AI-Driven COVID-19 Model Outperforms Competitors
11-30-20
While existing models to predict the spread of a disease already exist, few, if any, incorporate artificial intelligence (AI). Professor Yaser Abu-Mostafa is using a new model for predicting COVID-19's impact using AI and it dramatically outperforms other models, so much so that it has attracted the interest of public health officials across the country. "AI is a powerful tool, so it only makes sense to apply it to one of the most urgent problems the world faces," says Yaser Abu-Mostafa. [Caltech story]
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EE
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CMS
Yaser Abu-Mostafa
Robotics Engineers Take on COVID-19
11-18-20
Methods that were originally created to help robots to walk and autonomous cars to drive safely can also help epidemiologists predict the spread of the COVID-19 pandemic. Professor Aaron Ames and colleagues took these tools and applied them to the development of an epidemiological methodology that accounts for human interventions (like mask mandates and stay-at-home orders). By utilizing the U.S. COVID-19 data from March through May, they were able to predict the infection wave during the summer to high accuracy. "This is the greatest health challenge to face our society in a generation at least. We all need to pitch in and help in any way we can," Ames says. [Caltech story]
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MCE
CMS
Aaron Ames
Andrew Singletary
A Molecular Approach to Quantum Computing
09-03-20
The technology behind the quantum computers of the future is fast developing, with several different approaches in progress. Many of the strategies, or "blueprints," for quantum computers rely on atoms or artificial atom-like electrical circuits. In a new theoretical study in the journal Physical Review X, Caltech demonstrates the benefits of a lesser-studied approach that relies not on atoms but molecules. One concept behind the new research comes from work performed nearly 20 years ago by Professor John Preskill, Professor Alexei Kitaev, and their colleague Daniel Gottesman. [Caltech story]
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Alexei Kitaev
John Preskill
Advancing Future Quantum Science Efforts
08-27-20
Five new Department of Energy centers will apply quantum information science to emerging technologies. The centers will develop cutting-edge quantum technologies for use in a wide range of possible applications including scientific computing; fundamental physics and chemistry research; and the design of solar cells and of new materials and pharmaceuticals. Caltech faculty will participate in four of the new science centers: the Quantum Systems Accelerator, led by the Lawrence Berkeley National Laboratory, also known as Berkeley Lab; the Quantum Science Center, led by Oak Ridge National Laboratory; Q-NEXT, led by Argonne National Laboratory; and the Co-design Center for Quantum Advantage, led by Brookhaven National Laboratory. [Caltech story]
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APhMS
EE
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CMS
Oskar Painter
Andrei Faraon
AI for a Better Prediction COVID-19 Model
08-25-20
A team of Caltech students, led by Professor Yaser Abu-Mostafa, have developed a tool to predict the impact of COVID-19 using artificial intelligence (AI). While many models to predict the spread of a disease already exist, few if any incorporate AI, which makes predications based on observations of what is actually happening as opposed to what the model's designers think should happen. AI has the power to discover patterns hidden in data that the human eye might not recognize. [Caltech story]
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CMS
Yaser Abu-Mostafa
Machine Learning Helps Robot Swarms Coordinate
07-14-20
Soon-Jo Chung, Bren Professor of Aerospace, Yisong Yue, Professor of Computing and Mathematical Sciences, postdoctoral scholar Wolfgang Hönig, and graduate students Benjamin Rivière and Guanya Shi, have designed a new data-driven method to control the movement of multiple robots through cluttered, unmapped spaces, so they do not run into one another. "Our work shows some promising results to overcome the safety, robustness, and scalability issues of conventional black-box artificial intelligence (AI) approaches for swarm motion planning with GLAS and close-proximity control for multiple drones using Neural-Swarm," says Chung. [Caltech story]
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GALCIT
CMS
Yisong Yue
Soon-Jo Chung
postdocs
Benjamin Rivière
Guanya Shi
Wolfgang Hönig
Professor Hou Featured in Quanta Magazine
01-14-20
The Quanta Magazine has featured Thomas Y. Hou, Charles Lee Powell Professor of Applied and Computational Mathematics, for his work in Euler singularity. Mathematicians and physicists have used Euler equations to model how fluids evolve over time. If you toss a rock into a still pond, how will the water be moving five seconds later? The Euler equations can tell you. Hou provided a numerical description of the initial state of a fluid and used a computer to apply the Euler equations to determine the fluid’s motion in the future. “From the top the fluid is spiraling down, and from the bottom it is swirling up in the opposite direction,” said Professor Hou. [Quanta article]
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Thomas Hou
Making a Better Match
01-14-20
Professor Adam Wierman worked with a cross-disciplinary team to improve the Pasadena Unified School District's open-enrollment algorithm. Wierman knew from experience that the district's open-enrollment process was not optimal. "I couldn't help but notice that it wasn't particularly well designed," says Wierman. "There was a huge opportunity, I thought, to improve." With the team's new and improved algorithm, families are more likely to get their top match and are also more likely to keep their children in the school district rather than enrolling them in private or charter schools. [Caltech story]
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Adam Wierman
