Minho Lee

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minho.lee[at]uni-saarland.de

I am a Ph.D. student at Saarland University’s Institute of Preventive Medicine and Sports, conducting research on “Identification and characterization of injury-prone situations in football based on machine learning-based video analysis.” funded by the Deutsche Fußball Liga (DFL). I am under the supervision of Prof. Dr. med. Tim Meyer, Prof. Dr. Werner Krutsch, and Prof. Dr. Daniel Memmert.

My research interest lies in creating machine learning models that can be applied in real-world settings, with a particular focus on analyzing spatio-temporal data. Through this focus, my ultimate goal is to apply these methodologies extensively in the field of sports analytics.

Prior to this, I was a Master’s student in the School of Mathematics and Computing (Computational Science and Engineering) at Yonsei University advised by Prof. Jung-Il Choi. I also achieved a double major in Bachelor of Business Administration and Big Data Science (Data Analytics) at Sogang University, and during this period, I had the opportunity to work in Research & Innovation team at SAP Labs Korea.

News

Nov 16, 2024 One paper (Enhancing Topological Dependencies in Spatio-Temporal Graphs with Cycle Message Passing Blocks) got accepted to Learning on Graphs Conference 2024.
Jul 24, 2024 I’ll be going to Vienna to present my paper at the 2024 ICML GRaM Workshop. This will be my first international conference, and I look forward to engaging with many researchers!
Jul 1, 2024 I’m excited to announce that I started my PhD project at Saarland University in Germany in July 2024!

Selected Publications

  1. Enhancing Topological Dependencies in Spatio-Temporal Graphs with Cycle Message Passing Blocks
    Minho Lee*, Yun Young Choi*, Sun Woo Park, Seunghwan Lee, and Joohwan Ko.
    arXiv preprint 2024
  2. Topology-Informed Graph Transformer
    Yun Young Choi*, Sun Woo Park*,  Minho Lee, and Youngho Woo.
    Geometry-grounded Representation Learning and Generative Modeling Workshop at ICML 2024
  3. Bilevel-optimized continual learning for predicting capacity degradation of lithium-ion batteries
    Minho Lee, Seongyoon Kim, Sanghyun Kim, and Jung-Il Choi.
    Journal of Energy Storage 2024