Scholar
Kumail Alhamoud
Google Scholar ID: GVzdGe8AAAAJ
PhD Student, MIT
Citations & Impact
Citations
384
H-index
8
i10-index
8
Publications
13
Co-authors
19
list available
Publications
Resume (English only)
Academic Achievements
- CVPR 2025: 'Vision-Language Models Do Not Understand Negation' (Equal contribution)
- MICCAI 2024: 'FedMedICL: Towards Holistic Evaluation of Distribution Shifts in Federated Medical Imaging' (Equal contribution)
- Computers & Chemical Engineering (2024): Work on 2D molecular graph pretraining for 3D conformer generation
- TMLR (2023): 'Generalizability of Adversarial Robustness Under Distribution Shifts' (Featured Certification)
- CVPR 2023: 'Real-Time Evaluation in Online Continual Learning' (Highlight, top 2.5%)
- CVPR 2022: 'vCLIMB: A Novel Video Class Incremental Learning Benchmark' (Oral, top 2.5%)
- IEEE Transactions on Quantum Engineering (2022): Hybrid classical-quantum optimization for production scheduling
Background
- PhD student in Electrical Engineering and Computer Science (EECS) at MIT, advised by Prof. Marzyeh Ghassemi.
- Research focuses on making deep learning models more deployable under distribution shifts, with emphasis on adaptation and evaluation.
- Work spans multiple data modalities and applications in medical imaging, chemistry, and industrial optimization.
- Closely collaborates with Dr. Adel Bibi and Prof. Philip Torr from Oxford.
- Some research has been spotlighted by MIT CSAIL.
