Yonina Eldar

Research Overview

Our research focuses on building radically resource-aware sensing systems that sense only what matters - systems that diagnose, monitor, protect, and connect. By uniting physics, hardware, signal processing, and artificial intelligence, our group develops intelligent, interpretable, and sustainable sensing technologies that improve human life and strengthen security. This vision, which we call Green Intelligence, seeks to redefine the relationship between information, energy, and purpose: sensing not for maximal data, but for maximal insight and information. Our group conducts research at the intersection of artificial intelligence, sensing, signal processing, and biomedical engineering, with a strong emphasis on real-world impact in healthcare, communications, and defense.

The Signal Acquisition Modeling Processing and Learning (SAMPL) Lab, headed by Prof. Yonina Eldar, focuses on developing new technologies that more efficiently extract and process signals and information across a wide range of tasks, including medical imaging, radar, communication, scientific and optical imaging and biological inference. The lab also develops model-based methods for artificial intelligence (AI) that aid in obtaining increased information using minimal resources.

Signal processing is the area of science and engineering concerned with the generation, acquisition, representation, transmission and analysis of signals and information using mathematical theory and methods. Signal processing is the power behind our modern lives, enhancing our ability to communicate and share information. The technology in our everyday lives – from computers, cell phones and autonomous vehicles to medical and defense systems – is enabled by signal processing. The performance and effectiveness of these systems depend on the quality and efficiency of signal sampling and processing. In many cases, such as medical applications, automotive and aviation, these capabilities are critical to human health, life and wellbeing.

In the coming years, new and increasingly complex challenges will arise as we become even more dependent on signal processing in our everyday lives. As countless additional tasks and functions are replaced by smart and automated applications, they will require increasingly faster and more powerful technologies. As these new technologies sweep across the planet to billions of people in emerging markets, they will need to become increasingly more efficient and less costly.

While traditional systems treat the sampling and processing stages separately and require sampling at the well-known Nyquist rate, SAMPL lab introduces a paradigm shift in which sampling and processing are jointly designed in order to leverage the inherent properties of signals and tasks during the sampling stage. Thus, we can acquire and process only the information needed for the required task, reduce the sampling and processing rates well below the Nyquist rate, and greatly improve the resolution which can be obtained from a limited number of samples in time, space and frequency.

This approach paves the way to new technologies such as wireless ultrasound, compact portable devices with better imaging quality, fast and quantitative MRI, efficient wideband sensing, high resolution radar, efficient communication systems, joint radar and communication systems for automotive and IoT applications, super resolution microscopy and ultrasound, model-based efficient and interpretable deep networks for medical imaging, communication systems, radar based medical imaging and sensing, and more.

In order to perform the above, SAMPL lab combines theoretical research in the fields of mathematics, information theory, statistical signal processing, AI and computer science, and practical engineering research using our state-of-the-art lab to facilitate the transition from pure theory to prototype systems and clinical studies. Via our Clinical Research arm, we collaborate with physicians across Israel and abroad, to advance healthcare, medical diagnostics and imaging. Via our Technologies arm, we collaborate with industry partners to impact next-generation technologies. In addition, we collaborate closely with researchers in biology and physics in order to advance technology for scientific discovery.