Taking Flight: Professor Soon-Jo Chung


Soon-Jo Chung, Associate Professor of Aerospace and Bren Scholar; Jet Propulsion Laboratory Research Scientist, has wide research interests ranging from the creation of a robotic bat with flexible wings and realistic flight dynamics to the control of swarms of small satellites to the development of computer-vision-based navigation systems. [Interview with Professor Soon-Jo Chung]

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A Birder in the Hand: Mobile Phone App Can Recognize Birds From Photos


Pietro Perona, Allen E. Puckett Professor of Electrical Engineering, and colleagues have developed the Merlin Bird Photo ID mobile app which uses machine-learning technology to identify hundreds of North American bird species it "sees" in photos. "This app is the culmination of seven years of our students' hard work and is propelled by the tremendous progress that computer-vision and machine-learning scientists are making around the world," says Professor Perona. "A machine that recognizes objects in images, like humans do, was a distant dream when I was a graduate student and now it's finally happening." [Caltech story]

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Visualization Brings Data to Life


Students participating in Caltech's Data Visualization program aim to tackle cumbersome data-manipulation problem such as how to drive a rover on Mars from a command room on Earth. One of the goals of the program is to develop innovative software to streamline the ways in which scientists and engineers visually manipulate their data. "We use a human-centered design methodology," Professor Mushkin says. "Design students create sketches and ask the researchers to 'interact' with them by pointing, talking, shuffling, and annotating the paper, while computer science students create rough drafts of a variety of possible approaches to coding the visualization." [Caltech story]

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Practical Mathematics: An Interview with Andrew Stuart


Professor Andrew Stuart is interested in how the current era of data acquisition interacts with centuries of human intellectual development of mathematical models that describe the world around us. His research is informed by—and has applications for—diverse arenas such as weather prediction, carbon sequestration, personalized medicine, and crowd forecasting. [Interview with Prof. Stuart]

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Improving Computer Graphics with Quantum Mechanics


The Schrödinger equation, the basic description of quantum mechanical behavior, can be used to describe the motion of superfluids—fluids, supercooled to temperatures near absolute zero, that behave as though they are without viscosity. Professor Peter Schröder and his colleagues realized that the same equation with some small modifications can also be used to describe vorticity dominated phenomena of fluids at the macroscopic level--from smoke gently rising from a flame to the concentrated vorticity of a twister. [Caltech story & video]

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Counting L.A.’s Trees


Professor Pietro Perona, has developed a method using Google Earth and Google Street View to count the trees in the city of Los Angeles. The process of counting the trees using human tree counters is very expensive and would cost about $3 million today. The last time the city did such counting was more than two decades ago and at the time there were 700,000 street trees. Perona has tested the methodology in a section of Pasadena where the city recently commissioned a sidewalk survey. By comparing the results to the known inventory, he determined that the computer was about 80% accurate. [LA Times story] [KPCC story]

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A Microscopic Glowing Van Gogh


Paul Rothemund, Research Professor of Bioengineering, Computing and Mathematical Sciences, and Computation and Neural Systems, and colleagues have developed a technique that allows manmade DNA shapes to be placed wherever desired; to within a margin of error of just 20 nanometers. This technique removes a major hurdle for the large-scale integration of molecular devices on chips. As a demonstration of the technique’s capabilities the group has created one of the world's smallest reproductions of Vincent van Gogh's The Starry Night. [Caltech story]

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Community Seismic Network Detected Air Pulse From Refinery Explosion


The Community Seismic Network’s (CSN) tight network of low-cost detectors are improving the resolution of seismic data gathering and could offer city inspectors crucial information on building damage after a quake. On February 18, 2015, an explosion rattled the ExxonMobil refinery in Torrance, causing ground shaking equivalent to that of a magnitude-2.0 earthquake and blasting out an air pressure wave similar to a sonic boom. Traveling at 343 meters per second the air pressure wave reached a 52-story high-rise in downtown Los Angeles 66 seconds after the blast. The building's seismometers, which are part of the CSN, noted and recorded the motion of each individual floor. "We want first responders, structural engineers, and facilities engineers to be able to make decisions based on what the data say," explained Monica Kohler, Research Assistant Professor of Mechanical and Civil Engineering, and the lead author of a paper detailing the high-rise's response that recently appeared in the journal Earthquake Spectra. [Caltech story]

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Realtime Camera Planning


Yisong Yue, Assistant Professor of Computing and Mathematical Sciences, is working with colleagues at Disney Research to develop machine-learning algorithms to make automated cameras more human-like.  Professor Yue's research group is generally interested in building AI systems that imitate demonstrated behavior, including laboratory animals, basketball players, humans playing video games, etc.  In this recent work with Disney Research, they are developing an automated camera system that learns how best to film sports matches by watching how human camera operators behave at particular moments. Early testing shows that its shots are far smoother than other automated cameras. [Learn more about the applications] [Learn more about the theory] [techradar story] [Sports Illustrated story]

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Best Paper At Conference on Uncertainty in Artificial Intelligence


Leonard J. Schulman, Professor of Computer Science, and postdoctoral scholar Piyush Srivastava have won the best paper award at the 2016 Conference on Uncertainty in Artificial Intelligence for their paper, Stability of Causal Inference. [Read the paper]

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