Sigal Raab
Researcher, Postdoctoral Fellow at Weizmann Institute of Science
Sde Warburg, Center District, Israel
Summary
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Rockstar🎓
Top SchoolSigal Raab is a researcher and postdoctoral fellow at the Weizmann Institute with a strong background in computer vision, graphics and deep learning, building on a PhD from Tel Aviv University and over five years in research roles. Her career mixes academic rigor with industry impact, including a Machine Learning Engineer role at Amazon focused on computer vision and a history of systems and design leadership at Broadcom and other technology firms. She contributes to open-source ML work—most recently enhancing a PyTorch human motion diffusion model with action-to-motion sampling, visualization outputs and backwards-compatible tooling. Sigal’s strengths lie in translating cutting-edge generative models into reproducible code and demonstrable results, bridging data pipelines, model architecture and evaluation. Based in Sde Warburg, Israel, she combines deep theoretical knowledge with practical engineering fluency gained across startups, academia and large tech. An understated but valuable trait is her emphasis on clear, reproducible model outputs (e.g., MP4 motion visualizations), which improves both evaluation and adoption.
5 years of coding experience
29 years of employment as a software developer
MamramPhD candidate Computer Vision and Graphics Deep Learning, PhD candidate Computer Vision and Graphics Deep Learning at Tel Aviv UniversityPostdoctoral Fellow, Postdoctoral Fellow at Weizmann Institute of ScienceMaster of Science (MSc) Computer Science, Master of Science (MSc) Computer Science at Bar Ilan University
Stackoverflow
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Github Skills (10)
diffusion-models10
computer-vision10
pytorch10
machine-learning10
python10
modeling9
trainings9
evaluation9
eval9
ffmpeg8
Programming languages (2)
Github contributions (5)
GuyTevet/motion-diffusion-model
Oct 2022 - Nov 2022
The official PyTorch implementation of the paper "Human Motion Diffusion Model"
Role in this project:
ML Engineer
ML EngineerContributions:7 commits, 10 pushes, 38 comments in 1 month
Contributions summary:Sigal primarily focused on enhancing the human motion diffusion model by adding functionalities related to a2m (action-to-motion) sampling and training. This involved modifying data loading, model architectures, and evaluation scripts to support the new sampling approach. Further contributions included creating and integrating code to generate and save motion visualizations as MP4 files, demonstrating a focus on model output and result presentation. The user also addressed backward compatibility issues in the parsing of arguments within the project.
pytorchdiffusionmotionpytorch-implementation
sigal-raab/Motion
Apr 2021 - Jan 2023
Contributions:23 commits, 14 pushes, 1 branch in 1 year 9 months
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