TAU Prof. Nathan Intrator is studying what gives biosonar the edge over human-made technologies. He and his collaborator, Brown University Prof. Jim Simmons, have developed a unique method for measuring how animals interpret returning signals using superior real-time data processing. "Animal echolocations are done in fractions of milliseconds, at a resolution so high that a dolphin can see a tennis ball from 260 feet away." The animals are also able to process several pieces of information simultaneously.
It has been argued that today's supercomputers are able to process information at a rate comparable to that of simple invertebrates. And yet, even ignoring physical constraints, no existing algorithm running on the fastest supercomputer could enable a robot to fly around a room, avoid obstacles, land upside down on the ceiling, feed, reproduce, and perform many of the other simple tasks that a housefly learns to perform without external training or supervision. The apparent simplicity with which flies and even much simpler biological organisms manage to survive in a constantly changing environment suggests that current machine learning and information processing could still benefit a lot from understanding neural computation.
Prof. Intrator is studying learning and memory in the visual cortex, statistical aspects of learning, and the connection and application to feature extraction and pattern recognition. He is an international scholar in neural computation, machine learning, and pattern recognition and has authored/co-authored more than 120 refereed scientific publications.
His significant contributions include model estimation, validation, selection, interpretation, and discrimination techniques for high dimensional problems with a small amount of observed data. He is best known for his contribution to the Theory of Cortical Plasticity, brain imaging, decisions from multiple experts, and improving sonar system accuracy.
Prof. Intrator has been supported by US, European, and Israeli federal agencies on projects related to brain imaging and Brain-Machine Interface. His applied research led to several patents and applications and the founding of three companies in biomedical signal analysis, sonar imagery and homeland security.