About Me

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I recently completed my PhD at New York University under the guidance of Prof. Yi Fang. My research focuses on computer vision with a particular emphasis on fairness, foundational models, medical imaging, and self-supervised learning.

During my PhD, I had the opportunity to gain valuable research experience at the Harvard Ophthalmology AI Lab at Harvard Medical School. Additionally, I acquired industry experience as a Machine Learning Research Scientist intern at the Bosch Center for AI.

I welcome opportunities for collaboration and intellectual exchange. Whether you’re interested in joint research, discussing ideas, or seeking advice on the PhD journey, please don’t hesitate to get in touch.

Research Interests

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• Computer Vision
• Fairness
• Medical Imaging

• Self-supervised Learning
• LLMs
• Foundational Models

Education

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New York University
PhD, Computer Science, 2024 (GPA: 3.94)
Major Awards: Global PhD Fellowship; Best Paper Award

New York University Abu Dhabi
B.S., Electrical Engineering, 2019 (GPA: 3.90)
Study Abroad: New York City, Shanghai, Thailand, Sydney
Honor: Awarded a full scholarship for the undergraduate degree

Select Publications

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• FairCLIP: Harnessing Fairness in Vision-Language Learning.
  Yan Luo^*, Min Shi^*, Muhammad Osama Khan^*, Muhammad Muneeb Afzal, et al. In CVPR, 2024.

• Towards Equitable Kidney Tumor Segmentation: Bias Evaluation and Mitigation.
  Muhammad Muneeb Afzal, Osama Khan, Shujaat Mirza. In Machine Learning for Health (ML4H), 2023.

• Equitable deep learning for diabetic retinopathy detection with fair adaptive scaling.
  Min Shi^*, Muhammad Muneeb Afzal^*, Hao Huang^* et al.. In Nature Machine Intelligence (In Review), 2024.

• A Comprehensive Benchmark of Supervised and Self-supervised Pre-training on Multi-view Chest X-ray Classification.
  Muhammad Muneeb Afzal^*, Osama Khan^*, Yi Fang. In Medical Imaging with Deep Learning (MIDL), 2024.

• How Fair are Medical Imaging Foundation Models? (Best Paper Award - Health Equity & Global Health) .
  Osama Khan, Muhammad Muneeb Afzal, Shujaat Mirza, and Yi Fang. In Machine Learning for Health (ML4H), 2023.

• FairDiffusion: Enhancing Equity in Latent Diffusion Models via Fair Bayesian Perturbation.
  Yan Luo^*, Muhammad Osama Khan^*, Muhammad Muneeb Afzal, et al.. In Nature Machine Intelligence (In Review), 2024.

• FairDomain: Fairness in Cross-Domain Medical Image Classification and Segmentation.
  Yu Tian^*, Congcong Wen^*, Min Shi^*, Muhammad Muneeb Afzal, et al.. In ECCV, 2024.

Previously

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Before NYU, I obtained a B.S in Electrical Engineering from NYU Abu Dhabi. During high school, I represented the national team in International Mathematical Olympiad.