About Me
I am a PhD student in the Image and Video Computing (IVC) Group at Boston University. I am fortunate to be advised by Professor Kate Saenko and Professor Bryan A. Plummer. I am broadly interested in deep representation learning that is robust against bias and spurious correlations. My hope is to improve the tools for both understanding and mitigating deep learning models' pitfalls.
Outside research, I enjoy road biking, cooking, and photography.
Publications
- Vision-LLMs Can Fool Themselves with Self-Generated Typographic Attacks
- Maan Qraitem, Kate Saenko, Nazia Tasnim, Piotr Teterwak, Bryan A. Plummer
- In Submission [arxiv]/ [code]
- From Fake to Real: Pretraining on Balanced Synthetic Images to Prevent Bias
- Maan Qraitem, Kate Saenko, Bryan A. Plummer
- In Submission [arxiv]/[code: coming soon]
- Bias Mimicking: A Simple Sampling Approach for Bias Mitigation
- From Coarse to Fine-grained Concept based Discrimination for Phrase Detection
- Maan Qraitem, Bryan A. Plummer
- CVPR Workshop on Computer Vision in the Wild 2023 [arxiv]
- Bridging the gap: Machine learning to resolve improperly modeled dynamics
- Maan Qraitem, Dhanushka Kularatne, Eric Forgoston, M. Ani Hsieh
- Physica D: Nonlinear Phenomena [arxiv]
- Real-Time Physics-Based Removal of Shadows and Shading From Road Surfaces
- Bruce A. Maxwell, Casey A. Smith, Maan Qraitem, Ross Messing, Spencer Whitt, Nicolas Thien, Richard M. Friedhoff
- CVPR Workshop on Autonomous Driving 2019 [PDF]
- Circadian oscillations persist in low malignancy breast cancer cells
- Sujeewa S Lellupitiyage Don, Hui-Hsien Lin, Jessica J Furtado, Maan Qraitem, Stephanie R Taylor, Michelle E Farkas
- Cell Cycle [PDF]
Teaching
- CS 542 Machine Learning [Spring 2022, Boston University]
- CS 542 Machine Learning [Spring 2021, Boston University]
- CS 108 Introduction to Applications Programming [Fall 2020, Boston University]