Dr. Sharon Yalov-Handzel

Dr. Sharon Yalov-Handzel

Dr. Sharon Yalov-Handzel has over 30 years of experience in AI, both in a variety of high tech R&D roles and in academia as a researcher and teacher.

Her master’s and doctoral theses, from Weizmann Institute and Bar Ilan University respectively, dealt with optimizing robot motion planning.

Dr. Yalov-Hanzel’s primary work has been in robotics, with a focus on developing algorithms and solving mathematical models for planning robot motion and the navigation control and calibration systems of autonomic systems with various kinematic structures.

In recent years, Sharon has been consulting high tech companies and organizations on data science and Natural Language Processing (NLP). Her main efforts are currently in academia, teaching and researching advanced topics in AI.

Programming Languages

Natural Language Processing

Final Project in Computer Science

Natural Language Processing

Data Science Lab2

Studies of graduate students under my guidance:

Keren Glickman: Neural networks Convergence on Different Imbalanced Datasets Involving Synthetic data​ 

Ido Cohen: Comparison Between Classification and Ordinal Classification Algorithms in Dating Archeological Artifacts 

Brian Rikshpun: Comparison Between Traditional Species Taxonomies and Codon / BiCodon Hierarchy Generated by Machine Learning and Deep Learning Clustering 

Ester Oshrat Vaknin: The Impact of Balancing Images Dataset on Training Performance and Network Properties 

Netanel Shoshani: Comparing the results obtained from several different unsupervised networks for a differential number of categories 

Kfir Raiby: Extracting Structed Data from Unstructed Legal Hebrew Documents 

Gil Dov Stein: Origin Function Estimation from Linear Combination of Multiple Functions 

Alex Raygorodsky: Internal performance and Comparison of NN measures for different ratios of imbalanced medical datasets 

Erez Mahalu: Generative Adversarial Networks Applied to Music Presented in Image Format 

Liran Shani: Few Shot Learning for Information Retrieval with User-Enhanced Query Refinement 

Nikita Shavit: Analysis of Tissues Codon / Bicodon dataset 

Shay Doner: Extract Textual Features from Legal Hebrew Documents