Prof. Yael Amsterdamer

 Data Management

Whenever we search for information or verify a fact, we rely on vast amounts of data from diverse sources—social networks, government databases, and news reports. In the era of Big Data, the primary challenge is not just collecting data, but transforming it into useful, reliable, and accessible knowledge, while filtering out noise and redundancies.

Prof. Yael Amsterdamer’s research focuses on developing intelligent systems and algorithms for managing Big Data. The systems she builds analyze how data is utilized for tasks such as knowledge discovery, fact-checking, and determining data usage rights. The goal is to identify the most critical data for any given mission and streamline the process so that when human involvement is necessary, the effort required is kept to a minimum.

Primary Research Areas:

• Big Data Management: Developing algorithms for efficient data processing at scale.

• Interactive data management: Optimization of data-centric processes that include human experts or users in the loop

• Data Integration: Selection of data sources and how to integrate them in order to obtain the most relevant, complete and reliable data for given tasks

• Knowledge discovery and data mining: The extraction of useful patterns and insights from raw data

Research Nature:

 Integrated – Practical and Theoretical: Developing algorithmic methods alongside their practical application to large-scale data systems.

Career Path:

Data is a critical component of nearly every modern system and organization. Specializing in this field provides a deep understanding of the potential inherent in data, and develops skills in the creation and optimization of large-scale data processing workflows—expertise that is essential in any advanced technological organization.