I worked on a research project advised by Professor Duo Liu aimed at identifying and predicting meteorologically sensitive loads in power supply station areas. This project involved the development of advanced machine learning models to analyze municipal grid power load data and forecast both long- and short-term power load curves. The experience significantly deepened my understanding of power systems. It reinforced my skills in applying machine learning to real-world energy problems.

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Activity: Intelligent Vehicles Design and Lecture Practices

My Experience as a Cadre at the Association of Intelligent Vehicles and Opto-electronic Information, Chongqing University

From October 2021 to July 2022, I served as a cadre at the Association of Intelligent Vehicles and Opto-electronic Information at Chongqing University. During my time with the association, I had the opportunity to contribute to developing intelligent vehicle technologies, enhance my technical skills in microcontroller programming, and collaborate with fellow members on exciting projects related to trajectory cars. This experience enriched my understanding of the technical and organizational aspects of working in a student-led technical association.

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