Ron Mokady
Israel
Summary
🤩
Rockstar🎓
Top SchoolRon Mokady is a research leader and machine learning engineer with seven years of experience, currently serving as VP of Research at BRIA AI. He led the training of the first large-scale diffusion model trained on 100% legal data and previously ran BRIA’s research team. He pursued PhD studies at Tel Aviv University under Prof. Daniel Cohen-Or and Dr. Amit H. Bermano, with work published at CVPR, ICLR and SIGGRAPH and a patent filed. Internships at Google and Facebook AI had him contribute to next-generation visual editing tools, and his open-source work (e.g., a CLIP-based image captioning repo) reflects hands-on involvement in model training, data prep and inference. Early experience in hardware at Apple plus teaching and leadership roles in the IDF give him a practical cross-disciplinary perspective that turns cutting-edge research into deployable systems.
7 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Tel Aviv UniversityMaccabim-Reut High School
English, Hebrew
Github Skills (13)
transformers10
pytorch10
machine-learning10
image-text10
gpt210
image-annotation10
captions10
python10
caption10
data-processing9
jupyter-notebook9
nlp8
computer-vision8
Programming languages (3)
Github contributions (5)
rmokady/CLIP_prefix_caption
Sep 2021 - Feb 2022
Simple image captioning model
Role in this project:
ML Engineer
ML EngineerContributions:35 commits, 1 PR, 16 pushes in 5 months
Contributions summary:Ron primarily contributed to the project by uploading and updating a Jupyter Notebook for inference, likely related to using the image captioning model. They also made changes to the `train.py` and `parse_coco.py` files, indicating involvement in model training and data preparation. These changes suggest the user's focus on the model's implementation, training process, and data handling.
image-captioningimage-processingcomputer-visioncaptioning
rmokady/JOKR
Jun 2021 - Dec 2021
Implementation of "JOKR: Joint Keypoint Representation for Unsupervised Cross-Domain Motion Retargeting"
Contributions:38 commits, 34 pushes, 2 comments in 6 months
pytorchrepresentationretargetingunsupervised-learningdeep-learning
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