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General Information

Full Name Lingxiao Li
Languages Chinese, English

Education

  • 2022
    MSc in Computer Science
    Columbia University, New York, USA
  • 2020
    BSc (Hons) in Computer Science
    University of Liverpool, Liverpool, UK
  • 2020
    BSc (Hons) in Computer Science
    Xi’an Jiao-tong Liverpool University, Suzhou, China

Experience

  • 2024 - now
    Research Assistant
    Department of Information Engineering, The Chinese University of Hong Kong
    Advised by Prof. Xiangyu Yue
    • Customized Image Editing and Generation with Diffusion Models, Generative Models Theory
  • 2021 - 2023
    Research Intern
    Institute of Computing Technology, Chinese Academy of Sciences
    Advised by Prof. Shuhui Wang
    • This research focuses on generating diverse images for an unseen category given only a few images.
    • Achieve state-of-the-art few-shot image generation with high quality and diversity using GAN inversion to manipulate latent codes in hyperbolic space.
  • 2022 - 2023
    Research Assistant
    Department of Computer Science, Columbia University
    Advised by Prof. Junfeng Yang and Prof. Asaf Cidon
    • Monitor and adopt domain shifts at scale in the post-deployment phase to maintain a healthy and functional deep learning system.
  • 2021 - 2022
    Research Assistant
    Department of Electrical Engineering, Columbia University
    Advised by Prof. Zoran Kostic
    • Deployed and trained a customized YOLOv4 on Google Cloud Platform to track small objects in video from 12th floor eye bird camera, decorated the confounder in the training dataset to improve the detection accuracy.
    • Deployed DeepSORT and achieved an average of over 95% counting accuracy for vehicles.

Teaching

  • 2022
    CSOR W4231 - Analysis of Algorithms, Spring 22
    Department of Computer Science, Columbia University
    • Instructor: Eleni Drinea
    • Teaching Assistant for 400 students
    • Developed course material, assignments and gave tutorials

Academic Interests

  • Unsupervised/Few-shot learning
  • Generative models
    • GANs
    • Diffusion models
  • Multi-modal Learning - LLM Guilded Content Generation
  • Domain generalization
    • Test time domain adaptation
  • Representation Learning

Other Interests

  • Volunteer: Primary School Teacher, AIESEC Overseas Volunteer Program in Colombo, Sri Lanka, 2017
  • Hobbies: Classical Music, History, etc.