Animashree (Anima) Anandkumar, Bren Professor of Computing and Mathematical Sciences, develops efficient techniques to speed up optimization algorithms that underpin machine-learning systems. Speaking about the connections between industry and academia she explains,“bridging the gap between industry and academia is really important. It is a big part of what brought me to Caltech. The sooner we can take theory and deploy it practically, the faster innovation moves and the more impact it can have.” [Interview with Professor Anandkumar]
Take a deep dive into a crucial moment in technological history with Carver Mead, Gordon and Betty Moore Professor of Engineering and Applied Science, Emeritus. In this first of a series of videos being produced by the Caltech Archives, titled 'My First Chip’, Professor Mead tells the story of meeting Gordon Moore, who would soon predict that every year the semiconductor industry would double the number of transistors that could be fabricated on a commercial integrated circuit. Carver Mead and his students worked on the physics of ultra-small transistors, and showed that, in addition to allowing greater density, they ran faster and used less power. This work proved that Moore’s prediction did not violate any laws of physics, and it became known as 'Moore's Law'–the term coined and made famous by Professor Mead.
Azita Emami, Andrew and Peggy Cherng Professor of Electrical Engineering and Medical Engineering; Investigator, Heritage Medical Research Institute; and EAS Division Deputy Chair, along with her colleagues including Professor Mikhail Shapiro have developed microscale devices that relay their location in the body. "We wanted to make this chip very small with low power consumption, and that comes with a lot of engineering challenges," says Professor Emami. "We had to carefully balance the size of the device with how much power it consumes and how well its location can be pinpointed." [Caltech story]
Professor John Doyle and colleagues are among only nineteen groups in the United States to receive National Science Foundation (NSF) funding to conduct innovative research focused on neural and cognitive systems. They aim is to integrate the capabilities of deep learning networks into a biologically inspired architecture for sensorimotor control that can be used to design more robust platforms for complex engineered systems. [NSF release]
Caltech and Cornell teamed up to create the iNaturalist Challenge, a competition to create the best machine-learning algorithm for identifying the world's plant and animal species. The contest was an outgrowth of the institutions' previous work together on Visipedia, a visual encyclopedia created by a network of people and machine-learning computers that harvest image information off the internet. The technology was developed for the encyclopedia by Pietro Perona's Vision Group at Caltech and Serge Belongie's Computer Vision Group at Cornell Tech. [Caltech story]
Xiaoyue Ni, a materials science graduate student working with Professor Julia Greer, has shown that metals undergo permanent deformation even prior to yielding—the threshold at which a material under strain becomes permanently deformed. "What Xiaoyue's data are showing is that from the first moment you start deforming it, the dislocations start being active," Greer says. Now that we know how to do this, we can probe a variety of different classes of materials. [Caltech story]
Azita Emami, Andrew and Peggy Cherng Professor of Electrical Engineering and Medical Engineering; Investigator, Heritage Medical Research Institute; and EAS Division Deputy Chair, has been selected as a speaker for the National Academy of Engineering’s (NAE) 23rd annual U.S. Frontiers of Engineering (USFOE) symposium. The symposium will cover cutting-edge developments in four areas: Mega-Tall Buildings and Other Future Places of Work, Unraveling the Complexity of the Brain, Energy Strategies to Power Our Future, and Machines That Teach Themselves. The mission of the NAE is to advance the well-being of the nation by promoting a vibrant engineering profession and by marshalling the expertise and insights of eminent engineers to provide independent advice to the federal government on matters involving engineering and technology. [NAE Press Release]
Professor Ali Hajimiri and colleagues have developed a new camera design that replaces the lenses with an ultra-thin optical phased array (OPA). The OPA does computationally what lenses do using large pieces of glass: it manipulates incoming light to capture an image. "Here, like most other things in life, timing is everything. With our new system, you can selectively look in a desired direction and at a very small part of the picture in front of you at any given time, by controlling the timing with femto-second—quadrillionth of a second—precision," says Professor Hajimiri. [Caltech story] [ENGenious silicon photonics feature]