Announcing the Awardees of the 2023 TAD Center Research Grants

The grants are given for a broad range of projects in the fields of AI and Data Science, with a total of 3.2 Million NIS

09 March 2023
Announcing the Awardees of the 2023 TAD Center Research Grants

TAD Center is pleased to announce the awardees of the TAD Center Research Grants - Year 2023. This year 15 regular grants and 6 seed grants will be awarded, with a total of 3.2 Million NIS.


The grants are given for a broad range of projects in the fields of AI and Data Science. We thank all PIs who applied for TAD research grants and all the reviewers. We hope the grants will advance innovative research and interdisciplinary collaborations.


Research Grant Awardees:

  • Ronen Avraham (Law), Tamar Kricheli-Katz (Law), and Roded Sharan (Computer Science), Title: "Under the Hood of the American Supreme Court: Identifying Authorship in Unsigned Opinions"

  • Jonathan Belmaker (Zoology), Yossi Yovel (Zoology and Sagol School) and Yoav Ram (Zoology), Title: "Developing an acoustic monitoring tool for coral reef health"

  • Amit Bermano (Computer Science) and Yoav Lahini (Physics and Astronomy), Title: "Generative Models for the Design and Analysis of Quantum Devices"

  • Hadar Elor (Electrical Engineering) and Yoram Cohen (Archaeology), Title: "Paleography Powered by Learning: Analyzing Cuneiforms with Neural Networks"

  • Ram Fishman (Public Policy), Title: "Using Machine Learning to Understand the Impacts of Climatic Variability on Human Behavior"

  • Barak Hirshberg (Chemistry) and Yohai Bar-Sinai (Physics and Astronomy), Title: "Machine Learning of Collective Variables for Accelerating Molecular Dynamics Simulations"

  • Joachim Mayer (Industrial Engineering), Title: "Human-systems integration in AI-supported fake news detection"

  • Aya Meltzer Asscher (Linguistics) and Jonathan Berant (Computer Science), Title: "Elucidating Human Language Processing with Large Language Models"

  • Daniel Nevo (Mathematical Sciences), Itay Saporta-Eksten (Economics), and Analia Schlosser (Economics), Title: "Generalized regression discontinuity design with multiple time periods and comparison groups for causal inference: theory and practice"

  • Uri Obolski (Public Health) and Ran Gilad Bachrach (Biomedical Engineering), Title: "Mathematical foundations of xAI and their applications to personalized medicine and public health"

  • Yaron Oz (Physics and Astronomy) and Lior Wolf (Computer Science), Title: "Learning the Dynamics of Chaos and Turbulence"

  • Or Perlman (Biomedical Engineering) and Gil Navon (Chemistry) , Title: "Magnetic Sweet AI: Metabolic Brain Cancer Imaging using Deep MRI of a Sugar-Based Contrast Agent"

  • Tal Pupko (Shmunis School of Biomedicine and Cancer Research), Yishay Mansour (Computer Science), and Itay Mayrose (Plant Sciences), Title: "AI-based methodologies for phylogeny: model selection and tuning dataset-specific search Parameters"

  • Neta Rabin (Industrial Engineering) and Jeffrey Hausdorff (Medicine), Title: "Estimating real-world step length from inertial measurement units using advanced machine learning techniques"

  • Eshbal Ratzon (Jewish Philosophy) and Nachum Dershowitz (Computer Science), Title: "Dating the Dead Sea Scrolls Using Computational Linguistics Tools"


Seed Grant Awardees: 

  • Segev Barak (Psychological Sciences), Title: "Identifying and characterizing new biomarkers for alcohol addiction using artificial intelligence"

  • Uri Binyamin Rom (Music), Title: "Developing and Implementing an Algorithmic Toolset for Data-driven Music-Analytical Research"

  • Jason Friedman (Health Professions), Title: "Using inverse reinforcement learning to understand what is being learned in motor learning"

  • Yariv Gerber (Public Health) and Yael Benyamini (Social Work), Title: "Midlife Predictors of Exceptional Survival in a Cohort of 10,000 Israeli Male Employees"

  • Anatoli Khina (Electrical Engineering), Title: "Geometry-oriented Dependence Measures"

  • Yossi Yovel (Zoology and Sagol School) and Raja Giryes (Electrical Engineering), Title: "Large Scale Acoustic Based Navigation – a Machine Learning Approach"


Congratulations to the Awardees!



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