Research & Educational Labs

Research Labs

The Statistics and Data Science Lab

The Research lab, led by Dr. Amichai Painsky engages in theoretical, empirical, and quantitative research. The lab integrates advanced tools from the realms of mathematics, statistics, and computer science. Lab members develop and implement statistical methods, machine learning algorithms, and advanced analytics to tackle complex problems across various domains. The primary research topics in the lab include statistical learning, machine learning, inference, and prediction

The DEep Learning Technologies and Applications (DELTA) Lab’s
Research lab, The DEep Learning Technologies and Applications (DELTA) Lab’s mission is to help democratize deep-learning for everyone. The lab, headed by Dr. Noam Koenigstein, is focused on applied deep-learning algorithms for a variety of real-world problems. Research projects include areas of explainable AI (XAI), recommender systems, machine learning for agricultural applications, machine learning for macro-economic forecasting, machine learning in education, machine learning in electronic music, and more. As part of our various research activities, we maintain strong collaborations with the industry and the public sector.


Digital Epidemiology and Health Analytics (DEHA) Lab

The DEHA Lab at Tel Aviv University, led by Prof. Dan Yamin, focuses on interdisciplinary research combining technology and public health. The research team evaluates vaccine safety and efficacy, optimizes healthcare allocation, monitors real-time health using smartwatches and wearable technologies, develops disease spread models, and analyzes electronic medical records to guide health policy. Each study contributes to building a foundation for enhancing community well-being and promoting global health.


The Big Data Lab

Research lab, The Big Data Lab is a research lab headed by Prof. Erez Shmueli. Digital information about users is undoubtedly the oil of the new economy. Collecting, processing, and leveraging such data at large scale, a trend called Big Data, is the fuel that powers many online services like Facebook, Google, Amazon and Netflix. Big Data hold many promises, not only for the individual but also for the public good. At the individual level, Big Data can help users to become more connected, productive, and entertained. At the society level, Big Data creates tremendous opportunities in areas ranging from marketing to public health and urban planning. Research in this lab focuses on utilizing data to build computational models of human behavior.

Data Driven Modeling and Analysis Lab

The Research lab, led by Dr. Neta Rabin, is engaged in the development of data-driven models and algorithms with the aim of solving complex, real world problems. The lab members develop algorithms for robust and informative representation of complex systems, for example problems in which the input is high-dimensional, measured in different spatial locations over time, or sensed by diverse measuring instruments. Based on the output of the data modeling and representation, we further develop algorithms for varied machine learning tasks like regression, classification and anomaly detection. Our collaborations are mostly with the defense and government industries and from hospitals.


 LAMBDA(Laboratory of AI, Machine Learning and Business Data Analytics)

The Research lab, led by Prof. Irad Ben-Gal, is focuses on research, development and collaboration activities in the areas of artificial intelligence, big data analytics and data science, with a strong emphasis on real-life industrial challenges.
The Lab aims to serve as a hub of collaboration, enabling scholars and students to work collaboratively on practical data-science challenges, while exposing the industry to pioneering research methods and to the next generation of analytics tools. Accordingly, LAMBDA’s efforts are focused on large-scale collaborative research projects with a unique synergy among groups of academic researchers, developers, educators, industry-domain experts, practitioners and decision makers.


The Computer Integrated Manufacturing (CIM) Laboratory
The Educational  Lab offers introductory and advanced laboratories in Modern Computer Integrated Manufacturing.
Theoretical lectures are followed by practical laboratories and projects to cover the following concepts and technologies:
  • Robotics – including industrial and mobile robots
  • Computer Vision and Sensors
  • Computer Aided Design (CAD)
  • Computer Aided Manufacturing (CAM)
  • Computer Aided Process Planning (CAPP)
  • Computer Numerically Controlled (CNC) Turning and Milling
  • Automated Storage and Retrieval System (ASRS)
  • Programmable Logic Controllers (PLC)
  • Automated Assembly and Supervisory Control
  • Smart Cards and RFID
  • Human Machine Interface (HMI)
  • Decision Support Systems and advanced algorithms
  • CIM in the Internet
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