Maryam Sultana
Research Fellow at Oxford Brookes University
Oxford, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolMaryam Sultana is a Research Fellow at the Visual Artificial Intelligence Laboratory, Oxford Brookes University, with eight years of research experience spanning computer vision, deep learning, and uncertainty quantification. She completed a PhD in Computer Science at Kyungpook National University and has held research roles at Mohamed Bin Zayed University of AI and Kyungpook, contributing to generative adversarial networks, background modelling, domain adaptation, and foreground detection. Maryam actively collaborates internationally with labs in France and Pakistan and has served on program committees for top workshops at ICCV, NeurIPS, and UAI, demonstrating engagement with the research community beyond publications. Her work blends theoretical advances in robustness and domain generalization with applied experience in virtual reality and visual AI systems, and she brings a track record of organizing and reviewing high-profile workshops that shape emerging directions in vision and epistemic uncertainty.
9 years of coding experience
1 year of employment as a software developer
M.Phill, Electronics, A, M.Phill, Electronics, A at Quaid-i-Azam University, IslamabadDoctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Kyungpook National University
Github Skills (29)
dcgan10
generative-model10
generative-adversarial-network9
python9
machine-learning9
tensorflow9
vision-transformer9
deep-learning9
unsupervised-learning8
pytorch8
neural-network8
ml7
image-translation7
deep-neural-networks7
algorithms6
Programming languages (7)
Github contributions (5)
maryam089/SDViT
Jun 2022 - Nov 2022
Official repository for "Self-Distilled Vision Transformer for Domain Generalization" (ACCV-2022 ORAL)
Contributions:93 commits, 85 pushes, 1 branch in 5 months
transformervision-transformerdomain-generalizationpytorchdeep-learning
maryam089/DomainBed
Jun 2022 - Jun 2022
DomainBed is a suite to test domain generalization algorithms
Contributions:6 pushes in 1 day
datamininggeneralizationtestingdomain-generalizationtld
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.