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Monday, November 14th, 2016
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| 12:00a |
Tackling society’s big problems with systems theory Some of the biggest issues facing humanity — from global climate change, to water and power infrastructure, to monetary systems, social networks, and other complex systems — involve massive amounts of data that are daunting to analysts and policymakers. To help address these great challenges, MIT’s leaders decided a new approach was needed.
That decision led to the creation of the new Institute for Data, Systems, and Society (IDSS) two years ago, as a way to support and coordinate research using analytical tools to tackle major societal issues. Ali Jadbabaie was recruited from the University of Pennsylvania to serve as interim director and help establish the new center and its doctoral program. Now, with the program well underway, Jadbabaie has come to MIT full-time and become the associate director of IDSS and the director of one of its parts, the Sociotechnical Systems Research Center.
Jadbabaie’s work has spanned many disciplines and departmental affiliations, but his central focus has remained relatively constant: understanding the way distributed systems of people and/or devices interact and work together, and how to optimize those systems and interactions. Although IDSS has its own faculty and will award its own PhD degrees, it is an institute that by its very nature spans too many disciplines to fall within the purview of any single department, or even any one of MIT’s five schools. All of its roughly 40 faculty members do also have joint appointments in other departments; Jadbabaie is the JR East Professor of Engineering in the Department of Civil and Environmental Engineering.
“Our focus is on addressing large societal problems,” he explains, “whether they be power systems and energy systems, or social networks, or financial systems, or urban systems.” The common theme, he says, is that IDSS “tries to address them all from the lens of working from data, to models, to decisions, by using analytical tools from data science.”
He says this approach builds on the long history of MIT’s Laboratory for Information and Decision Systems (LIDS), which is MIT’s oldest lab and now part of IDSS. Both of these entities take the approach of “combining data science with systems theory and social sciences to solve these large global problems.”
For example, one such large system is the nation’s electrical grid, which has grown in a piecemeal fashion over more than a century of operation. “It’s a large-scale engineering system that obeys physical laws, but it also interacts with human users, so its operation depends on how people act, and how they act collectively. If they all plug in at the same time, the system needs to adjust accordingly. And it’s not just the users that affect it: There are also the institutional effects of markets and regulators, and how you adjust prices.”
Traditionally, such large systems have been primarily studied and controlled by people working in particular disciplines — in the case of the grid, by power systems engineers. “But more and more,” Jadbabaie says, “you need to bring in the human systems, and the pricing and regulatory aspects. … It has evolved beyond anything anyone expected. You have all these services now that have this social aspect.”
“We at IDSS try to make sense of the effects of social interactions on people’s decisions. How do social cascades happen?” he says. For example, during the Arab Spring, social media played a major role in expanding a few individual acts of protest into widespread social movements. “All these social and political aspects, this interaction of the technology with the social systems — that’s why we felt that something like IDSS was needed” to help understand such systems in their entirety, he says.
Jadbabaie was born in Iran and grew up mostly in Tehran, where he earned his undergraduate degree. He met his wife, Nikroo Hashemi, in kindergarten there. They met again in college and got married toward the end of their respective doctoral research programs (she at Yale, and he at Caltech, where he earned his PhD in control and dynamical systems). Hashemi became a physician and now works as a transplant hepatologist at Brigham and Women’s Hospital in Boston.
His father, who is now retired in Iran, studied chemical engineering at MIT in the early 1960s, before spending most of his career as an academic administrator in his home country, including a stint as chancellor of two universities there.
Jadbabaie’s own research began with undergraduate studies in electrical engineering and then focused on systems engineering. His research areas included networks of mobile robots and sensors, and the behavior of swarms that need to interact locally and communicate efficiently to coordinate their activities. After a postdoc stint at Yale, he spent 14 years at the Department of Electrical and Systems Engineering at the University of Pennsylvania, with joint appointments in the Department of Computer and Information Science and the Department of Operations, Information and Decisions at the Wharton School, where he earned many awards for his work in the areas of optimization-based control, network science and network economics, and multiagent coordination.
Large, interactive networks, whether they be social networks, banking systems, teams of robots, or transportation systems, all involve the interaction of many different components including technology, economics, psychology, and communications. To address these systems in a systematic way, “there was this recognition that we need a new way of thinking about them that the traditional departmental structure doesn’t address,” he says. At IDSS, Jadbabaie says, he and his colleagues are set on “training a new generation of students in this kind of thinking.” | | 12:00a |
Tackling society’s big problems with systems theory Some of the biggest issues facing humanity — from global climate change, to water and power infrastructure, to monetary systems, social networks, and other complex systems — involve massive amounts of data that are daunting to analysts and policymakers. To help address these great challenges, MIT’s leaders decided a new approach was needed.
That decision led to the creation of the new Institute for Data, Systems, and Society (IDSS) two years ago, as a way to support and coordinate research using analytical tools to tackle major societal issues. Ali Jadbabaie was recruited from the University of Pennsylvania to serve as interim director and help establish the new center and its doctoral program. Now, with the program well underway, Jadbabaie has come to MIT full-time and become the associate director of IDSS and the director of one of its parts, the Sociotechnical Systems Research Center.
Jadbabaie’s work has spanned many disciplines and departmental affiliations, but his central focus has remained relatively constant: understanding the way distributed systems of people and/or devices interact and work together, and how to optimize those systems and interactions. Although IDSS has its own faculty and will award its own PhD degrees, it is an institute that by its very nature spans too many disciplines to fall within the purview of any single department, or even any one of MIT’s five schools. All of its roughly 40 faculty members do also have joint appointments in other departments; Jadbabaie is the JR East Professor of Engineering in the Department of Civil and Environmental Engineering.
“Our focus is on addressing large societal problems,” he explains, “whether they be power systems and energy systems, or social networks, or financial systems, or urban systems.” The common theme, he says, is that IDSS “tries to address them all from the lens of working from data, to models, to decisions, by using analytical tools from data science.”
He says this approach builds on the long history of MIT’s Laboratory for Information and Decision Systems (LIDS), which is MIT’s oldest lab and now part of IDSS. Both of these entities take the approach of “combining data science with systems theory and social sciences to solve these large global problems.”
For example, one such large system is the nation’s electrical grid, which has grown in a piecemeal fashion over more than a century of operation. “It’s a large-scale engineering system that obeys physical laws, but it also interacts with human users, so its operation depends on how people act, and how they act collectively. If they all plug in at the same time, the system needs to adjust accordingly. And it’s not just the users that affect it: There are also the institutional effects of markets and regulators, and how you adjust prices.”
Traditionally, such large systems have been primarily studied and controlled by people working in particular disciplines — in the case of the grid, by power systems engineers. “But more and more,” Jadbabaie says, “you need to bring in the human systems, and the pricing and regulatory aspects. … It has evolved beyond anything anyone expected. You have all these services now that have this social aspect.”
“We at IDSS try to make sense of the effects of social interactions on people’s decisions. How do social cascades happen?” he says. For example, during the Arab Spring, social media played a major role in expanding a few individual acts of protest into widespread social movements. “All these social and political aspects, this interaction of the technology with the social systems — that’s why we felt that something like IDSS was needed” to help understand such systems in their entirety, he says.
Jadbabaie was born in Iran and grew up mostly in Tehran, where he earned his undergraduate degree. He met his wife, Nikroo Hashemi, in kindergarten there. They met again in college and got married toward the end of their respective doctoral research programs (she at Yale, and he at Caltech, where he earned his PhD in control and dynamical systems). Hashemi became a physician and now works as a transplant hepatologist at Brigham and Women’s Hospital in Boston.
His father, who is now retired in Iran, studied chemical engineering at MIT in the early 1960s, before spending most of his career as an academic administrator in his home country, including a stint as chancellor of two universities there.
Jadbabaie’s own research began with undergraduate studies in electrical engineering and then focused on systems engineering. His research areas included networks of mobile robots and sensors, and the behavior of swarms that need to interact locally and communicate efficiently to coordinate their activities. After a postdoc stint at Yale, he spent 14 years at the Department of Electrical and Systems Engineering at the University of Pennsylvania, with joint appointments in the Department of Computer and Information Science and the Department of Operations, Information and Decisions at the Wharton School, where he earned many awards for his work in the areas of optimization-based control, network science and network economics, and multiagent coordination.
Large, interactive networks, whether they be social networks, banking systems, teams of robots, or transportation systems, all involve the interaction of many different components including technology, economics, psychology, and communications. To address these systems in a systematic way, “there was this recognition that we need a new way of thinking about them that the traditional departmental structure doesn’t address,” he says. At IDSS, Jadbabaie says, he and his colleagues are set on “training a new generation of students in this kind of thinking.” | | 10:00a |
Enabling wireless virtual reality One of the limits of today’s virtual reality (VR) headsets is that they have to be tethered to computers in order to process data well enough to deliver high-resolution visuals. But wearing an HDMI cable reduces mobility and can even lead to users tripping over cords.
Fortunately, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have recently unveiled a prototype system called “MoVR” that allows gamers to use any VR headset wirelessly.
In tests, the team showed that MoVR can enable untethered communication at a rate of multiple Gbps, or billions of bits per second. The system uses special high-frequency radio signals called “millimeter waves” (mmWaves) that many experts think could someday help deliver blazingly-fast 5G smartphones.
“It’s very exciting to get a step closer to being able to deliver a high-resolution, wireless-VR experience,” says MIT professor Dina Katabi, whose research group has developed the technology. “The ability to use a cordless headset really deepens the immersive experience of virtual reality and opens up a range of other applications.”
Researchers tested the system on an HTC Vive but say that it can work with any headset. Katabi co-wrote a paper on the topic with PhD candidate Omid Abari, postdoc Dinesh Bharadia, and master’s student Austin Duffield. The team presented their findings last week at the ACM Workshop on Hot Topics in Networks (HotNets 2016) in Atlanta.
How it works
One issue with existing wireless technologies like WiFi is that they can’t support advanced data-processing.
“Replacing the HDMI cable with a wireless link is very challenging since we need to stream high-resolution multi-view video in real-time,” says Haitham Hassanieh, an assistant professor of electrical and computer engineering at the University of Illinois at Urbana Champaigna who was not involved in the research. “This requires sustaining data rates of more than 6 Gbps while the user is moving and turning, which cannot be achieved by any of today's systems.”
Since VR platforms have to work in real-time, systems also can’t use compression to accommodate lower data rates. This has led companies to make some pretty awkward attempts at untethered VR, like stuffing the equivalent of a full PC in your backpack.
The CSAIL team instead turned to mmWaves, which have promising applications for everything from high-speed Internet to cancer diagnosis. These high-frequency waves have one major downside, which is that they don’t work well with obstacles or reflections. If you want mmWaves to deliver constant connectivity for your VR game, you would need to always have a line of sight between transmitter and receiver. (The signal can be blocked even by just briefly moving your hand in front of the headset.)
To overcome this challenge, the team developed MoVR to act as a programmable mirror that detects the direction of the incoming mmWave signal and reconfigures itself to reflect it toward the receiver on the headset. MoVR can learn the correct signal direction to within two degrees, allowing it to correctly configure its angles.
“With a traditional mirror, light reflects off the mirror at the same angle as it arrives,” says Abari. “But with MoVR, angles can be specifically programmed so that the mirror receives the signal from the mmWave transmitter and reflects it towards the headset, regardless of its actual direction.”
Each MoVR device consists of two directional antennas that are each less than half the size of a credit card. The antennas use what are called “phased arrays” in order to focus signals into narrow beams that can be electronically steered at a timescale of microseconds.
Abari says that future versions of MoVR’s hardware could be as small as a smartphone, allowing for users to put several devices in a single room. This would enable multiple people to play a game at the same time without blocking each others’ signals. | | 11:00a |
Researchers create synthetic cells to isolate genetic circuits Synthetic biology allows scientists to design genetic circuits that can be placed in cells, giving them new functions such as producing drugs or other useful molecules. However, as these circuits become more complex, the genetic components can interfere with each other, making it difficult to achieve more complicated functions.
MIT researchers have now demonstrated that these circuits can be isolated within individual synthetic “cells,” preventing them from disrupting each other. The researchers can also control communication between these cells, allowing for circuits or their products to be combined at specific times.
“It’s a way of having the power of multicomponent genetic cascades, along with the ability to build walls between them so they won’t have cross-talk. They won’t interfere with each other in the way they would if they were all put into a single cell or into a beaker,” says Edward Boyden, an associate professor of biological engineering and brain and cognitive sciences at MIT. Boyden is also a member of MIT’s Media Lab and McGovern Institute for Brain Research, and an HHMI-Simons Faculty Scholar.
This approach could allow researchers to design circuits that manufacture complex products or act as sensors that respond to changes in their environment, among other applications.
Boyden is the senior author of a paper describing this technique in the Nov. 14 issue of Nature Chemistry. The paper’s lead authors are former MIT postdoc Kate Adamala, who is now an assistant professor at the University of Minnesota, and former MIT grad student Daniel Martin-Alarcon. Katriona Guthrie-Honea, a former MIT research assistant, is also an author of the paper.
Circuit control
The MIT team encapsulated their genetic circuits in droplets known as liposomes, which have a fatty membrane similar to cell membranes. These synthetic cells are not alive but are equipped with much of the cellular machinery necessary to read DNA and manufacture proteins.
By segregating circuits within their own liposomes, the researchers are able to create separate circuit subroutines that could not run in the same container at the same time, but can run in parallel to each other, communicating in controlled ways. This approach also allows scientists to repurpose the same genetic tools, including genes and transcription factors (proteins that turn genes on or off), to do different tasks within a network.
“If you separate circuits into two different liposomes, you could have one tool doing one job in one liposome, and the same tool doing a different job in the other liposome,” Martin-Alarcon says. “It expands the number of things that you can do with the same building blocks.”
This approach also enables communication between circuits from different types of organisms, such as bacteria and mammals.
As a demonstration, the researchers created a circuit that uses bacterial genetic parts to respond to a molecule known as theophylline, a drug similar to caffeine. When this molecule is present, it triggers another molecule known as doxycycline to leave the liposome and enter another set of liposomes containing a mammalian genetic circuit. In those liposomes, doxycycline activates a genetic cascade that produces luciferase, a protein that generates light.
Using a modified version of this approach, scientists could create circuits that work together to produce biological therapeutics such as antibodies, after sensing a particular molecule emitted by a brain cell or other cell.
“If you think of the bacterial circuit as encoding a computer program, and the mammalian circuit is encoding the factory, you could combine the computer code of the bacterial circuit and the factory of the mammalian circuit into a unique hybrid system,” Boyden says.
The researchers also designed liposomes that can fuse with each other in a controlled way. To do that, they programmed the cells with proteins called SNAREs, which insert themselves into the cell membrane. There, they bind to corresponding SNAREs found on surfaces of other liposomes, causing the synthetic cells to fuse. The timing of this fusion can be controlled to bring together liposomes that produce different molecules. When the cells fuse, these molecules are combined to generate a final product.
More modularity
The researchers believe this approach could be used for nearly any application that synthetic biologists are already working on. It could also allow scientists to pursue potentially useful applications that have been tried before but abandoned because the genetic circuits interfered with each other too much.
“The way that we wrote this paper was not oriented toward just one application,” Boyden says. “The basic question is: Can you make these circuits more modular? If you have everything mishmashed together in the cell, but you find out that the circuits are incompatible or toxic, then putting walls between those reactions and giving them the ability to communicate with each other could be very useful.”
Vincent Noireaux, an associate professor of physics at the University of Minnesota, described the MIT approach as “a rather novel method to learn how biological systems work.”
“Using cell-free expression has several advantages: Technically the work is reduced to cloning (nowadays fast and easy), we can link information processing to biological function like living cells do, and we work in isolation with no other gene expression occurring in the background,” says Noireaux, who was not involved in the research.
Another possible application for this approach is to help scientists explore how the earliest cells may have evolved billions of years ago. By engineering simple circuits into liposomes, researchers could study how cells might have evolved the ability to sense their environment, respond to stimuli, and reproduce.
“This system can be used to model the behavior and properties of the earliest organisms on Earth, as well as help establish the physical boundaries of Earth-type life for the search of life elsewhere in the solar system and beyond,” Adamala says. |
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