I am currently an assistant professor of Computer Science.
Before that, I was a research fellow in Prof. Michal Irani vision lab at the faculty of Computer Science and Applied Mathematics at Weizmann Institute.
I was a postdoctoral fellow under the supervision of Prof. Daniel Rubin at the Biomedical Data Sciences, Stanford University with specialization in computer vision and machine learning. I also collaborated with Demetri Terzopoulos from UCLA and awarded the prestigious Young Investigator Award of the QIN-NIH for "his outstanding and innovative work in adaptive methods and career vision for advancing quantitative imaging"
Throughout my entire academic career, I tackle fundamental challenges in the CV / ML fields, applying them for complex data (with focus on medical data to improve personalized 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
Combination of theoretical and applicative aspects to improve CV techniques
Integrated image-text frameworks
Medical Image Analysis for personalized medicine (detection, segmentation, classification and prediction of pathologies)
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