Professor Gharib Constructs Leonardo da Vinci's Model of Flow
07-16-19
Leonardo da Vinci studied the motion of blood in the human body. He was interested in the heart’s passive, three-cusp aortic valve, which he realized must be operated by the motion of blood. He theorized that vortices curl back to fill the cusps in the flask-shaped constriction at the aorta’s neck. Morteza Gharib, Hans W. Liepmann Professor of Aeronautics and Bioinspired Engineering; Booth-Kresa Leadership Chair, Center for Autonomous Systems and Technologies; Director, Graduate Aerospace Laboratories; Director, Center for Autonomous Systems and Technologies, has used modern imaging techniques to demonstrate the existence of the revolving vortices that Leonardo interpreted as closing the valve. [Nature Article]
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Morteza Gharib
Biological Circuits: A Beginner’s Guide
07-10-19
A team of researchers including Noah Olsman (PhD ’19), John Doyle, Jean-Lou Chameau Professor of Control and Dynamical Systems, Electrical Engineering, and Bioengineering, and Richard Murray, Thomas E. and Doris Everhart Professor of Control and Dynamical Systems and Bioengineering, has developed a set of guidelines for designing biological circuits using tools from mechanical and electrical engineering. Like electric circuits—but made out of cells and living matter—biological circuits show promise in producing pharmaceuticals and biofuels. [Caltech story]
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John Doyle
Richard Murray
CDS
Professor Daraio Gives Elsevier Distinguished Lecture in Mechanics
05-27-19
Chiara Daraio, Professor of Mechanical Engineering and Applied Physics, was invited to give the Spring 2019 Elsevier Distinguished Lecture in Mechanics at Princeton. Her lecture was entitled “Mechanics of Robotic Matters.” She discussed recent progress in the design of micro- and macro-scale, nonuniform materials that can bend into freeform objects, in response to environmental stimuli or with simple application of point loads. She also showed how the use of responsive materials, like shape memory polymers and liquid crystal elastomers, allows creating new, passive soft robots. [Elsevier Lecture]
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Chiara Daraio
MCE
"Neural Lander" Uses AI to Land Drones Smoothly
05-23-19
Professors Chung, Anandkumar, and Yue have teamed up to develop a system that uses a deep neural network to help autonomous drones "learn" how to land more safely and quickly, while gobbling up less power. The system they have created, dubbed the "Neural Lander," is a learning-based controller that tracks the position and speed of the drone, and modifies its landing trajectory and rotor speed accordingly to achieve the smoothest possible landing. The new system could prove crucial to projects currently under development at CAST, including an autonomous medical transport that could land in difficult-to-reach locations (such as a gridlocked traffic). "The importance of being able to land swiftly and smoothly when transporting an injured individual cannot be overstated," says Professor Gharib who is the director of CAST; and one of the lead researchers of the air ambulance project. [Caltech story]
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Morteza Gharib
Yisong Yue
Soon-Jo Chung
Animashree Anandkumar
Lasers Aim to Replace Scalpels in Cutting-Edge Biopsy Technique
05-16-19
Professor Lihong Wang and Postdoctoral Scholar Dr. Junhui Shi have developed a new imaging technique that uses pulses from two kinds of lasers to take pictures of microscopic biological structures. This new approach, called ultraviolet-localized mid-infrared photoacoustic microscopy, or ULM-PAM, develops images of the microscopic structures found in a piece of tissue by bombarding the sample with both infrared and ultraviolet laser light. "Because ultraviolet light and infrared have different properties, we had to find special mirrors and glass that could focus both," Dr. Shi says. "And because no camera exists that can see both, we had to develop ways to see if they were correctly focused." [Caltech story]
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Lihong Wang
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Junhui Shi
Katie Bouman Joins EAS and CMS
04-11-19
Congratulations to the entire Event Horizon Telescope team, and especially to Dr. Katie Bouman who is joining the Engineering and Applied Science (EAS) Division in June as assistant professor of computing and mathematical sciences (CMS). Currently, Caltech and CO Architects are working with her to design and construct a unique laboratory that will facilitate her work in computational imaging. The laboratory is the first of its kind and is designed for her to conduct experimental work in conjunction with her computational approaches – making it possible, for instance, to observe phenomena previously difficult or impossible to measure. The black hole imaging is one spectacular example of how Professor Bouman’s algorithms are advancing our knowledge of the world; she has also developed algorithms that let us “see around corners” and detect material properties (such as stiffness and dampness) via imaging. In her work, Bouman has also developed methods to combine information from both imaging as well as acoustic systems to analyze sub-pixel scale vibrations of otherwise seemingly still objects. As a result, relatively inexpensive cameras, combined with powerful algorithms, are an increasingly attractive alternative to complex and expensive laser-based systems to sense “invisible” attributes of a material. [Caltech story - How to Take a Picture of a Black Hole]
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Katie Bouman
Laser Technology Helps Researchers Scrutinize Cancer Cells
04-01-19
Lihong Wang, Bren Professor of Medical Engineering and Electrical Engineering, and colleagues are using photoacoustic microscopy (PAM) to improve on an existing technology for measuring the oxygen-consumption rate (OCR). This new method allows the researchers to determine how oxygenated a sample of blood is by "listening" to the sound it makes when illuminated by the laser. Professor Wang calls this single-cell metabolic photoacoustic microscopy, or SCM-PAM. [Caltech story]
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Lihong Wang
Computer Scientists Create Reprogrammable Molecular Computing System
03-20-19
Erik Winfree, Professor of Computer Science, Computation and Neural Systems, and Bioengineering, and colleagues have designed DNA molecules that can carry out reprogrammable computations, for the first time creating so-called algorithmic self-assembly in which the same "hardware" can be configured to run different "software." Although DNA computers have the potential to perform more complex computations than the ones featured in the Nature paper, Professor Winfree cautions that one should not expect them to start replacing the standard silicon microchip computers. That is not the point of this research. "These are rudimentary computations, but they have the power to teach us more about how simple molecular processes like self-assembly can encode information and carry out algorithms. Biology is proof that chemistry is inherently information-based and can store information that can direct algorithmic behavior at the molecular level," he says. [Caltech story]
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Erik Winfree
