Hanoona Rasheed
United Arab Emirates
Summary
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Rockstar🎓
Top SchoolHanoona Rasheed is a computer vision researcher and PhD candidate at MBZUAI with six years of experience building interpretable, grounded multimodal models for image and video understanding. She has contributed to top-tier conferences (CVPR, NeurIPS, ECCV, ICCV, ICLR, ACL) and completed research internships at Meta and Adobe focused on scalable video data engines, spatio-temporal grounding, and long-video story reasoning. Her work emphasizes reducing textual drift and improving sustained attention to visual evidence, aiming for models that are both reliable and usable in real-world settings. Prior roles in robotics and signal processing (including Bosch and Unique World Robotics) give her a strong applied ML background across perception, chemometrics, and embedded systems. She combines deep research rigor with practical system-building experience, having delivered publications tied to production-scale data engineering efforts. Based in the UAE, she blends academic excellence with industry-focused impact on multimodal AI.
6 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy, Artificial Intelligence, Doctor of Philosophy, Artificial Intelligence at MBZUAI (Mohamed bin Zayed University of Artificial Intelligence)
Github Skills (87)
representations10
backbone10
clip10
chatbot9
object-detection9
semantic-segmentation9
supervised-learning9
vocabulary9
computer-vision8
3d-reconstruction8
paper8
self-supervised-learning8
lmms8
google-colab8
pytorch8
Programming languages (1)
Github contributions (5)
mmaaz60/mvits_for_class_agnostic_od
Nov 2021 - Jul 2022
Official repository of paper titled "Class-agnostic Object Detection with Multi-modal Transformer" (ECCV 2022).
Contributions:1 review, 14 commits, 3 PRs in 7 months
multimodal-learningclass-agnostic-detectionpytorchmulti-modalmodal
hanoonaR/object-centric-ovd
Jul 2022 - Oct 2022
[NeurIPS 2022] Official repository of paper titled "Bridging the Gap between Object and Image-level Representations for Open-Vocabulary Detection".
Contributions:1 release, 22 commits, 3 PRs in 3 months
pytorchrepresentationsdeep-learningneuripsneurips-2022
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