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Yale app Hunala aims to be ‘Waze for coronavirus’A team of Yale researchers has developed a new app, Hunala, that aims to be the “Waze for coronavirus.”
Led by Sterling Professor Nicholas Christakis, a physician and social networks expert, with colleagues in the Yale School of Engineering and Applied Science, the free app provides a daily snapshot of personal and regional risk for COVID-19 infection based on data from the Centers for Disease Control and Prevention and users’ self-reported health and demographic information.
Just as Waze relies on crowd-sourced data to provide real-time updates of traffic conditions in order to redirect drivers to less congested routes, Hunala relies on daily inputs from users to provide a real-time look at coronavirus risk based on individuals’ associations, activities, and health status. The app’s effectiveness at assessing COVID-19-related risks improves as the number of users grows. Since the app launched two weeks ago, 3,000 people have signed up.
“We think this will help the American public as we emerge from lockdowns to assess their risk,” said Christakis, the Sterling Professor of Social and Natural Science, “especially as we head toward a second wave [of infections].”
Christakis directs The Human Nature Lab, part of the Yale Institute for Network Science, which aims to better understand the intersection of human networks and human health.
When users download Hunala, they are prompted to enter basic information about themselves, including location, age, health history, prior positive tests for COVID-19, and whether they’ve been in large gatherings in the past 24 hours.
Each day, the app asks users for updated information. In return, it adjusts two color-coded dials, one representing their regional and one their personal risk, from low (blue) to high (red).
During sign-up, users also list people from their phone contacts who are close family and friends. These contacts receive a notification that someone they know has joined Hunala and an invitation to join. A person’s social network helps the app assess risk because disease spreads from person to person.
“A person closer to the center of the network is at higher risk,” Christakis said. “Popular people are more likely to get infections early in the epidemic.”
The app is designed to protect users’ privacy and anonymity: contacts are only messaged once; the app does not store contact information; and users’ names and health information are never shared.
But these networks of people are essential for the app to assess risk.
“If something happens in some part of the network — if one ‘node’ tests positive, then the risk goes up for people in that network,” said Yale’s Amin Karbasi, assistant professor of electrical engineering and computer science and head of the multidisciplinary Interference, Information, and Decision Group. He is leading the machine learning and artificial intelligence backbone of the app.
As Waze leads drivers to change routes when there’s a traffic jam ahead, the researchers hope that Hunala’s assessments will help users to modify their behavior to reduce their risk.
“If the app tells you that your risk is high, you may be more likely to physical distance from friends and not go outside as much,” said Jacob Derechin, a doctoral student in Christakis’ Human Nature Lab and a member of the team.
Additional members of the Yale team are principal software engineer Mark McKnight; web app developer Wyatt Israel; and biomedical engineering doctoral student Shivkumar Vishnempet. Computer science major Alexi Christakis, ’20, nephew of Dr. Christakis, contributed early in the process.
Christakis began studying social networks 20 years ago. In a 2010 TED talk, “How social networks predict epidemics,” he describes how certain people represent the centers of networks, with many connections via family, friends, and work. “If we want to track something that was spreading through a network,” such as a disease, he said, “what we ideally would like to do is to set up sensors on the central individuals … monitor those people that are right there in the middle of the network, and somehow get an early detection of whatever it is that is spreading through the network.”
Hunala is an effort to do this: By pulling data from as many people as possible it predicts who is at risk and warns them to act accordingly.
“This is a tool, just like masks,” Christakis said. “We are alive at a moment when a new pathogen has been introduced to our species. It’s not going away, and millions of us will be affected.”
The best defense, he said, is information.
by Brita Belli, YaleNews
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Yale Researchers Part of New NSF-Funded Quantum CenterYale University is among the core partners of the new Center for Quantum Networks (CQN), funded by the National Science Foundation (NSF).
With the University of Arizona serving as the lead institute and host, the center will be funded with an initial five-year, $26 million grant from the National Science Foundation, with an additional five-year $24.6 million option. In addition to Yale, partners include Brigham Young University, Harvard University, Howard University, the Massachusetts Institute of Technology, Northern Arizona University, University of Chicago, University of Massachusetts Amherst and University of Oregon.
The center is part of the NSF’s Engineering Research Center (ERC) program, which supports education, technology translation and research at U.S. universities designed to have strong societal impacts. Although they’re initially funded by the NSF, ERCs are expected to be self-sustaining within 10 years.
CQN aims to lay the foundations of the quantum internet - a communications network that would be more secure and could work with the next generation of computers. The CQN will also investigate the impact of a future quantum internet on education, workforce development, innovation and society.
Yale’s participation in the center is led by Leandros Tassiulas, John C. Malone Professor of Electrical Engineering & Computer Science; Hong Tang, the Llewellyn West Jones, Jr. Professor of Electrical Engineering, Applied Physics & Physics; and Michel Devoret, the Frederick W. Beinecke Professor of Applied Physics & Physics.
Quantum technology takes advantage of the properties of electrons, photons, and atoms to develop computers powerful enough to process a massive amount of information. Tassiulas said the center will be at the forefront of creating the future quantum internet.
“This project would realize the underlying interconnection infrastructure that will be based on quantum phenomena like quantum entanglement,” Tassiulas said. Quantum entanglement is the uncanny ability for two particles to interact, regardless of distance and no physical connection. Such a network, researchers say, could revolutionize how people compute and communicate by creating a fabric to connect quantum computers, data centers and gadgets using their native quantum information states of “quantum bits,” or qubits. Qubits offer dramatic increases in processing capacity by not just having the 0 or 1 state of the classical bit, but also allowing what is termed a “superposition” of both states at the same time.
Tassiulas said his role will be in developing network level protocols for this new interconnection infrastructure – analogous to the protocols realizing today’s Internet. Tang and Devoret will focus on the hardware of quantum technology.
The center is one of the NSF’s four new engineering research centers announced Tuesday. The other centers will focus on extending the viability of cells, tissues, organs and organisms; designing sustainable infrastructure for electrified vehicles; and realizing precision agriculture.
“For the last 35 years, engineering research centers have helped shape science and technology in the United States by fostering innovation and collaboration among industry, universities and government agencies,” said NSF Director Dr. Sethuraman Panchanathan. “As we kick off a new generation of centers, NSF will continue to work with its partners to ensure the success of these collaborative enterprises and the transformative, convergent research impact they produce.”
A major focus of the CQN team will be advancing key underlying technologies, including fundamental quantum materials and devices, the quantum and classical processing required at a network node, and quantum network protocols and architectures. CQN also aims to demonstrate the first U.S.-based fault-tolerant quantum network that can distribute quantum information at high speeds, in high fidelity and over long distances, and to simultaneously serve multiple user groups. CQN research will accelerate recent advances in quantum computing by scaling quantum computational capabilities with distributed access through a quantum network.
In addition to the nine university research partners, a large innovation ecosystem of over 10 companies and the potential of $2 billion of venture capital has been cultivated during the proposal process. As the case with today’s Internet, quantum networking technologies show great promise for U.S. economic development, and CQN’s industry partners have indicated strong interest in the potential for new quantum device and system technologies. A key component of CQN’s Innovation Ecosystem is a partnership with the Quantum Economic Development Consortium, a National Institute of Standards and Technology-led consortium aimed to form a functional bridge between quantum information science and engineering researchers and the industry. CQN’s industry partnerships will also play a valuable role in defining application road maps to inform CQN’s technical direction and research investments.
This article was originally published by the Yale School of Engineering & Applied Science on August 4, 2020.
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