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Leandros Tassiulas Named 2020 ACM Fellow

YINS
January 13, 2021

Leandros Tassiulas, the John C. Malone Professor of Electrical Engineering and Computer Science, has been named a fellow of the Association for Computing Machinery (ACM), the world’s largest educational and scientific computing society.

The ACM Fellows program recognizes the top 1% of ACM Members for their outstanding accomplishments in computing and information technology and/or outstanding service to ACM and the larger computing community. Fellows are nominated by their peers, with nominations reviewed by a distinguished selection committee.

Tassiulas was selected “for contributions to network control and optimization with applications in communication networks.”

Tassiulas’s research interests are in the field of computer and communication networks with emphasis on fundamental mathematical models and algorithms of complex networks, architectures and protocols of wireless systems, sensor networks, novel internet architectures and experimental platforms for network research. His most notable contributions include the max-weight scheduling algorithm and the back-pressure network control policy, opportunistic scheduling in wireless, the maximum lifetime approach for wireless network energy management, and the consideration of joint access control and antenna transmission management in multiple antenna wireless system

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Hunala app screenshot

Yale app Hunala aims to be ‘Waze for coronavirus’

YINS
June 5, 2020
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.
 
Hunala can be downloaded at hunala.yale.edu.
 
by Brita Belli, YaleNews
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Daniel Spielman

Yale’s Daniel Spielman wins Held Prize for solving decades-old problem

YINS
January 21, 2021
The National Academy of Sciences (NAS) has presented the 2021 Michael and Sheila Held Prize to Daniel Spielman, Sterling Professor of Computer Science and professor of statistics and data science, for helping to solve a theoretical problem that had vexed mathematicians for decades.
 
The Held Prize honors outstanding, innovative, creative, and influential research in combinatorial and discrete optimization, or related parts of computer science, such as the design and analysis of algorithms and complex theory.
 
Spielman shares the award with Adam W. Marcus of the École polytechnique fédérale de Lausanne in Switzerland and Nikhil Srivastava of the University of California, Berkeley.
 

Spielman, Marcus, and Srivastava received international attention after publishing new constructions of Ramanujan graphs, that describe sparse, but highly-connected networks, and a solution to what is known as the Kadison-Singer problem, a decades-old problem that asks whether unique information can be gleaned from a system in which only some of the features can be observed or measured. The solution has relevance for a number of fields, including pure mathematics, the mathematical foundations of quantum physics, and computer science.

The trio began working on these questions in 2009 when they were all at Yale.

Their groundbreaking papers on these questions, both published in 2015, solved problems that mathematicians had been working on for several decades,” NAS said in announcing the prize. “In particular, their solution to the Kadison-Singer problem, first posited in 1959, has been hailed as one of the most important developments in mathematics in the past decade. The proofs provided new tools to address numerous other problems, which have been embraced by other computer scientists seeking to apply the geometry of polynomials to solve discrete optimization problems.”

Spielman said his initial reaction to receiving the Held Prize was “complete surprise.”

We had no idea we were being considered for the Held Prize,” he said. “It is very nice to receive it for this work, because it rewards the biggest gamble I have made in my career and because it was the result of an exhilarating collaboration that lasted many years.”

Spielman, who joined the Yale faculty in 2006 as a professor of applied mathematics and computer science, is a 1992 summa cum laude graduate of Yale.

In 2013, he received a MacArthur Fellowship, popularly known as the “genius” grant, from the John D. and Catherine T. MacArthur Foundation. He was awarded the 2010 Rolf Nevanlinna Prize from the International Mathematical Union, the 2009 Fulkerson Prize, and, on two occasions, the Gödel Prize for outstanding papers in the area of theoretical computer science. He is also a member of the NAS.

by Jim Shelton, YaleNews

About the Michael and Sheila Held Prize

The Michael and Sheila Held Prize is presented annually and carries with it a $100,000 prize. The prize honors outstanding, innovative, creative, and influential research in the areas of combinatorial and discrete optimization, or related parts of computer science, such as the design and analysis of algorithms and complexity theory. This $100,000 prize is intended to recognize recent work (defined as published within the last eight years). The prize was established in 2017 by the bequest of Michael and Sheila Held.

http://www.nasonline.org/programs/awards/michael-and-sheila-held-prize.html

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Daniel Spielman

Daniel Spielman Elected to American Academy of Arts & Sciences

YINS
April 22, 2021

Daniel Spielman, the Sterling Professor of Computer Science, Statistics and Data Science and Mathematics, was elected to the American Academy of Arts & Sciences in 2021 for his contributions to Mathematical and Phyisical Sciences, Computer Sciences.

Founded in 1780, the academy “honors excellence and convenes leaders from every field of human endeavor to examine new ideas, address issues of importance to the nation and the world, and work together to cultivate every art and science which may tend to advance the interest, honor, dignity, and happiness of a free, independent, and virtuous people.”

A full list of new members can be found here

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Yale Researchers Part of New NSF-Funded Quantum Center

Yale Researchers Part of New NSF-Funded Quantum Center

YINS
August 4, 2020

Yale 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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YINS Seminar: “What is tractable in large scale reinforcement learning?”

Speaker: Csaba Szepesvari
Professor & Canada CIFAR AI Chair, Amii  
Department of Computing Science  
University of Alberta 

Event time: 
Wednesday, June 2, 2021 - 12:00pm to 1:00pm
Event Type: 
Weekly Seminar

“Erdos Goes Neural: an Unsupervised Learning Framework for Combinatorial Optimization on Graphs”

Speaker: Andreas Loukas, PhD
Research Scientist, Ecole Polytechnique Fédérale de Lausanne

Event time: 
Wednesday, April 28, 2021 - 12:00pm to 1:00pm
Event Type: 
Weekly Seminar

“Walking the Boundary of Learning and Interaction”

Speaker: Dorsa Sadigh
Assistant Professor, Computer Science and Electrical Engineering
Stanford University

Event time: 
Wednesday, May 19, 2021 - 12:00pm to 1:00pm
Event Type: 
Weekly Seminar

YINS Seminar: Emily Breza (Harvard)

“Effects of caste-based affirmative action in governance on socio-economic networks and resource provision” 

Speaker: Emily Breza
Assistant Professor of Economics, Harvard University
 

Event time: 
Wednesday, May 5, 2021 - 4:00pm to 5:00pm
Event Type: 
Weekly Seminar

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