Anette “Peko” Hosoi named associate dean of engineering

Anette “Peko” Hosoi has been named associate dean of the MIT’s School of Engineering. Currently the associate department head in the Department of Mechanical Engineering and the Neil and Jane Pappalardo Professor of Mechanical Engineering, Hosoi has been at MIT since 1997 and a member of the faculty since 2002. She will begin her new role on Sept. 1, 2017. Vladimir Bulović, the Fariborz Maseeh (1990) Professor of Emerging Technology, serves as the school’s associate dean for innovation in the School of Engineering.

“I am thrilled that Peko has agreed to join the dean’s leadership team,”says Anantha Chandrakasan, dean of the School of Engineering. “She is a distinguished scholar and a real force in helping us understand how we can better educate our students. I am looking forward to working closely with her as our plans in the school begin to take shape.”

Hosoi will contribute to the school’s mission broadly, though she anticipates making the most contributions in educational initiatives and strategic planning and implementation. 

From her first job at MIT as an instructor in the Department of Mathematics, to her role as one of the faculty leaders for the New Engineering Education Transformation (NEET) program, Hosoi has a long record of working closely with students. A MacVicar Faculty Fellow, she has been instrumental in creating and supporting a range of educational activities in mechanical engineering, including enhancements to the current flexible undergraduate program Course 2-A and student activities such as MakerWorks. She is also a past winner of the Ruth and Joel Spira Award for Distinguished Teaching, the School of Engineering Junior Bose Award for Education, the Bose Award for Excellence in Teaching, and the Den Hartog Distinguished Educator Award. Hosoi believes the School of Engineering is poised to make some significant changes in how the Institute trains its engineers.  

“We as MIT faculty are extremely precise and analytical in our research,” she notes. “We need to bring the same rigor to how we think about education.” NEET, which Hosoi co-leads with Ford Professor of Engineering Edward Crawley, stems from exactly this kind of thinking, Hosoi adds. 

Hosoi, who studied physics at Princeton University and then the University of Chicago, began her research career working in fluid mechanics and thin-film flows. Over the years, she says, her work has followed a circuitous path through soft matter, soft robotics, bio-inspired engineering design, biomechanics, and sports technology. Her research has garnered attention by both fellow scientists and the general media. Recent discoveries of note include a beaver-inspired wetsuit that maximizes warmth and minimizes bulk, a “tree-on-a-chip” design that mimics the pumping mechanism of trees and plants, and even a digging robot inspired by the Atlantic razor clam. In 2012, Hosoi was named a fellow of the American Physical Society for “innovative work in thin fluid films and in the study of nonlinear interactions between viscous fluids and deformable interfaces including shape, kinematic, and rheological optimization in biological systems.”

Hosoi’s interest in sports led her to co-found MIT 3-Sigma Sports, a program that seeks to improve athletic performance and advance endurance, speed, accuracy, and agility in sports through collaborations between students, faculty, alumni, and industry partners. This combination of people around a particular problem is exactly what Hosoi wants to do more of, she says. “The most successful research programs at MIT always engage the students in some way.”

Hosoi’s nickname comes from a brand of Japanese candy: “It’s like an American being called ‘Snickers’” she says. “My grandmother, who’s Japanese, thought I looked like the little girl on the box, and it stuck.” She lives in Cambridge, Massachusetts, with her husband Justin Brooke.

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Automatic image retouching on your phone

The data captured by today’s digital cameras is often treated as the raw material of a final image. Before uploading pictures to social networking sites, even casual cellphone photographers might spend a minute or two balancing color and tuning contrast, with one of the many popular image-processing programs now available.

This week at Siggraph, the premier digital graphics conference, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory and Google are presenting a new system that can automatically retouch images in the style of a professional photographer. It’s so energy-efficient, however, that it can run on a cellphone, and it’s so fast that it can display retouched images in real-time, so that the photographer can see the final version of the image while still framing the shot.

The same system can also speed up existing image-processing algorithms. In tests involving a new Google algorithm for producing high-dynamic-range images, which capture subtleties of color lost in standard digital images, the new system produced results that were visually indistinguishable from those of the algorithm in about one-tenth the time — again, fast enough for real-time display.

The system is a machine-learning system, meaning that it learns to perform tasks by analyzing training data; in this case, for each new task it learned, it was trained on thousands of pairs of images, raw and retouched.

The work builds on an earlier project from the MIT researchers, in which a cellphone would send a low-resolution version of an image to a web server. The server would send back a “transform recipe” that could be used to retouch the high-resolution version of the image on the phone, reducing bandwidth consumption.

“Google heard about the work I’d done on the transform recipe,” says Michaël Gharbi, an MIT graduate student in electrical engineering and computer science and first author on both papers. “They themselves did a follow-up on that, so we met and merged the two approaches. The idea was to do everything we were doing before but, instead of having to process everything on the cloud, to learn it. And the first goal of learning it was to speed it up.”

Short cuts

In the new work, the bulk of the image processing is performed on a low-resolution image, which drastically reduces time and energy consumption. But this introduces a new difficulty, because the color values of the individual pixels in the high-res image have to be inferred from the much coarser output of the machine-learning system.

In the past, researchers have attempted to use machine learning to learn how to “upsample” a low-res image, or increase its resolution by guessing the values of the omitted pixels. During training, the input to the system is a low-res image, and the output is a high-res image. But this doesn’t work well in practice; the low-res image just leaves out too much data.

Gharbi and his colleagues — MIT professor of electrical engineering and computer science Frédo Durand and Jiawen Chen, Jon Barron, and Sam Hasinoff of Google — address this problem with two clever tricks. The first is that the output of their machine-learning system is not an image; rather, it’s a set of simple formulae for modifying the colors of image pixels. During training, the performance of the system is judged according to how well the output formulae, when applied to the original image, approximate the retouched version.

Taking bearings

The second trick is a technique for determining how to apply those formulae to individual pixels in the high-res image. The output of the researchers’ system is a three-dimensional grid, 16 by 16 by 8. The 16-by-16 faces of the grid correspond to pixel locations in the source image; the eight layers stacked on top of them correspond to different pixel intensities. Each cell of the grid contains formulae that determine modifications of the color values of the source images.

That means that each cell of one of the grid’s 16-by-16 faces has to stand in for thousands of pixels in the high-res image. But suppose that each set of formulae corresponds to a single location at the center of its cell. Then any given high-res pixel falls within a square defined by four sets of formulae.

Roughly speaking, the modification of that pixel’s color value is a combination of the formulae at the square’s corners, weighted according to distance. A similar weighting occurs in the third dimension of the grid, the one corresponding to pixel intensity.

The researchers trained their system on a data set created by Durand’s group and Adobe Systems, the creators of Photoshop. The data set includes 5,000 images, each retouched by five different photographers. They also trained their system on thousands of pairs of images produced by the application of particular image-processing algorithms, such as the one for creating high-dynamic-range (HDR) images. The software for performing each modification takes up about as much space in memory as a single digital photo, so in principle, a cellphone could be equipped to process images in a range of styles.

Finally, the researchers compared their system’s performance to that of a machine-learning system that processed images at full resolution rather than low resolution. During processing, the full-res version needed about 12 gigabytes of memory to execute its operations; the researchers’ version needed about 100 megabytes, or one-hundredth as much. The full-resolution version of the HDR system took about 10 times as long to produce an image as the original algorithm, or 100 times as long as the researchers’ system.

“This technology has the potential to be very useful for real-time image enhancement on mobile platforms,” says Barron. “Using machine learning for computational photography is an exciting prospect but is limited by the severe computational and power constraints of mobile phones. This paper may provide us with a way to sidestep these issues and produce new, compelling, real-time photographic experiences without draining your battery or giving you a laggy viewfinder experience.”

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High school students receive 2017 MIT AgeLab OMEGA Scholarships for work with elders

On July 19, the MIT Age Lab, in partnership with the New England University Transportation Center and the AARP, presented the second annual OMEGA Scholarship awards to three accomplished young adults from the Boston area. Caroline Collins-Pisano of Noble and Greenough School in Dedham; Ella Houlihan of Lincoln-Sudbury Regional High School in Sudbury, and Anna Neumann of Newton South High School in Newton were each awarded a 2017 OMEGA Scholarship, which recognizes young people who work to foster intergenerational connections within their communities.

All three winners are leaders in school organizations that promote social connectivity between older adults and youth. Collins-Pisano is a founder of the Golden Dawgs, which organizes events including concerts, theatrical performances, and classes both at Noble and Greenough and local senior centers. Neumann is a cofounder of Crossing Generations at Newton South, which plans intergenerational social events, conducts oral history interviews with veterans, and organizes opportunities for young people to learn more about global aging trends. And Houlihan is a student leader of the Lincoln-Sudbury chapter of Bridges Together, which hosts an ongoing group of older adults for discussions and activities focused around a particular theme, such as resilience.

“While social isolation is profoundly personal, it has powerful public implications” said Joseph Coughlin, director of the MIT AgeLab. “Whether it’s saying hello to the older person who lives three doors over from you, or organizing an intergenerational field trip for an ice cream cone, it is the smallest human acts that bring neighborhoods, communities, and generations together.” Michael E. Festa, director of AARP Massachusetts, said, “Disrupting aging starts with younger people. This is about every generation in a community learning to grow old together.”

The OMEGA awards were presented at MIT’s Samberg Conference Center before the recipients’ parents and teachers, members of state nonprofit and government organizations, representatives from the Massachusetts Governor’s Council on Aging, MIT AgeLab researchers, and the AgeLab’s 85-plus Lifestyle Leaders Panel. The OMEGA Scholarships will provide $1,000 toward each recipient’s college tuition and an additional $1,000 to each recipient’s school to continue these outstanding intergenerational efforts.

OMEGA, which stands for Opportunities for Multigenerational Engagement, Growth, and Action, was created by the MIT AgeLab to support the development and growth of student programs and clubs that connect high school students with older adults. The MIT AgeLab is a multidisciplinary research program that works with business, government, and nongovernmental organizations to improve the quality of life of older people and those who care for them. AgeLab offers the OMEGA Scholarship with AARP and the U.S. Department of Transportation-sponsored New England University Transportation Center.

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How to court millennial shoppers? Lose the logo

The luxury handbag market is increasingly courting millennials. But they aren’t your typical shoppers.

“We discovered the new generation of consumers don’t really like to have a lot of logos,” says Wendy Wen ’09, the co-founder of Senreve, a luxury handbag company started last November. “They want something that’s high quality … but doesn’t scream flash.”

Unlike handbags that use a company logo as a key design element, Senreve’s line of designer bags limits branding. Their octopus logo does not even make an appearance on the handbag itself, and the Senreve company name is so subtle, it can be hard to locate.

The shift is intentional, and the result of hundreds of hours of consumer interviews that Wen and co-founder Coral Chung conducted before launching Senreve.

“Using the brand as a proxy for quality is futile,” says Wen, who earned her degree in economics and management. “Millennials now have information at their fingertips.”

That means Senreve’s customers can quickly learn about the Florentine craft workers who make their handbags and Wen's impetus for starting the company: frustration. As a fashion enthusiast working in finance, she would save her earnings to purchase high-end bags only to end up exasperated by their lack of compartments, their heavy weight, and their clunky straps.

Wen met Chung in business school and says the pair joined forces to capitalize on an “opportunity to create a new generation of luxury that defined the millennial that was not only beautiful but also functional.” Their company is solely online.

“I don’t have a store shelf to fill,” Wen says. “We can stock a few units of cool new colors like lilac, blush, or dandelion yellow, and if they sell out or do really well, we will put in a re-order.”

The tactic allows Senreve to sell many more colors than the three or four typically offered by brick-and-mortar competitors.

Being an online shop also affords Senreve an immediate window into customer buying patterns, which Wen insists improves service.

“You get so much more real-time data around what colors they’re clicking on, what questions they’re asking, and you can respond a lot faster,” she says.

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Division of Student Life introduces statement on diversity and inclusion

The MIT Division of Student Life (DSL) Staff Engagement Advisory Board (SEAboard) has introduced a statement intended to inform and guide staff on issues related to diversity and inclusion. The statement reads:

Our mission, as a division that is here for students, is to attract, hire, and retain talented staff members who represent the diversity of the MIT student body. We strive to provide all DSL staff members with the skills, tools, and support to create and maintain a respectful and responsive environment for living, teaching, and learning. We achieve this by:

• creating a climate of inclusion that reflects our division’s values and promotes an open exchange of ideas where each voice is heard;
• advancing DSL’s policies, practices, and programming for diversity, inclusion, and equity;
• promoting DSL staff equality of access, opportunity, representation, and participation within the division and beyond; and
• enhancing the awareness, knowledge, and skills of MIT community members through our work across campus.

The statement was inspired by recommendations made in 2015 by MIT’s Black Students Union on how to make MIT more diverse and inclusive. Suzy Nelson, vice president and dean for student life, suggested that SEABoard’s Diversity and Inclusion Committee consider how the recommendations could be applied to DSL. “The recommendations provide us with a roadmap for how we can improve our campus and how we can make our campus more welcoming and affirming for all,” Nelson said. “Because DSL has a strong hand in shaping the student experience, we need to be mindful of these recommendations and work to operationalize them.” 

Twelve volunteers to the Diversity and Inclusion Committee came from across DSL’s many disciplines and met in November 2016 with the goals of making the division a better place to work, and better for minority students. “When we came together for our first meeting, we talked about why folks were interested,” explained Libby Mahaffy, assistant director for conflict management and co-chair of the committee. “A lot of them said, ‘I wanted to do something that matters; that has impact.’” The committee was also co-chaired by Gerardo Garcia-Rios, assistant dean and interim co-director of student support services, and Lauren Haynie, former special assistant to the athletic director (who left MIT for a new position in June).

Before taking specific steps, the committee decided first to develop a statement on diversity and inclusion in DSL that would frame future discussions and work. They sought guidance and feedback on elements of a statement from students, staff, and faculty through a variety of channels, including email, webforms, and word of mouth. “It was a very robust feedback process,” said Mahaffy. “It really felt great that folks were thinking about it and talking about it.”

While the statement was written for DSL, the committee believes there will be community-wide impact. “When folks are happier at work, they’re happier with the students that they work with,” said Mahaffy. “It makes a difference for you to feel like you belong somewhere, because then you’ll treat others with that same kind of respect and belonging.”

“In a lot of ways, it’s aspirational,” added Rios. “It represents kind of what could be the best of DSL. We may not necessarily be there now, but it gives us a template for the future.”

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Hacking functional fabrics to aid emergency response

Hazardous environments such as disaster sites and conflict zones present many challenges for emergency response. But the new field of functional fabrics — materials modified to incorporate various sensors, connect to the internet, or serve multiple purposes, among other things — holds promise for novel solutions.

Over the weekend, MIT became a hotbed for developing those solutions.

A three-day hackathon on campus brought together students and researchers from MIT and around Boston who developed functional fabric concepts to solve major issues facing soldiers in combat or training, first responders, victims and workers in refugee camps, and many others. The event was hosted by the MIT Innovation Initiative, the Advanced Functional Fabrics of America (AFFOA) Institute, and MD5, a partnership between the U.S. Department of Defense (DoD) and a network of national research universities.

Participants pitched their ideas on Friday night. By Sunday afternoon, more than 20 teams stationed around the MIT Media Lab’s sixth floor had design mockups drawn on poster boards, algorithms and brainstorming notes scribbled on large sheets of hanging paper, and even hardware and software prototypes on display.

Two winning teams earned grand prizes of up to $15,000, courtesy of MD5. Remote Triage, formed by MIT students, designed an automated triage system for field medics, consisting of sensor-laden clothing that detects potential injury and a web platform that prioritizes care. The other team, Security Blanket, designed a double-sided, multipurpose blanket for people displaced from their homes, based on an idea from a Drexel University student.

Some other ideas included smart belts that passively detect radiation exposure in submarines; military gear fitted with radio-frequency identification tags to manage materials and improve packing efficiency; biometric-monitoring stickers that detect potential post-traumatic stress disorder symptoms; lightweight body armor designed to better protect the heart and neck; stress-detecting shirts that improve military training exercises; and uniforms made with materials and tiny fans that deliver cool and hot airflow across the body. All teams were invited to continue working with MD5.

“This is just the start,” Bill Kernick, technology and partnership development executive for MD5 told MIT News. “The idea of the hackathon is getting the sparks of these ideas moving and creating a relationship with these innovators, who may have not thought about working with DoD, to help solve some really hard problems.”

In that regard, Vladimir Bulović, co-director of the MIT Innovation Initiative and the Fariborz Maseeh (1990) Professor of Emerging Technology, said the hackathon embodies MIT’s goal of developing innovations for real-world applications. “As long as we can deliver impact that leads toward productive next steps, we have succeeded in our mission,” he said.

Through the hackathon, Bulović added, participants were also introduced to the newly launched AFFOA — a consortium of which MIT is a partner — and learned about the ever-growing possibilities of functional fabrics. “Fiber as a format that can deliver electronics, optics, photonics … is an entirely new platform that has not existed before,” he said. “It’s a new frontier.”

On Friday night, hackathon participants listened to talks from various experts — including military officers, first responders, and government representatives — who described major challenges they face in their fields. Participants brainstormed solutions, pitched their ideas to all attendees, and ultimately formed a total of 22 teams. Experts and mentors, from MIT and elsewhere, were on hand all weekend to help teams shape their ideas. (Some experts also joined individual teams.) On Sunday, a panel of judges — including representatives from industry, AFFOA, and MIT — chose 10 teams as finalists to pitch ideas, with two teams emerging as the big winners.

Some teams entered the hackathon with established ideas they wanted to refine. The finalist team OREverywhere, for instance, tweaked its augmented-reality (AR) headgear over the weekend to help field medics. The AR system displays biometric information collected from wearable sensors worn by soldiers and connects all medics on the field. A medic, for instance, can see when a soldier is injured, alert nearby medics, provide advice during care, and monitor everything via video feed — all while helping another soldier. During Sunday’s pitch round, the team presented a live demonstration.

Other teams developed their concepts entirely over the weekend. The MIT students of Remote Triage, who are all friends, landed on their winning idea during dinner, after hearing from an expert about problems with battlefield triage efficiency. “We came in with literally nothing. We weren’t even planning on pitching,” team member Aditi Gupta, a PhD student in the Harvard-MIT Program in Health Sciences and Technology, told MIT News.

In two days, the team of six, including a former military officer, designed a mockup of an automated triage system called VITAL. It includes a garment integrated with sensors that continuously monitor vital signs. Signals are sent to a machine-learning algorithm that determines the necessary order of care for injured soldiers, from least urgent to most urgent, color-coded as green, yellow, red, and black. Other features also help the medic determine the whereabouts of the soldier down and the location of their injury, among other things.

With the prize money and other resources from MD5, Gupta said the team now aims to design sensor-laden clothing and further develop the machine-learning algorithm that will power their platform. They’re meeting with MD5 next week to discuss options for moving forward.

Gupta was surprised at how much the team completed in a short time. Hackathons, she added, really help participants — especially tech-minded MIT students — find real-world applications for their ideas and people to help make those ideas a reality. “Hackathons are useful in opening your mind and seeing the bigger picture in terms of how your technology fits in society,” she says, “as well as meeting people out of your field that have knowledge and expertise you don’t.”

Christina Kara, a Drexel University student who manages a lab that researches functional fabrics, had a similar experience. After hearing a first responder talk about working with Hurricane Katrina victims — who were in desperate need of tarps and blankets, and suffered from bacterial skin infections — she pitched the winning concept behind Security Blanket.

Teaming up with that first responder and a few others, the group developed a multipurpose comfort blanket for refugee camps or disaster relief that consists of a waterproof, flexible, robust material on the outside. The inside is lined with antimicrobial, soft, and quick-drying microfibers. The blankets can roll out into a sleeping bag or fold into a backpack. Luminescent strips on the outside improve safety by increasing visibility at night, as well.

“In the five minutes we’ve talked to you, 100 people have been displaced in the world,” Kara said during her team’s pitch. “This is not a problem that’s going away. When we have something that’s fairly affordable, multiuse tool to empower them in their everyday life … you’re improving the experience of these individuals.”

After being announced a winner on Sunday, Kara was in shock, but excited to move forward with her idea, with help from MD5. “Being in a situation, where I have a problem to solve and think about was a new experience for me,” Kara told MIT News. “It was an amazing experience.”

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El nuevo puente Tappan Zee de Nueva York se abrirá al tráfico a finales de Agosto

Hace unos meses os mencionamos que acaban de completar la instalación de los 96 cables atirantados que conectaban más de 40 secciones de acero estructural en las cuatro torres principales de 127 metros del nuevo puente Tappan Zee de Nueva York

Ahora en el mes de Julio, los trabajadores del puente, se han centrado en las tareas de pavimentación, señalización, comprobación de las luces,etc. para tener preparado el puente el 25 de agosto y recibir 138.000 coches diarios en el primer tramo en dirección del Oeste hacia el Norte.

El nuevo puente significará reducir la congestión para los conductores una vez que esté finalizado plenamente en 2018 con la apertura del segundo tramo. Contará con ocho carriles de circulación (cuatro carriles para cada sentido), tendrá un sistemas de control del tráfico y un carril bus de cercanías desde el día en que se abra. Además incluirá un carril bici y senda peatonal.

A continuación os dejamos con la  noticia de la CBS donde a vista de pájaro podemos ver por medio de un drone la evolución actual del puente.

Una vez que esté finalizado el nuevo puente por completo, la vieja estructura será desmontada pieza a pieza y transportada por barco. Esto incluye la superestructura de acero del puente, la subestructura de hormigón, los paneles de cubierta de carretera de hormigón,el acero y las pilas.

LOS NÚMEROS DEL PUENTE

4: El número de carriles de tráfico en cada dirección.

4.9: La longitud del nuevo puente, en kilómetros
6: El número de puntos de descanso, en la ruta de uso compartido.
8: El número de torres de hormigón que ayudan a suspender el puente sobre la parte más profunda del río Hudson.
14: Kilómetros de cable que permanecen instalados antes de que se complete el puente.

27: El ancho, en metros, del tramo de Westchester.
30: La anchura, en metros, del alcance de Rockland.

42: La altura, en metros, del tramo principal hasta el agua.
50: Kilómetros de pilotes de cimentación.

128: La altura, en metros, de las torres principales.
134: El número de vigas en la parte superior de la que se asienta la cubierta de carretera, que se instalará una vez que el puente se completa en 2018.

183: La longitud, en metros, del canal principal.
192: El número de cables permanentes colgados de cada una de las ocho torres principales del puente.
366: La longitud, en metros, del tramo principal, torre a torre.

3600: Personas que han participado en el proyecto.
138.000: El número de coches que cruzan el Tappan Zee Bridge diariamente
230.000: Metros cúbicos de hormigón en el proyecto.

8.000.000: Horas de trabajos sumados.
99.000.000: Kilos de acero en el proyecto.
3.3 mil millones €: El costo total del nuevo puente Tappan Zee.



IMÁGENES

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