Professor Beck Receives Masanobu Shinozuka Medal
James L. (Jim) Beck, George W. Housner Professor of Engineering and Applied Science, Emeritus, has received the American Society of Civil Engineers (ASCE) Masanobu Shinozuka Medal, "for his original contributions to subset simulation in reliability analysis of stochastic systems, a powerful technique that allows probabilistic estimation of rare events; for his pioneering work in developing technologies for machine learning in earthquake engineering applications." The medal is given in recognition of outstanding contributions to the field of stochastic mechanics, reliability and risk and simulation. [List of medal recipients]
Undergraduate Students Win International Data Science Competition
Undergraduate students Hongsen Qin, Emma Qian, Thomas Hoffmann, and Alexander Zlokapa (advised by Professors Aaron Ames, Erik Winfree, Jonathan Katz, Maria Spiropulu, and Yaser Abu-Mostafa) have won the Citadel Data Open International Data Science Competition. This winning team chose to investigate the optimal way to spend $1 billion to save lives from malaria and sanitation-related diseases, allocating funds for different prevention methods and optimizing budget breakdowns country by country. To quantify the socioeconomic impacts of their policy proposal, they modeled a variety of aspects from mosquito feeding cycles to climate change using techniques ranging from causal discovery methods to interpretable machine learning. The Caltech team was among 24 teams that were evaluated and questioned by a panel of experts including the former Chief Scientist of AI at Microsoft, a Princeton professor, and the chief of equities at Citadel. The Caltech team was chosen as the first place winner based on the depth, rigor, and comprehensiveness of their analysis.
Katie Bouman Joins EAS and CMS
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]
Joel A. Tropp Named 2019 SIAM Fellow
Joel A. Tropp, Steele Family Professor of Applied and Computational Mathematics has been elected to the 2019 class of Society for Industrial and Applied Mathematics (SIAM) fellows. He was nominated for his exemplary research as well as outstanding service to the community. He is being recognized for contributions to signal processing, data analysis and randomized linear algebra.
Computer Scientists Create Reprogrammable Molecular Computing System
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]
Teaching Coding in Elementary Schools
On Friday afternoons, Caltech computer science students visit public schools in Pasadena to help third-, fourth-, and fifth-graders learn to code. Their work is part of a recently introduced course in which Caltech undergrads study and practice strategies for teaching programming to children. “We start with basic concepts and, by the end, students have coded their own games in Scratch [a visual programming language developed for children],” says Caltech senior Anna Resnick, who helps lead the class as a teaching assistant. “A few have even told us they want to be programmers someday.” [Caltech story]
Meet the 2018 Amazon Fellows
The Amazon Fellows program is the result of a partnership between Caltech and Amazon AWS around Machine Learning and Artificial Intelligence (AI). The 2018 Amazon fellows are Ehsan Abbasi, Gautam Goel, Jonathan Kenny, Palma London, and Xiaobin Xiong. Abbasi is interest in contributing to a deeper understanding of convex and non-convex learning methods in AI and is an Electrical Engineering graduate student working with Professor Babak Hassibi. Goel’s research interest is at the interface of the theory and practice of machine learning and is advised by Professor Adam Wierman. London is also working with Professor Wierman. She is developing efficient algorithms for solving extremely large optimization problems. The methods are applicable to distributed and parallel optimization. For example in a distributed data center setting, the algorithms are robust to unreliable data transfer between data centers and take into account privacy concerns. Kenny is a Computation & Neural Systems graduate student working with Professor Thanos Siapas on deep neural networks to identify and classify brain states. Xiong is a mechanical engineering graduate student who enjoys working on real physical robots, to make them walk, jump, and run in real life. He is advised by Professor Aaron Ames and their research is focused on robotic bipedal locomotion
Creating a "Virtual Seismologist"
Professor Yisong Yue is collaborating with Caltech seismologists to use artificial intelligence (AI) to improve the automated processes that identify earthquake waves and assess the strength, speed, and direction of shaking in real time. Professor Yue explains, “the reasons why AI can be a good tool have to do with scale and complexity coupled with an abundant amount of data. Earthquake monitoring systems generate massive data sets that need to be processed in order to provide useful information to scientists. AI can do that faster and more accurately than humans can, and even find patterns that would otherwise escape the human eye.” [Read the full Q&A]