The revolution in the measurement and collection of data and the resulting huge amounts of data have made data science a very important field of study and research. Today researchers are mining data available from various sources, such as web query logs, social media posts and blogs, satellites, sensors,  network traffic, and more.

Our labs focus on analyzing large-scale data streams such as news, blogs, sensor data, social media and more to provide personalization, perform predictive analytics, and identify anomalies in the data.

Our research covers a range of topics in machine learning and data science:

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• Automated Machine Learning (AutoML)

• Connected Cars and Intelligent Transportation Systems

• Recommender Systems

• Cyber Security

• Computational Criminology

• Natural Language Processing (NLP)

• Medical Information Analytics

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In the recommender systems our current focus is using Deep Learning techniques to build concise representations of the meanings of user's context and use these powerful features to provide accurate personal recommendations.

Another focus is the application of machine learning for cyber security. In various projects we collect network data, honeypot data, or transaction data, to detect anomalies or fraud, predict the malware behavior and perform continuous authentication and more.

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The labs is lead by Prof. Lior Rokach, Prof. Bracha Shapira, Dr. Rami Pusis, Dr.Oren Tzur and Dr. Gilad Katz . Graduate, M.Sc. and Ph.D students are engaged in the labs as scientific developers, research assistants, project managers and data scientists. 

All the labs collaborate with many partners in the relevant industry.