NJIT’s Bipin Rajendran is named a Senior Member of the National Academy of Inventors

Bipin Rajendran, an engineer who develops computing systems that aim to match the efficiency seen in nature by studying the organizational principles of the brain, has been elected a Senior Member of the National Academy of Inventors (NAI). NAI Senior Members are active faculty, scientists and administrators "who have demonstrated remarkable innovation-producing technologies that have brought or aspire to bring, real impact on the welfare of society," according to the Academy. They have also proved successful in patenting, licensing and commercializing their inventions. Rajendran, an associate professor of electrical and computer engineering and expert in nanoscale electronic devices and system design, holds 59 issued U.S. patents. He joins a class of 54 newly elected members from institutions including Yale University, the Texas Heart Institute and the Naval Information Warfare Center. "Advances in computing have enabled systems with astonishing capabilities that augment and even surpass human capacity in many facets of life, but there is a crucial gap in all of these awe-inspiring artificial systems: the enormous amount of energy they consume to perform their tasks," he notes of technologies such as two-legged humanoid robots developed for search-and-rescue operations in hazardous environments and big data-analytics engines that work alongside doctors to diagnose diseases and suggest treatment plans. He adds, "While the Watson supercomputer from IBM required 85,000 watts to challenge and ultimately vanquish two "Jeopardy!" champions, Watson’s conqueror, former U.S. Congressman Rush Holt, relied on a far more efficient machine — the human brain — which functions on a mere 20 watts." At the heart of these brain-inspired systems are artificial neural networks, which are mathematical models of the networks of neurons and synapses in the brain. In order to endow them with human-like intelligence, vast troves of information are fed to them, and their internal parameters — the strengths […]

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