Muhammad Huzaifa

Machine Learning graduate student, MBZUAI, Abu-Dhabi - BSc from SEECS, NUST, Pakistan.

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Masdar City, Abu Dhabi

Hi, I am Muhammad Huzaifa, a Machine Learning Master research student, affilated with IVAL at Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI). I am working under the supervision of Dr. Salman Khan and Dr. Fahad Khan. I am also grateful to be supervised and mentored by Dr. Muzammal Naseer.

My research focuses on investigating robust visual perception through techniques such as adversarial machine learning and representation learning. Additionally, I explore the adaptation of multi-modal models for vision tasks such as image recognition, object detection, and image captioning, especially in scenarios with limited data, including few-/zero-shot learning setups.

Email / Google Scholar / Github / Twitter / CV

News

Oct 29, 2024 Test-Time Low Rank Adaptation via Confidence Maximization for Zero-Shot Generalization Accepted at WACV, 2025
Sep 15, 2024 ObjectCompose Accepted at ACCV for oral presentation!
Aug 14, 2024 Serving as a reviewer at WACV’25
Jul 27, 2024 We have released Test-Time Low Rank Adaptation via Confidence Maximization for Zero-Shot Generalization of Vision-Language Models
Apr 30, 2024 Serving as a reviewer at ECCV’24

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Selected publications

* denotes joint first authors

  1. ObjectCompose.jpg
    ObjectCompose: Evaluating Resilience of Vision-Based Models on Object-to-Background Compositional Changes
    Hashmat Shadab Malik* ,  Muhammad Huzaifa* ,  Muzzamal Naseer , and 2 more authors
    ACCV, 2024
  2. tta-raza.png
    Test-Time Low-Rank Adaptation via Confidence Maximization for Zero-Shot Generalization of Vision-Language Models
    Raza Imam ,  Hanan Gani ,  Muhammad Huzaifa , and 1 more author
    WACV, 2025
  3. defensive_diffusion.png
    On enhancing the robustness of vision transformers in medical imaging: Defensive diffusion
    Raza Imam* ,  Muhammad Huzaifa* ,  and  Mohammed El Amine Azz
    In 27th Conference on Medical Image Understanding and Analysis 2023 , 2023