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RaptorMai/README.md

My name is Zheda(Marco) Mai, and I am a third-year Ph.D. student from the Department of Computer Science and Engineering at the Ohio State University, advised by Professor Wei-Lun (Harry) Chao. My research interests lie in Efficient Foundation Model Adaptation, Multimodal LLM, Continual Learning. You can find more information about me at my personal page: https://zheda-mai.github.io/.

+ I am actively looking for a research internship! 
+ If you are aware of any opportunities or have any recommendations,
+ I would greatly appreciate your insights and referrals. Please feel free to reach out!

I obtained my MASc. from the University of Toronto advised by Prof. Scott Sanner. I mostly worked on Continual Learning and Recommender Systems during my master collaborating with LG AI Research.

Prior to that, I completed my BASc. in Engineering Science at the University of Toronto, where I was fortunate to work with Dr. Erkang Zhu.

You can contact me at mai.145@osu.edu or by LinkedIn.

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  1. online-continual-learning Public

    A collection of online continual learning paper implementations and tricks for computer vision in PyTorch, including our ASER(AAAI-21), SCR(CVPR21-W) and an online continual learning survey (Neuroc…

    Python 399 57

  2. CVPR20_CLVision_challenge Public

    1'st Place approach for CVPR 2020 Continual Learning Challenge

    Python 46 4

  3. Deep-AutoEncoder-Recommendation Public

    Keras implementation of AutoRec and DeepRecommender from Nvidia.

    Jupyter Notebook 62 21

  4. CompBench Public

    [NeurIPS'25] MLLM-CompBench evaluates the comparative reasoning of MLLMs with 40K image pairs and questions across 8 dimensions of relative comparison: visual attribute, existence, state, emotion, …

    Jupyter Notebook 36 2

  5. OSU-MLB/ViT_PEFT_Vision Public

    [CVPR'25] Lessons Learned from a Unifying Empirical Study of Parameter-Efficient Fine-Tuning (PEFT) in Visual Recognition

    Jupyter Notebook 30

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