Starting in fall 2018, EAS will offer students a new undergraduate degree option in a field that is at the forefront of computer science: information and data sciences (IDS). Mathematics will form the backbone of the new option. Students in IDS will take core courses focusing on machine learning, information theory, probability, statistics, linear algebra, and signal processing. After that, they will have the opportunity to branch out with electives that cover applications of data sciences to science and engineering. Professor Adam Wierman hopes the creation of this new option will prepare both students and Caltech for the future. "It almost doesn't matter what you're interested in. If you want to make discoveries and be on the cutting edge of your field, you're going to need the skills to analyze and manipulate large collections of information," he says. [Caltech story] [Degree option details]
In a letter to the Caltech community during National Postdoc Appreciation Week, the Caltech President emphasizes the role this key group plays at the Institute. He stated, “Caltech's mission of world-leading research and education depends crucially on our postdoctoral scholars. Although their time at Caltech may be short, they quickly become vital parts of the Institute's intellectual fabric.” [President’s Letter] [EAS Postdoc Resource Page]
Carver Mead, one of the fathers of modern computing, combines memoir and instruction in new video series. "My feeling is that these days, if it's not on the web, it doesn't exist," Professor Mead says of the decision to launch the new video channel. The video series is available for free on YouTube, and aims to provide a better understanding of the birth and evolution of modern computing, as told by one of its key participants and witnesses. [Caltech story]
Graduate student Grant Van Horn and postdoctoral scholars Oisin Mac Aodha, working with Professor Pietro Perona, started the iNaturalist Challenge last year, to see how much they could push machine-learning technology. The competition is now in its second year and the dataset contains over 8,000 species, with a combined training and validation set of 450,000 images that have been collected and verified by multiple users from iNaturalist. This year's competition promise to be much more challenging because there are more species and less examples for the computer to learn from. The top submissions will be invited to give talks at CVPR, which is the premier annual computer vision event. [Enter the competition]
Four graduate students from the Computing and Mathematical Sciences (CMS) Department and one from the Electrical Engineering (EE) Department have been selected as 2017 Amazon Fellows. This fellows program is the result of a partnership between Caltech and Amazon AWS around Machine Learning and Artificial Intelligence. The EE fellow is Srikanth Tenneti who is exploring the potential of deep learning for Direction of Arrival applications, and extending Ramanujan Sums based techniques for multi-dimensional periodicity extraction. CMS graduate student Navid Azizan Ruhi is researching faster optimization algorithms for machine learning. He is looking forward to visiting Amazon AI as a fellow and exchanging ideas with their researchers. Computer science graduate student Hoang Le is developing methods for efficient and intelligent sequential decision making in realistic systems. Florian Schaefer, whose focus is applied and computational mathematics, is researching the interface of statistical estimation and the design of fast algorithms. Control and dynamical systems graduate student Ellen Feldman, working with Professor Joel Burdick, has used part of the funding to present her research at the Society for Neuroscience annual meeting and looking forward to other future opportunities to share her research.
Caltech and Disney Research have entered into a joint research agreement to pioneer robotic control systems and further explore artificial intelligence technologies. Pietro Perona will work with Disney roboticist Martin Buehler to create navigation and perception software that could allow robotic characters to safely move through dense crowds and interact with people. Aaron Ames will work with Disney Research's Lanny Smoot to further explore robot autonomy and machine learning by creating objects that can self-navigate and perform stunts. Yisong Yue has been working with engineers from Disney Research on the use of machine learning to analyze the behavior of soccer players and to measure audience engagement. [Caltech story]
As she steps down as CEO of the Anita Borg Institute, Telle Whitney (PhD ’85) reflects on her career in tech—and the path ahead for the next generation of women. From Caltech to researcher to entrepreneur to advocate for women in technology, this Caltech alumna’s career has thrived on risk-taking and transition—and she’s inspired and assisted hundreds of thousands of women along the way. [Techer profile]
Professor Venkat Chandrasekaran and graduate student Armeen Taeb have developed an empirical statewide model of the California reservoir network. This work offers reservoir managers insight on how to plan and respond to drought conditions. "The bread and butter of hydrology is using physical laws to describe water phenomena. But the behavior of these reservoirs is not solely determined by physical laws of the water cycle, but also by demands and what these reservoirs are being used for," Taeb explains. [Caltech story]
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.
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]