Assaf is currently a research fellow in Prof. Michal Irani vision lab at the faculty of Computer Science and Applied Mathematics at Weizmann Institute.
In addition, Assaf was an advisor in Prof. Yonina Eldar group (the same faculty), supervising the lab’s CV and ML projects, specifically in the medical domain.
Before that, Assaf was a postdoctoral fellow in the Quantitative Imaging Lab (QIL) at the Biomedical Data Sciences, Stanford University with specialization in computer vision and machine learning.
Throughout his entire academic career, Assaf tackles fundamental challenges in the CV / ML fields, applying them to medical data to improve healthcare.
Data Normalization - new approaches for normalization of heterogeneous data
CV and ML algorithms for tackling key challenges such as limited annotated data, imbalanced data, highly diverse dataset
Generalizable and adaptive frameworks for Big Data
Statistical Computer Vision techniques medical image analysis
Integrated image-text frameworks
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