MIT Welcome Center opens in Kendall Square

The MIT Welcome Center opened this month in Building E38, just steps from the Kendall/MIT MBTA subway station in Cambridge, Massachusetts. Visitors and MIT community members can stop by the center for wayfinding and other information about campus and the local area. Later this fall, prospective students and their families can attend in-person information sessions in the center’s 200-seat auditorium, which will also be made available for use by the Cambridge community.

“This open, bright, and welcoming space allows us to craft an even better visit experience for our prospective students and their families,” says Stu Schmill, dean of admissions and student financial services. “Being in the heart of Kendall Square and sharing the space with MIT InnovationHQ, MIT Open Space Programming team, the Office of Sustainability, and others in E38 will enable visitors to experience the dynamic, open, and community-minded nature of MIT.”

A gift of Tina Moghadam and Hamid Moghadam ’77, SM ’78, the center was originally slated to launch in summer 2020, but the opening was delayed due to the pandemic. The center is the result of an iterative process guided by a working group made up of representatives from across the Institute, including the Innovation Initiative, MIT Admissions, the Office of the Executive Vice President and Treasurer (EVPT), Open Space Programming, the Institute Office of Communications, Campus Construction, Campus Planning, Institute Events, the MIT Museum, and the MIT Press.

“It’s exciting to see the center and open space come to life as part of MIT’s Kendall Square gateway,” says EVPT Glen Shor. “Visitors will quickly come to see what MIT is all about, and how to make their way around our vibrant campus.”

“Only at MIT”

In creating the center, a goal was for visitors to know right away they had entered MIT’s campus. The artwork, lighting, and interiors are inspired by the concept of “only at MIT,” evoking MIT’s eclectic culture.

The lobby’s “Welcome Wall” features a photo of MIT’s Great Dome, overlaid by the colorful doodles of artist Lydia Krasilnikova ’14, MEng’16, who also illustrated the MIT Admissions website and the first-year application.

The first floor’s rotating story wall currently showcases the work of the student group Borderline, which created art representing what it means to be an MIT student. When viewed with the Artive app, the mural is transformed into dynamic, animated images.

Also on display is Arthur Ganson’s delightful kinetic sculpture “Margot’s Cat.” Stepping on the foot pedal springs the sculpture to life, as a dollhouse-size chair moon-bounces over a cat figurine, evoking the convergence of engineering, creativity, and playfulness — a familiar triad at MIT.

The fabric frieze above the auditorium will soon feature a lighting installation by Soso Limited, an interactive agency founded by MIT alumni, that runs on Processing, a graphical programming language developed by MIT researchers.

And for visitors wanting to snap a photo of their visit to campus, a selfie wall with a three-dimensional MIT sign provides an Instagram-ready backdrop.

A community green space

Beyond the center’s large glass windows are two acres of open space with trees and plantings — a space for visitors to eat lunch, take a break from the urban environment, and enjoy the nature around them.

The area acts as an extension of the Infinite Corridor, connecting Kendall to the rest of campus. “We’ve already seen people running into each other, like they do in the Infinite, exchanging ideas and reconnecting,” explains Jessie Schlosser Smith, director of open space programming.

Since launching the space in August, Smith and her team have organized nearly a dozen free, public events, including movie nights, a Tuesday “Lunch Breaks” series with performances, talks, and hands-on activities, and Saturday morning programs geared toward families.

The programming brings activity into the public space and shows the MIT community’s wide range of experiences and interests, telling a fuller story and providing a window into an MIT that local community members might not know.

“Having this beautiful outdoor space has been amazing, precious, and useful during Covid times,” says Smith. “Partnering with local artists and nonprofit organizations, we are developing programs that foster inclusive interactions and community connections. Our Cambridge neighbors are encouraged to enjoy our public spaces. We want to create a welcoming and inclusive environment through our programming and broaden the reach of MIT.”

Earlier this month, local artist Silvia Lopez Chavez led a community art project where participants were asked to reflect on experiences, challenges, and hopes of the past year. Their reflections will be incorporated into a temporary mural that will be displayed on the building’s glass façade on Main Street that will be unveiled on Oct. 27.

“With the opening of the welcome center, open space, the MIT Press Bookstore, and later, the MIT Museum, the gateway area will soon live up to its promise of advancing Kendall’s trademark bump-and-connect vibe — with a focused emphasis on welcoming all from MIT, Cambridge, the region, and beyond,” says Sarah Gallop, co-director of MIT’s Office of Government and Community Relations.

The MIT Welcome Center is open to the public, Monday through Friday, 9 a.m. to 6 p.m., excluding MIT holidays. Visit openspace.mit.edu to learn about about upcoming MIT Open Space Programming events.

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Budding coders create apps aimed at real-world impact

How can computer science be used to help make the world a better place? It’s a lofty question, but one that drives the team behind MIT App Inventor, a virtual programming platform that allows budding programmers of all ages to create their own apps.

Following a year of disruption caused by the Covid-19 pandemic, the App Inventor team hosted its second annual virtual Appathon for Good this summer, a marathon-like event during which over 1,000 coders used the App Inventor platform to create apps aimed at helping people in communities around the world. Participants in this year’s Appathon ranged in age from 4 to 82 and hailed from 86 countries.

Hal Abelson, the Class of 1922 Professor in the Department of Electrical Engineering in Computer Science, explains that one of the goals behind the Appathon is to help underscore the importance of impact when it comes to designing new AI systems. Thanks to advances in computer science, he says, it is now possible for high school students to create mobile applications that help people with everything from accessing clean water to urban planning.

“We are blown away by what kids are doing this year and their visions for a better world,” says Abelson. “Kids are now using professional-grade tools to put themselves in the position of drivers of technology.”

From apps created to help improve mental health to food exchange platforms focused on alleviating hunger and systems that help users avoid zombies in a dystopian future, Appathon participants showcased how technology has the power to enable coders to make a significant difference in the world.

Mental health

The impact of lockdowns, school closures, and social isolation on the mental health of kids and teens has been a growing concern during the Covid-19 pandemic. In an effort to help facilitate communication between children and their parents, a U.S.-based team of youths and adults participating in the Appathon for Good developed Vividly, a platform that allows children to share their thoughts and feelings through a virtual intermediary.

“Nowadays technology is so integrated into all of our lives, and children and teens are growing up using technology as a whole other means of expression. This fact can be utilized in improving parent-child communication,” explains Bella Baidak, a 22-year-old graduate student who helped lead the Vividly team as a mentor, which took second place in the mixed youth and adult team category for their efforts.

“Oftentimes teens may feel more comfortable making a social media post about how they feel or texting a friend rather than having a face-to-face conversation with their parents,” Baidak adds. “When it comes to vulnerable topics, technology may be a more comfortable outlet for many teens. Though technology should definitely not be a replacement for face-to-face communication, an app like Vividly could certainly help break the ice.”

Sophia Cho, a 17-year-old student in the U.S., created a platform aimed at helping users maintain and improve their own mental health, based off her own experience using such techniques as meditation, exercise, goal-setting, and journaling. The app, named Mentallia, provides a way for people to track what they are doing to aid their mental well-being, and uses a points system to help motivate participation.

“I love computer science and making useful apps and programs. Many people also deal with a lot of stress daily, so I knew that by making the app I could help other people while also fulfilling one of the themes for the Appathon, which was computational action,” explains Cho.
“I plan on adding a machine learning aspect to Mentallia so that the app can find patterns between certain situations and the user’s emotions and physical symptoms, and give advice on what to do, more or less, to alleviate any distress.”

Inspired by a family friend with dementia, Louie Chiang, an 11-year-old student from Taiwan, developed the NoWorries app, which is focused on improving the quality of life for the elderly. The app features a memory game that users can play with their family photos.

“[When users] play the game, they can see the photos and bring back old memories to make them happy,” says Chiang of the inspiration for the game. He adds that in the future he hopes to “focus on helping elderly people by making more apps that can make their lives easier and happier.”

Hunger

A number of Appathon participants were also motivated to create platforms addressing hunger and facilitating access to food pantries. Communitry, a food exchange platform created by a team of youths and adults from the Philippines, was developed to serve as a hub for food pantries so that people in need can find assistance. The app is also aimed at connecting community organizers looking to establish local food resources. Communitry users can access a map to see established food pantries worldwide and to find directions for pantries near them.

Another app, dubbed Love Parcel, helps users find ways to get donated items to the people who need them. Love Parcel allows people to submit requests for needed items and for charity organizations to help them fulfill the need for specific items, such as food, clothing, or toys.

Cities of the future

Motivated by a desire to improve conditions for pedestrians in Hong Kong, Nathan Lam, a 19-year-old student in Hong Kong whose team worked out of the MIT Hong Kong Innovation Node, and his teammates developed an app that uses live data from busy streets to help traffic lights work better for pedestrians. Lam noted that as red-light running and jaywalking are common in Hong Kong, he and his teammates were inspired to make a meaningful impact on daily life by improving the city’s traffic light system.

“The Appathon presented us with the perfect opportunity to bring our idea to life and improve the community with our app,” Lam and his teammates explain. They add that they plan to implement several changes to their app in the coming months, such as “using a better networking device that supports a 5G connection to reduce the network latency in data transfer, improving intercommunication between traffic lights to increase the efficiency of complicated junctions, and incorporating a priority index to allow emergency vehicles to clear traffic more quickly.”

From traffic lights to visions of the future, some participants created platforms to help people survive in dystopian worlds. From a tracker that could be used to help track and avoid zombies to a platform that explores what life could be like if we live among aliens, and a community monitoring app for residents of the Moon, Appathon participants invented creative solutions to a myriad of futuristic challenges.

Whether or not a zombie tracker is needed in the future, the App Inventor team hopes that providing children and adults with the opportunity to create programs that can make a difference in the world around them will help to empower a whole new generation of computational action.

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MIT brings Campaign for a Better World to a successful finish

MIT has announced the conclusion of its Campaign for a Better World, which raised $6.24 billion to support the Institute’s work on some of the world’s most pressing challenges.

Altogether, 112,703 individuals and organizations contributed to the campaign, which was publicly launched in 2016 and formally ran from July 2011 to June 2021. Sixty-four percent of all donors were MIT alumni, while more than 56,000 donors made their first gift to MIT during the campaign.

“Everywhere I traveled throughout the campaign, I was struck by the energy and enthusiasm of our alumni and friends and by how deeply the ‘better world’ theme resonated with them,” says President L. Rafael Reif. “They understood instinctively that this is what MIT was made for. Thanks to the enthusiastic generosity of our donors at every scale, the campaign has already fueled vital advances to address some of the world's most urgent challenges — and I know the progress has only just begun.”

In early 2019, MIT increased the campaign’s original $5 billion fundraising goal to $6 billion.

“Philanthropy is a powerful change-maker,” says Julie A. Lucas, MIT’s vice president for resource development. “Our donors want to advance world-shaking, moonshot ideas that can change life as we know it, like when a machine-learning model plays a key role in developing a vaccine, or an exoplanet is discovered, or breakthroughs are made in carbon-free energy production. They do these things by making sure MIT has the resources to nurture talent, meet unexpected opportunities, and pursue bold ideas.”

Strengthening MIT at its core

During the campaign, MIT raised $239 million for scholarships, an increase of 36 percent compared to the prior decade. Scholarships are the foundation of MIT’s commitment to need-blind undergraduate admission and a component of the Institute’s ability to provide a full range of support for students who have earned their place at MIT.

Additionally, $531 million was raised toward fellowships for MIT’s graduate students, an increase of 105 percent over the prior decade. This includes 100 graduate fellowships in the School of Engineering and the School of Science created by the mathematical computing software company MathWorks, co-founded by Jack Little ’78.

To empower MIT’s faculty and tap the full potential of rising stars, 90 professorships were created during the campaign.

Unrestricted giving to MIT increased by 67 percent compared to the previous decade, as alumni and friends signaled their confidence in MIT by making gifts of critical resources that can be directed wherever they are most needed by the MIT community. The campaign’s unrestricted funding helped advance early-stage ideas, supply vital equipment, renew existing buildings, and supplement financial aid.

“MIT is a singular magnet for science and technology talent from around the world,” says W. Eric L. Grimson PhD ʼ80, chancellor for academic advancement and the Bernard M. Gordon Professor of Medical Engineering. “This campaign has put us on a firm footing. We have the resources to leverage the creativity of our faculty and students as they tackle the world's great problems. And that's only been possible through the support of our generous, farsighted donors.”

Advancing problem solving and discovery

Supported by the campaign, MIT scientists built on decades of research to advance mRNA vaccines to battle Covid-19, scanned space in search of planets beyond our solar system, and reached across disciplines to engage the era’s defining challenge, climate change. MIT researchers are unlocking the secrets of the brain and exploring the use of artificial intelligence (AI) to improve health. MIT innovators promoted entrepreneurial creativity and crafted new ways to share learning across the world.

“MIT needs to remain the preeminent institution that it is, where researchers, policymakers, engineers, entrepreneurs, and the scientists of the future are born,” says Maria Zuber, the Institute’s vice president for research and the E. A. Griswold Professor of Geophysics. “This would simply be impossible without philanthropic support. Every single mind can be the wellspring of something that can change the world, and we need every great idea that we can get.”

During the campaign, MIT announced the establishment of the MIT Stephen A. Schwarzman College of Computing, committed to addressing the global opportunities and challenges presented by the prevalence of computing and the rise of AI. An interdisciplinary hub for work in computer science, AI, data science, and the social and ethical responsibilities of computing, the college will be headquartered in a signature new building on MIT’s campus.

At the McGovern Institute for Brain Research, the Hock E. Tan and K. Lisa Yang Center for Autism Research was founded to support research on the genetic, biological, and neural bases of autism spectrum disorder, while the K. Lisa Yang and Hock E. Tan Center for Molecular Therapeutics in Neuroscience was launched as a major new research effort to change how we treat brain disorders. Both centers were made possible with commitments from Lisa Yang and Hock Tan ’75, SM ’75.

The MIT Quest for Intelligence was launched to discover the foundations of human and machine intelligence and develop technological tools to positively influence society. MIT.nano, a facility to make, measure, and image materials at the nanoscale, opened its doors at the center of campus. The Alana Down Syndrome Center was established to engage scientists and engineers in an effort to increase understanding of the biology and neuroscience of Down syndrome and improve the health, autonomy, and inclusion of people with this genetic condition.

The Schimmel Family Program for Life Sciences will support the Department of Biology’s Graduate Training Initiative and graduate students across MIT.

Endeavors supported by Community Jameel, the social enterprise organization founded and chaired by Mohammed Abdul Latif Jameel ’78, sought practical solutions to complex global problems. The Abdul Latif Jameel World Education Lab, an anchor of MIT Open Learning, serves learners in the developing world, especially women and girls underserved by education, and a growing displaced population that includes refugees, while the Abdul Latif Jameel Clinic for Machine Learning in Health aims to develop AI technologies to revolutionize the prevention, detection, and treatment of disease.

The King Climate Action Initiative, housed in MIT’s Abdul Latif Jameel Poverty Action Lab, rigorously studies programs reducing the effects of climate change on vulnerable populations, then works with policymakers to scale up the most successful interventions.

New spaces for collaboration, creativity, and innovation

Kendall Square, home to one of the world’s great concentrations of innovative companies and community organizations, continued to be transformed into a vibrant new gateway to MIT. The recently opened MIT InnovationHQ — which sits atop the newly created MIT Welcome Center and MIT Admissions — encompasses more than 25,000 square feet of space for innovation and entrepreneurship activities. A new residential tower provides 454 housing units for graduate students and families with children. The MIT Museum will soon take up residence on Main Street.

“Thinkers and doers, innovators and adopters, all are in proximity to and in direct contact with each other,” says Martin A. Schmidt SM ’83, PhD ’88, the Institute’s provost and the Ray and Maria Stata Professor of Electrical Engineering and Computer Science. “Innovation today is a contact sport that demands the continual interplay of people and ideas. This interplay is the hallmark of MIT. It's the driving impulse behind the incredible research happening and the incredible buildings this campaign has enabled.”

The Metropolitan Storage Warehouse is being converted into a modern hub for interdisciplinary design research and education, a new home for the School of Architecture and Planning, and a location for the largest community-wide makerspace on campus run by MIT Project Manus. A new music building targeted for completion in 2024 will relocate MIT’s conservatory-level music program to the West Campus area and consolidate many of its activities under a single roof. The 2017 premiere of the Theater Arts Building on Vassar Street provided the Institute with its first facility dedicated to the performing arts.

A renovation of the landmark Wright Brothers Wind Tunnel created the most advanced academic wind tunnel in the nation. Building 2, home of the Department of Mathematics, was dedicated as the Simons Building in honor of James H. ’58 and Marilyn Simons, whose gift enabled MIT to restore and renovate the landmark building.

Building 52, an Art Deco landmark on Memorial Drive that is the original home of the MIT Sloan School of Management and headquarters of the Department of Economics, was named for Morris ’52, SM ’53, ME ’55 and Sophie Chang, who made a gift to restore and renovate the building. The New Vassar undergraduate residence hall on Vassar Street, Building W46, opens up the West Campus and provides students with a central residential location.

Alumni in record numbers engaged with the Institute

Over the course of the campaign, 83 percent of alumni engaged with MIT through the MIT Alumni Association by making annual gifts to the Institute, attending alumni events, or logging on to the Infinite Connection, the online portal for alumni. More than 27,000 alumni volunteered, served on boards, and participated in regional clubs.

The MIT Campaign for a Better World global tour that debuted in October 2016 brought Institute leaders, faculty, and students to New York City, San Francisco, London, Hong Kong, and other cities where many alumni and supporters live and work. More than 11,650 alumni and friends attended, live or online.

“I have been grateful for the partnership and support of our alumni and friends from the very start of this campaign,” says President Reif. “Our mission calls on us to make a better nation and a better world. The campaign will help us do exactly that. To me, that will be its legacy.”

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The language of change

Ryan Conti came to MIT hoping to find a way to do good things in the world. Now a junior, his path is pointing toward a career in climate science, and he is preparing by majoring in both math and computer science and by minoring in philosophy.

Language for catalyzing change

Philosophy matters to Conti not only because he is interested in ethics — questions of right and wrong — but because he believes the philosophy of language can illuminate how humans communicate, including factors that contribute to miscommunication. “I care a lot about climate change, so I want to do scientific work on it, but I also want to help work on policy — which means conveying arguments well and convincing people so that change can occur,” he says.

Conti says a key reason he came to MIT was because the Institute has such a strong School of Humanities, Arts, and Social Sciences (MIT SHASS). “One of the big factors in my choosing MIT is that the humanities departments here are really, really good,” says Conti, who was named a 2021 Burchard Scholar in honor of his excellence in the Institute’s humanistic fields. “I was considering literature, writing, philosophy, linguistics, all of that.”

Revitalizing endangered indigenous languages

Within MIT SHASS, Conti has focused academically on the philosophy of language, and he is also personally pursuing another linguistic passion — the preservation and revitalization of endangered indigenous languages. Raised in Plano, Texas, Conti is a citizen of the Chickasaw Nation, which today has fewer than 50 first-language speakers left.

“I’ve been studying the language on my own. It’s something I really care about a lot, the entire endeavor of language revitalization,” says Conti, who credits his maternal grandmother with instilling his appreciation for his heritage. “She would always tell me that I should be proud of it,” he says. “As I got older and understood the history of things, the precarious nature of our language, I got more invested.” Conti says working to revitalize the Chickasaw language “could be one of the most important things I do with my life.”

Already, MIT has given him an opportunity — through the MIT Solve initiative — to participate in a website project for speakers of Makah, an endangered indigenous language of the Pacific Northwest. “The thrust at a high level is trying to use AI [artificial intelligence] to develop speech-to-text software for languages in the Wakashan language family,” he says. The project taught him a lot about natural language processing and automatic speech recognition, he adds, although his website design was not chosen for implementation.

Glacier dynamics, algorithms — and Quizbowl!

MIT has also given Conti some experience on the front lines of climate change. Through the Undergraduate Research Opportunities Program, he has been working in MIT’s Glacier Dynamics and Remote Sensing Group, developing machine learning algorithms to improve iceberg detection using satellite imagery. After graduation, Conti plans to pursue a PhD in climate science, perhaps continuing to work in glaciology.

He also hopes to participate in a Chickasaw program that pairs students with native speakers to become fluent. He says he sees some natural overlap between his two passions. “Issues of indigenous sovereignty and language preservation are inherently linked with climate change, because the effects of climate change fall unequally on poor communities, which are oftentimes indigenous communities,” he says.

For the moment, however, those plans still lie at least two years in the future. In the meantime, Conti is having fun serving as vice president of the MIT Quizbowl Team, an academic quiz team that competes across the region and often participate in national tournaments. What are Conti’s competition specialties? Literature and philosophy.
 

Story prepared by MIT SHASS Communications
Editor, Designer: Emily Hiestand, Communications Director
Senior Writer: Kathryn O'Neill, Associate News Manager

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3 Questions: Paula Hammond and Tim Jamison on graduate student advising and mentoring

Launched in June, the MIT Ad Hoc Committee on Graduate Advising and Mentoring is aimed at delivering a strategic plan to guide and inform the development of effective mentoring policies and programs that would be implemented at the Institute. Made up of 10 graduate students and 11 other members representing staff and faculty, the committee plans to include elements of the recommendations provided in a 2019 report from the National Academies of Sciences, Engineering and Medicine (NASEM) on the "Science of Effective Mentorship in STEMM."

Here, committee co-chairs Paula Hammond (Institute Professor and head of the Department of Chemical Engineering) and Tim Jamison (the Robert R. Taylor Professor of Chemistry and associate provost) discuss the committee’s origin and the work already underway across campus, and offer insight into the future of advising and mentoring at MIT.

Q: What motivated the creation of this committee? 

Hammond: Effective graduate advising and mentoring are essential components of our mission as educators at MIT. Our work as a committee is timely and significant as we face a national reckoning on issues of sexual harassment and assault, structural racism, and misogyny. It is a clear opportunity for a change in culture and a shift in power dynamics. It’s with this context in mind that our work will support the imperative that all graduate students exit their programs with technical knowledge and confidence, and ownership of their research skills, and the practical tools they need to advance in the world. Students can achieve these through successful mentorship experiences. 

As a department head, faculty often tell me there is a lack of sufficient guidance and uniform messaging on how to provide valuable mentoring experiences for their graduate students. We know faculty need access to tools and other resources to cultivate their mentoring skills and help them address difficult mentoring situations when they arise. 

With the development and implementation of programs, resources, and policies that support and incentivize excellence in advising and mentoring, we can successfully create environments that meet our graduate students’ needs so they may prosper. In turn, the knowledge and innovations that stem from our research groups will also thrive. For faculty, their work environments will improve, and they will achieve a greater sense of fulfillment in their roles as advisors and mentors. Overall, effective mentorship benefits everyone, and this has been an expressed need on both sides. 

Jamison: Several initiatives across campus have led up to the efforts of this ad hoc committee. For example, the Academic and Organizational Relationships (AOR) Working Group developed a series of recommendations in response to the National Academies report on the "Sexual Harassment of Women: Climate, Culture, and Consequences in Academic Sciences, Engineering, and Medicine." As co-chairs of the AOR Working Group, Paula and I worked with the committee members to develop recommendations to minimize the vulnerabilities in dependent professional relationships such as graduate students and faculty advisors. 

In another initiative, the Academic Council approved a revision to Policies and Procedures 3.2, Tenure Process in fall 2020. This revision made excellence in mentoring and advising a criterion of tenure review. 

In April 2021, Task Force 2021 and Beyond entered its second phase. One of the Refinement and Implementation Committees of this Task Force issued a proposal to review and recommend ways to enhance graduate advising and mentoring effectiveness. 

Also in April, members of the Graduate Student Council (GSC) published a campus climate survey, which provided the Institute with recommendations about improving mentoring experiences, including establishing communication channels for students. We are grateful that two of the graduate students involved in conducting this GSC survey are now serving on this ad hoc committee. In June 2021, shortly after the committee first launched, the Graduate Womxn at MIT (gwaMIT) also issued a report of its findings and recommendations to improve the graduate experiences of women based on a series of focus group discussions among female MIT graduate students.

Q: What has the committee accomplished so far?

Jamison: Since the launch of the committee in June, our efforts have centered on creating the framework that will guide the development of MIT’s Strategic Plan on Graduate Advising and Mentoring. We developed our mission and vision statements and also established the strategic plan’s draft goals and objectives. These elements were informed by the findings of the Graduate Student Council survey and the gwaMIT report, as well as by the recommendations of the 2019 NASEM report on the science of effective mentorship. Recently, we launched a new website, which provides a summary of our charge and committee members, and will be used as one channel to provide updates to and feedback from the MIT community. 

Hammond: Much of the strategic plan framework we developed thus far complements many ongoing efforts across the Institute. In 2020, the School of Engineering worked closely with the Center for the Improvement of Mentoring Experiences in Research (CIMER) to offer a pilot workshop using theoretically-grounded, evidence-based, and culturally-responsive training interventions and investigations for new faculty. The school designed the workshop to accelerate the acquisition of mentoring insights, address best practices, and cultivate productive mentee-mentor relationships. The Institute scaled a version of this workshop for all new faculty beginning this fall. The Institute also recently launched a transitional support program for graduate students who wish to change research advisors or groups. And, last but not least, the Office of Graduate Education continually announces their Committed to Caring faculty members in an ongoing celebration of MIT faculty members who go above and beyond to make an impact in the lives of graduate students.

Q: Looking ahead, what do you anticipate will be the most important impacts of this committee?

Hammond: A key focus of our efforts is creating an Institute-wide vision that cultivates a culture of excellence in advising and mentoring at MIT. We need a vision that fosters the well-being of, the high-quality research by, and the professional development of all graduate students and faculty. By establishing the necessary infrastructure to evaluate and improve advising and mentoring at the individual, department, school, and Institute levels, we will successfully support a rewarding mentoring experience for all.

Jamison: Mentoring and advising are fundamental responsibilities of our faculty. The greater their mentoring skills and the more they serve as positive influences and role models, the better the experience and greater the success of our graduate students in their professional pursuits. Moreover, the more successful the graduate students are, the more the faculty will also benefit. I believe firmly that this phenomenon — a “virtuous cycle of mentorship” — can and will be experienced by even more members of our community.  That is, by improving the advising and mentoring of our graduate students, we will surely see powerful, positive long-term impacts on both graduate education and the Institute’s research enterprise.

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Zeroing in on the origins of Earth’s “single most important evolutionary innovation”

Some time in Earth’s early history, the planet took a turn toward habitability when a group of enterprising microbes known as cyanobacteria evolved oxygenic photosynthesis — the ability to turn light and water into energy, releasing oxygen in the process.

This evolutionary moment made it possible for oxygen to eventually accumulate in the atmosphere and oceans, setting off a domino effect of diversification and shaping the uniquely habitable planet we know today.  

Now, MIT scientists have a precise estimate for when cyanobacteria, and oxygenic photosynthesis, first originated. Their results appear today in the Proceedings of the Royal Society B.

They developed a new gene-analyzing technique that shows that all the species of cyanobacteria living today can be traced back to a common ancestor that evolved around 2.9 billion years ago. They also found that the ancestors of cyanobacteria branched off from other bacteria around 3.4 billion years ago, with oxygenic photosynthesis likely evolving during the intervening half-billion years, during the Archean Eon.

Interestingly, this estimate places the appearance of oxygenic photosynthesis at least 400 million years before the Great Oxidation Event, a period in which the Earth’s atmosphere and oceans first experienced a rise in oxygen. This suggests that cyanobacteria may have evolved the ability to produce oxygen early on, but that it took a while for this oxygen to really take hold in the environment.

“In evolution, things always start small,” says lead author Greg Fournier, associate professor of geobiology in MIT’s Department of Earth, Atmospheric and Planetary Sciences. “Even though there’s evidence for early oxygenic photosynthesis — which is the single most important and really amazing evolutionary innovation on Earth — it still took hundreds of millions of years for it to take off.”

Fournier’s MIT co-authors include Kelsey Moore, Luiz Thiberio Rangel, Jack Payette, Lily Momper, and Tanja Bosak.

Slow fuse, or wildfire?

Estimates for the origin of oxygenic photosynthesis vary widely, along with the methods to trace its evolution.

For instance, scientists can use geochemical tools to look for traces of oxidized elements in ancient rocks. These methods have found hints that oxygen was present as early as 3.5 billion years ago — a sign that oxygenic photosynthesis may have been the source, although other sources are also possible.

Researchers have also used molecular clock dating, which uses the genetic sequences of microbes today to trace back changes in genes through evolutionary history. Based on these sequences, researchers then use models to estimate the rate at which genetic changes occur, to trace when groups of organisms first evolved. But molecular clock dating is limited by the quality of ancient fossils, and the chosen rate model, which can produce different age estimates, depending on the rate that is assumed.

Fournier says different age estimates can imply conflicting evolutionary narratives. For instance, some analyses suggest oxygenic photosynthesis evolved very early on and progressed “like a slow fuse,” while others indicate it appeared much later and then “took off like wildfire” to trigger the Great Oxidation Event and the accumulation of oxygen in the biosphere.

“In order for us to understand the history of habitability on Earth, it’s important for us to distinguish between these hypotheses,” he says.

Horizontal genes

To precisely date the origin of cyanobacteria and oxygenic photosynthesis, Fournier and his colleagues paired molecular clock dating with horizontal gene transfer — an independent method that doesn’t rely entirely on fossils or rate assumptions.

Normally, an organism inherits a gene “vertically,” when it is passed down from the organism’s parent. In rare instances, a gene can also jump from one species to another, distantly related species. For instance, one cell may eat another, and in the process incorporate some new genes into its genome.

When such a horizontal gene transfer history is found, it’s clear that the group of organisms that acquired the gene is evolutionarily younger than the group from which the gene originated. Fournier reasoned that such instances could be used to determine the relative ages between certain bacterial groups. The ages for these groups could then be compared with the ages that various molecular clock models predict. The model that comes closest would likely be the most accurate, and could then be used to precisely estimate the age of other bacterial species — specifically, cyanobacteria.

Following this reasoning, the team looked for instances of horizontal gene transfer across the genomes of thousands of bacterial species, including cyanobacteria. They also used new cultures of modern cyanobacteria taken by Bosak and Moore, to more precisely use fossil cyanobacteria as calibrations. In the end, they identified 34 clear instances of horizontal gene transfer. They then found that one out of six molecular clock models consistently matched the relative ages identified in the team’s horizontal gene transfer analysis.

Fournier ran this model to estimate the age of the “crown” group of cyanobacteria, which encompasses all the species living today and known to exhibit oxygenic photosynthesis. They found that, during the Archean eon, the crown group originated around 2.9 billion years ago, while cyanobacteria as a whole branched off from other bacteria around 3.4 billion years ago. This strongly suggests that oxygenic photosynthesis was already happening 500 million years before the Great Oxidation Event (GOE), and that cyanobacteria were producing oxygen for quite a long time before it accumulated in the atmosphere.

The analysis also revealed that, shortly before the GOE, around 2.4 billion years ago, cyanobacteria experienced a burst of diversification. This implies that a rapid expansion of cyanobacteria may have tipped the Earth into the GOE and launched oxygen into the atmosphere.

Fournier plans to apply horizontal gene transfer beyond cyanobacteria to pin down the origins of other elusive species.

“This work shows that molecular clocks incorporating horizontal gene transfers (HGTs) promise to reliably provide the ages of groups across the entire tree of life, even for ancient microbes that have left no fossil record … something that was previously impossible,” Fournier says. 

This research was supported, in part, by the Simons Foundation and the National Science Foundation.

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Taylor Perron receives 2021 MacArthur Fellowship

Taylor Perron, professor of geology and associate department head for education in MIT’s Department of Earth, Atmospheric, and Planetary Sciences, has been named a recipient of a 2021 MacArthur Fellowship.

Often referred to as “genius grants,” the fellowships are awarded by the John D. and Catherine T. MacArthur Foundation to talented individuals in a variety of fields. Each MacArthur fellow receives a $625,000 stipend, which they are free to use as they see fit. Recipients are notified by the foundation of their selection shortly before the fellowships are publicly announced.

“After I had absorbed what they were saying, the first thing I thought was, I couldn’t wait to tell my wife, Lisa,” Perron says of receiving the call. “We’ve been a team through all of this and have had a pretty incredible journey, and I was just eager to share that with her.”

Perron is a geomorphologist who seeks to understand the mechanisms that shape landscapes on Earth and other planets. His work combines mathematical modeling and computer simulations of landscape evolution; analysis of remote-sensing and spacecraft data; and field studies in regions such as the Appalachian Mountains, Hawaii, and the Amazon rainforest to trace how landscapes evolved over time and how they may change in the future.

“If we can understand how climate and life and geological processes have interacted over a long time to create the landscapes we see now, we can use that information to anticipate where the landscape is headed in the future,” Perron says.

His group has developed models that describe how river systems generate intricate branching patterns as a result of competing erosional processes, and how climate influences erosion on continents, islands, and reefs.

Perron has also applied his methods beyond Earth, to retrace the evolution of the surfaces of Mars and Saturn’s moon Titan. His group has used spacecraft images and data to show how features on Titan, which appear to be active river networks, were likely carved out by raining liquid methane. On Mars, his analyses have supported the idea that the Red Planet once harbored an ocean and that the former shoreline of this Martian ocean is now warped as a result of a shift in the planet’s spin axis.

He is continuing to map out the details of Mars and Titan’s landscape histories, which he hopes will provide clues to their ancient climates and habitability.

“I think answers to some of the big questions about the solar system are written in planetary landscapes,” Perron says. “For example, why did Mars start off with lakes and rivers, but end up as a frozen desert? And if a world like Titan has weather like ours, but with a methane cycle instead of a water cycle, could an environment like that have supported life? One thing we try to do is figure out how to read the landscape to find the answers to those questions.”

Perron has expanded his group’s focus to examine how changing landscapes affect biodiversity, for instance in Appalachia and in the Amazon — both freshwater systems that host some of the most diverse populations of life on the planet.

“If we can figure out how changes in the physical landscape may have generated regions of really high biodiversity, that should help us learn how to conserve it,” Perron says.

Recently, his group has also begun to investigate the influence of landscape evolution on human history. Perron is collaborating with archaeologists on projects to study the effect of physical landscapes on human migration in the Americas, and how the response of rivers to ice ages may have helped humans develop complex farming societies in the Amazon.

Looking ahead, he plans to apply the MacArthur grant toward these projects and other “intellectual risks” — ideas that have potential for failure but could be highly rewarding if they succeed. The fellowship will also provide resources for his group to continue collaborating across disciplines and continents.

“I’ve learned a lot from reaching out to people in other fields — everything from granular mechanics to fish biology,” Perron says. “That has broadened my scientific horizons and helped us do innovative work. Having the fellowship will provide more flexibility to allow us to continue connecting with people from other fields and other parts of the world.”

Perron holds a BA in earth and planetary sciences and archaeology from Harvard University and a PhD in earth and planetary science from the University of California at Berkeley. He joined MIT as a faculty member in 2009.

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Citizens emerge from the slums

Do the world’s nearly 1 billion urban poor, who subsist without legal housing, reliable water and sewer infrastructure, and predictable employment, lack political engagement as well?

Ying Gao does not buy the claim by many social scientists that social and economic marginalization necessarily means political marginalization.

“My results contradict the prevailing wisdom about slums and the political behaviors they are believed to foster,” says Gao, a doctoral student in political science. “I’m discovering that people do not participate less in politics (by voting), in labor markets (by getting jobs), or in social activities (by being active in community groups), just because they lack legal housing.”

Gao’s dissertation project focuses on Indonesia and plumbs a massive dataset tracking a representative sample of 30,000 individuals over 20 years. Her initial findings reveal “a kind of shared urban political culture that is more subtle and interesting than unconditional theories of marginalization would suggest.”

A politically active urban populace, previously unacknowledged and neglected, could prove consequential in the efforts of developing nations to improve the lives of the poor. This is an increasingly urgent matter, Gao says, as developing cities big and small swell with new residents and struggle to meet their needs.

With a background in urban studies and planning and international development, Gao hopes her continued analysis and research will point to public policy interventions that prove useful to governments and aid organizations.

Poverty, but not always a trap

At the heart of Gao’s dissertation research lies the question: In cities of the developing world, do citizens in informal (unregulated) housing or jobs participate in politics differently from those situated in legal housing or employment arrangements?

“The common narrative is that when you move to a slum, there is less access to good services, and it’s harder to get good jobs, which leads to even less social mobility,” says Gao. “This poverty trap story also suggests that under such conditions, where people don’t see much public service because the government is spending more time in places better off, marginalized citizens don’t have as much incentive to vote and demand better services.”

Gao set out to test the premise of these stories, drawing on fine-grained quantitative resources. She seized on the Indonesian Family Life Survey, conducted between 1993 and 2014. “These are high-quality, underutilized datasets that allow me to tease out housing conditions, connect them to social and political outcomes, and enable me to talk about slums and their effects on average people in a way that’s chronological and different from one-off qualitative studies,” says Gao.

Gao also relied on her own fieldwork involving informal workers in Jakarta — motorcycle delivery drivers — conducted in 2017 and funded by MIT GOV/LAB and MIT D-Lab. During this research, she explored the differences between areas of the sprawling megacity populated by informal workers residing in informal housing. Gao learned that many of these laborers grouped themselves into cooperative associations, where they could advocate for wages and project “a sense of influence beyond their members.”

Analyzing her varied datasets, a process still underway, Gao finds that Indonesian families move fluidly between formal and unregulated housing and “are not marginalized,” she says. “They are more ordinary than we might have thought, being active in labor markets, and are as socially engaged in their communities as people in good housing.” This is in contrast, Gao notes, “to what we know about people in poor housing and disadvantaged neighborhoods in rich countries, who on average have lower opportunities for social association.”

Her studies have yielded additional insights into what makes slums livable for people who experience them: residents form self-help social groups, including rotating savings and credit associations, “where people pool money and everyone draws on that pool once in a while.” At the height of the Covid-19 pandemic, Gao ran an original online survey of informal workers across different job sectors in Indonesia, and found that these small committee groups “had a big influence in encouraging people to comply with government lockdown policies.”

If the urban poor are indeed engaged citizens, with neighborhood and worker-based associations, and able to cooperate across ethnic or religious differences, can governments and aid agencies find productive measures for working together with them to improve their quality of life?

In the final phase of her dissertation, Gao will run surveys in Indonesia to examine if public policy interventions can make a positive impact on the lives of urban poor. She will be looking specifically at whether an Indonesian participatory slum-upgrading program leads to better infrastructure by enhancing the political capacity of community leaders in informal communities.

Place and political identity

The specific ways a place shapes identity has long fascinated Gao. Born in China but raised in Japan, her bicultural lens made her acutely aware of “how people develop a sense of belonging to a place and how that can have big political consequences.”

Gao studied international relations at Georgetown University. But her interest began turning toward international development after graduation, when she spent several years at financial firms in Japan, and later with the UN Human Settlements Programme, working on problems of sustainable urban development in low-income countries in Asia. “These regions were so dynamic because of all the people moving to cities,” she says. “Urbanization is one of the biggest trends of humanity, and presents enormous opportunity and risk.”

Intent on understanding how cities cater to the welfare of residents, Gao earned a master’s degree from MIT’s Department of Urban Studies and Planning in 2014. It was there that she homed in on unregulated housing and the informal economy as robust topics for academic exploration, and as potent targets for public policy that could change people’s lives.

Gao was drawn to MIT’s political science doctoral program by its tradition of “research that goes against the grain, which looks at how people actually live in developing societies and questions how things are done in the field of development.” She hopes to follow in the footsteps of a “long lineage of engaged women scholars” at the program and across the Institute, such as thesis committee member Lily Tsai, Ford Professor of Political Science.

“I want to move between research and policy contributions, continuing to work on questions that lie at the intersection of urbanization and development,” she says. “How can developing nations solve the physical problems of inadequate housing in a way that could improve relations between citizens and government, so that poor urban citizens can participate politically and lift themselves up?”

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Making roadway spending more sustainable

The share of federal spending on infrastructure has reached an all-time low, falling from 30 percent in 1960 to just 12 percent in 2018.

While the nation’s ailing infrastructure will require more funding to reach its full potential, recent MIT research finds that more sustainable and higher performing roads are still possible even with today’s limited budgets.

The research, conducted by a team of current and former MIT Concrete Sustainability Hub (MIT CSHub) scientists and published in Transportation Research D, finds that a set of innovative planning strategies could improve pavement network environmental and performance outcomes even if budgets don’t increase.

The paper presents a novel budget allocation tool and pairs it with three innovative strategies for managing pavement networks: a mix of paving materials, a mix of short- and long-term paving actions, and a long evaluation period for those actions.

This novel approach offers numerous benefits. When applied to a 30-year case study of the Iowa U.S. Route network, the MIT CSHub model and management strategies cut emissions by 20 percent while sustaining current levels of road quality. Achieving this with a conventional planning approach would require the state to spend 32 percent more than it does today. The key to its success is the consideration of a fundamental — but fraught — aspect of pavement asset management: uncertainty.

Predicting unpredictability

The average road must last many years and support the traffic of thousands — if not millions — of vehicles. Over that time, a lot can change. Material prices may fluctuate, budgets may tighten, and traffic levels may intensify. Climate (and climate change), too, can hasten unexpected repairs.

Managing these uncertainties effectively means looking long into the future and anticipating possible changes.

“Capturing the impacts of uncertainty is essential for making effective paving decisions,” explains Fengdi Guo, the paper’s lead author and a departing CSHub research assistant.

“Yet, measuring and relating these uncertainties to outcomes is also computationally intensive and expensive. Consequently, many DOTs [departments of transportation] are forced to simplify their analysis to plan maintenance — often resulting in suboptimal spending and outcomes.”

To give DOTs accessible tools to factor uncertainties into their planning, CSHub researchers have developed a streamlined planning approach. It offers greater specificity and is paired with several new pavement management strategies.

The planning approach, known as Probabilistic Treatment Path Dependence (PTPD), is based on machine learning and was devised by Guo.

“Our PTPD model is composed of four steps,” he explains. “These steps are, in order, pavement damage prediction; treatment cost prediction; budget allocation; and pavement network condition evaluation.”

The model begins by investigating every segment in an entire pavement network and predicting future possibilities for pavement deterioration, cost, and traffic.

“We [then] run thousands of simulations for each segment in the network to determine the likely cost and performance outcomes for each initial and subsequent sequence, or ‘path,’ of treatment actions,” says Guo. “The treatment paths with the best cost and performance outcomes are selected for each segment, and then across the network.”

The PTPD model not only seeks to minimize costs to agencies but also to users — in this case, drivers. These user costs can come primarily in the form of excess fuel consumption due to poor road quality.

“One improvement in our analysis is the incorporation of electric vehicle uptake into our cost and environmental impact predictions,” Randolph Kirchain, a principal research scientist at MIT CSHub and MIT Materials Research Laboratory (MRL) and one of the paper’s co-authors. “Since the vehicle fleet will change over the next several decades due to electric vehicle adoption, we made sure to consider how these changes might impact our predictions of excess energy consumption.”

After developing the PTPD model, Guo wanted to see how the efficacy of various pavement management strategies might differ. To do this, he developed a sophisticated deterioration prediction model.

A novel aspect of this deterioration model is its treatment of multiple deterioration metrics simultaneously. Using a multi-output neural network, a tool of artificial intelligence, the model can predict several forms of pavement deterioration simultaneously, thereby, accounting for their correlations among one another.

The MIT team selected two key metrics to compare the effectiveness of various treatment paths: pavement quality and greenhouse gas emissions. These metrics were then calculated for all pavement segments in the Iowa network.

Improvement through variation

 The MIT model can help DOTs make better decisions, but that decision-making is ultimately constrained by the potential options considered.

Guo and his colleagues, therefore, sought to expand current decision-making paradigms by exploring a broad set of network management strategies and evaluating them with their PTPD approach. Based on that evaluation, the team discovered that networks had the best outcomes when the management strategy includes using a mix of paving materials, a variety of long- and short-term paving repair actions (treatments), and longer time periods on which to base paving decisions.

They then compared this proposed approach with a baseline management approach that reflects current, widespread practices: the use of solely asphalt materials, short-term treatments, and a five-year period for evaluating the outcomes of paving actions.

With these two approaches established, the team used them to plan 30 years of maintenance across the Iowa U.S. Route network. They then measured the subsequent road quality and emissions.

Their case study found that the MIT approach offered substantial benefits. Pavement-related greenhouse gas emissions would fall by around 20 percent across the network over the whole period. Pavement performance improved as well. To achieve the same level of road quality as the MIT approach, the baseline approach would need a 32 percent greater budget.

“It’s worth noting,” says Guo, “that since conventional practices employ less effective allocation tools, the difference between them and the CSHub approach should be even larger in practice.”

Much of the improvement derived from the precision of the CSHub planning model. But the three treatment strategies also play a key role.

“We’ve found that a mix of asphalt and concrete paving materials allows DOTs to not only find materials best-suited to certain projects, but also mitigates the risk of material price volatility over time,” says Kirchain.

It’s a similar story with a mix of paving actions. Employing a mix of short- and long-term fixes gives DOTs the flexibility to choose the right action for the right project.

The final strategy, a long-term evaluation period, enables DOTs to see the entire scope of their choices. If the ramifications of a decision are predicted over only five years, many long-term implications won’t be considered. Expanding the window for planning, then, can introduce beneficial, long-term options.

It’s not surprising that paving decisions are daunting to make; their impacts on the environment, driver safety, and budget levels are long-lasting. But rather than simplify this fraught process, the CSHub method aims to reflect its complexity. The result is an approach that provides DOTs with the tools to do more with less.

This research was supported through the MIT Concrete Sustainability Hub by the Portland Cement Association and the Ready Mixed Concrete Research and Education Foundation.

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Counting cells may shed light on how cancer spreads

As tumors grow within an organ, they also release cells that enter the bloodstream. These cells can travel to other organs, seeding new tumors called metastases.

MIT engineers have now developed a technique that, for the first time, allows them to measure the generation rate of these circulating tumor cells (CTCs) in mice. Their approach, which also reveals how long CTCs survive once released into the bloodstream, could help scientists learn more about how different types of cancers spread through the body.

“By exchanging blood between mice while counting CTCs in real-time, we obtained a direct measurement of how quickly CTCs enter the circulation and how long it takes before they’re cleared,” says Scott Manalis, the David H. Koch Professor of Engineering in the departments of Biological Engineering and Mechanical Engineering, a member of the Koch Institute for Integrative Cancer Research, and the senior author of the study.

Using their new system, the researchers were able to study CTCs from pancreatic tumors as well as two types of lung tumors.

Graduate student Alex Miller and Bashar Hamza PhD ’20, a Koch Institute visiting scientist, are the lead authors of the paper, which appears today in Nature Communications.

Capturing rare cells

Circulating tumor cells are rare in patients: One milliliter of blood might contain between one and 10 such cells. In recent years, researchers have devised strategies to capture these elusive cells, which can yield a great deal of information about a patient’s tumor, and even help doctors track how a tumor is responding to treatment.

“Circulating tumor cells are attractive because you can get them from blood and they provide a window into the tumor. It’s a lot easier than biopsying the tumor,” Manalis says.

In mice, CTCs are even more difficult to find because mice only have a little more than 1 milliliter of blood. Being able to study CTCs in mice could help researchers answer many outstanding questions about how rapidly these cells are shed by tumors, how long they survive in circulation, and how efficiently they seed new tumors, Manalis says.

To try to answer some of those questions, Manalis and his students designed a system that lets them remove blood from a mouse with a tumor and flow it into a healthy mouse. Through a separate tube, blood from the healthy mouse flows back to the tumor-bearing mouse. The system includes two cell-counters (one for each mouse) that detect and remove circulating tumor cells from the blood.

Using this setup, the researchers can analyze all of the blood from each mouse in less than an hour. After determining the concentration of CTCs in the bloodstream of the tumor-bearing mouse and of the healthy mouse, they can calculate the rate at which CTCs are generated in the tumor-bearing mouse. They can also calculate the half-life of the cells — a measure of how long they survive in the bloodstream before being cleared by the body.

Working with members of the Jacks lab in the Koch Institute, the researchers used the system to study mice with three different types of tumors: pancreatic cancer, small cell lung cancer, and non-small cell lung cancer.

They found that the half-life of CTCs was fairly similar between the three types of tumors, with values ranging from 40 seconds to about 250 seconds. However, the generation rates showed much more variability between different tumor types. Small cell lung tumors, which are known to be aggressively metastatic, could shed more than 100,000 CTCs per hour, while non-small cell lung tumors and pancreatic tumors shed as few as 60 CTCs per hour.

Previous studies that relied on injecting tumor cells from cell lines cultivated in the lab have found that those cells had a half-life of only a few seconds in the bloodstream, but the new results from Manalis’ lab suggest that endogenous CTCs actually persist much longer than that.

Generating metastases

The researchers also showed that the healthy mice that received CTCs later developed metastases, even after only exchanging a few thousand CTCs. They found that CTCs from small-cell lung tumors formed metastases in the livers of the recipient healthy mice, just as they did in the mice where the tumors originally formed.

“What we realized was that these CTCs that we’re injecting into the healthy recipient mouse start to grow and create metastases that we can detect after a couple of months,” Hamza says. “That was exciting to observe because it validated that our blood-exchange technique can also be used to gently inject a viable CTC sample in its native blood environment without having to enrich it using harsh in vitro techniques.”

Using this approach, researchers now hope to study how different drug treatments influence CTC levels. “With this system, we can look at real-time concentration of CTCs, so we can perform a drug treatment and look at how it is affecting half-life time and generation rate,” Miller says.

The researchers also plan to study other types of cancers, including blood cancers such as leukemias and lymphomas, using this system. The technique could also be used to study the circulation dynamics of other kinds of cells, including immune cells such as neutrophils and natural killer cells.

The research was funded by the Virginia and D.K. Ludwig Fund for Cancer Research, the Cancer Systems Biology Consortium, the National Cancer Institute, the Pew-Stewart Scholars Program for Cancer Research, a Sloan Fellowship in Chemistry, and the National Institutes of Health.

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Lindsey Backman: Biochemist, mentor, and advocate

Raised in Tampa, Florida, Lindsey Backman takes pride in her family’s history and its role in the vibrant Cuban American community there. She remembers the weekends she would spend as a kid, getting café con leche with her grandparents and dancing in the studio with her friends. The cultural experiences she shared with friends, family, and  neighbors growing up helped her feel comfortable being herself while growing up, and showed her from an early age how valuable a welcoming community could be to a person’s success.

Backman went on to pursue her BS in chemistry at the University of Florida. Surrounded by a diverse community, she felt supported as she leaned deeper into her interest in science. She was soon nominated to a program that matched students from underrepresented backgrounds in STEM with a university professor to pursue a summer research project. Although Backman was still uncertain about going to another university to do lab research, with encouragement from her department she gave the program a chance.

Backman matched with Professor Catherine Drennan at MIT to work on visualizing structural biology and took part in the MIT Summer Research Program in Biology (MSRP-Bio). The research clicked with her immediately and became a turning point; Backman returned to participate in the lab the following summer and then applied to graduate school.

“Getting nominated to the program changed my life. I certainly wouldn’t have applied to MIT otherwise,” says Backman. “At first, I was convinced I wouldn’t fit in, but soon found myself surrounded by people as passionate about science as I was. I knew I was in the right place.”

Uncovering secrets about the human microbiome

Today, Backman is a graduate student in the Drennan lab and researches the chemistry of the human microbiome, a collection of gut microbes essential to sustaining the body. Backman is interested in how certain bacteria can outcompete other strains by producing unique proteins that process abundant nutrients or repair broken enzymes. Her use of X-ray crystallography has helped her produce atomic models that shed light on the structure of these proteins.

One type of protein Backman and her team have characterized is called a spare part protein. When produced, this protein can help restore a broken enzyme’s ability to catalyze essential reactions. “When fixing a car with a flat tire, you would replace the tire and not the whole car. A similar strategy is being used here. These spare-part proteins act to bind and restore the activity of the enzyme completely,” she says.

Over the years, Backman has seen the depth of questions surrounding the microbiome grow. Scientists have begun to recognize how important the microbiome is to human health. “Ever since my first summer research experience at MIT, I’ve been dedicated to studying this one unique repair mechanism,” says Backman. “We’ve gone from solving the structure of the proteins to now understanding how the mechanism works. But there’s still so much more to learn — we have started to suspect these repair mechanisms speak to a broader motif in other enzymes as well.”

Backman and her team have also been leaders in characterizing how an important enzyme, called hydroxy-L-proline dehydratase (HypD), performs its unusual chemistry. This abundant enzyme takes hydroxyproline, a common nutrient in the gut, and can obtain a competitive advantage by using it as a nutrient and source of energy.

“Only a unique subset of bacteria can process hydroxyproline. On the clinical side, we have seen during infection that virulent bacteria with this ability, such as C. difficile, will start rapidly consuming hydroxyproline to proliferate,” says Backman. “Conversely, we could one day create antibiotics that specifically inhibit HypD without killing our beneficial bacteria.”

Encouraging the future of science

Outside of her research, Backman cares deeply about serving and being a part of the Latinx community on campus. She helped co-found the MIT Latinx Graduate Student Association and has served for four years as a graduate resident assistant for La Casa, the Latinx undergraduate living community at New House. “La Casa is a really tight-knit and familial community,” says Backman. “Some of our original freshmen are now seniors, so it’s been really rewarding to see their whole transition throughout college. I love getting to watch students explore and come to realize what they’re passionate about.”

Backman has also been instrumental in spurring equity initiatives on campus. She is currently a student representative for the MIT Department of Chemistry Diversity, Equity, and Inclusion Committee and has worked to implement programs that support the success of underrepresented groups on campus. Her five years of service as an MIT Chemistry Access Program mentor have encouraged many underrepresented undergraduate students to pursue chemistry graduate programs. For all her hard work at improving MIT’s campus, Backman recently received the Hugh Hampton Young Fellowship.

In the future, Backman aspires to continue researching the microbiome and mentoring students by becoming a professor. She hopes to continue the cycle and inspire more young scientists to recognize their inner potential. “I was never one of those kids that knew I wanted to be a scientist someday. My PI completely changed my life, and I would not be at MIT today without her,” she says. “Having mentors that believe in you at critical points in your life can make all the difference.”

“I think there’s this wrong assumption that diversity initiative work takes away from time that could be spent doing science. In my mind, we need to recognize how these things go hand in hand,” says Backman.

“The only way we’re going to get the best scientists is by creating a healthier, more diverse environment where people of all backgrounds feel welcomed. It’s only when people feel comfortable that they can make their greatest contributions to the field.”

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Behind the scenes, brain circuit ensures vision remains reliable

When it comes to processing vision, the brain is full of noise. Information moves from the eyes through many connections in the brain. Ideally, the same image would be reliably represented the same way each time, but instead different groups of cells in the visual cortex can become stimulated by the same scenes. So how does the brain ultimately ensure fidelity in processing what we see? A team of neuroscientists in the Picower Institute for Learning and Memory at MIT found out by watching the brains of mice while they watched movies.

What the researchers discovered is that while groups of “excitatory” neurons respond when images appear, thereby representing them in the visual cortex, activity among two types of “inhibitory” neurons combines in a neatly arranged circuit behind the scenes to enforce the needed reliability. The researchers were not only able to see and analyze the patterns of these neurons working, but once they learned how the circuit operated they also took control of the inhibitory cells to directly manipulate how consistently excitatory cells represented images.

“The question of reliability is hugely important for information processing and particularly for representation — in making vision valid and reliable,” says Mriganka Sur, the Newton Professor of Neuroscience in MIT’s Department of Brain and Cognitive Sciences and senior author of the new study in the Journal of Neuroscience. “The same neurons should be firing in the same way when I look at something, so that the next time and every time I look at it, it’s represented consistently.”

Research scientist Murat Yildirim and former graduate student Rajeev Rikhye led the study, which required a number of technical feats. To watch hundreds of excitatory neurons and two different inhibitory neurons at work, for instance, they needed to engineer them to flash in distinct colors under different colors of laser light in their two-photon microscope. Taking control of the cells using a technology called “optogenetics” required adding even more genetic manipulations and laser colors. Moreover, to make sense of the cellular activity they were observing, the researchers created a computer model of the tripartite circuit.

“It was exciting to be able to combine all these experimental elements, including multiple different laser colors, to be able to answer this question,” Yildirim says.

Reliable representation

The team’s main observation was that as mice watched the same movies repeatedly, the reliability of representation among excitatory cells varied along with the activity levels of two different inhibitory neurons. When reliability was low, activity among parvalbumin-expressing (PV) inhibitory neurons was high and activity among somatostatin-expressing (SST) neurons was low. When reliability was high, PV activity was low and SST activity was high. They also saw that SST activity followed PV activity in time after excitatory activity had become unreliable.

PV neurons inhibit excitatory activity to control their gain, Sur says. If they didn’t, excitatory neurons would become saturated amid a flood of incoming images and fail to keep up. But this gain suppression apparently comes at the cost of making representation of the same scenes by the same cells less reliable, the study suggests. SST neurons meanwhile, can inhibit the activity of PV neurons. In the team’s computer model, they represented the tripartite circuit and were able to see that SST neuron inhibition of PV neurons kicks in when excitatory activity has become unreliable.

"This was highly innovative research for Rajeev's doctoral thesis," Sur says.

The team was able to directly show this dynamic by taking control of PV and SST cells with optogenetics. For instance, when they increased SST activity they could make unreliable neuron activity more reliable. And when they increased PV activity, they could ruin reliability if it was present.

Importantly, though, they also saw that SST neurons cannot enforce reliability without PV cells being in the mix. They hypothesize that this cooperation is required because of differences in how SST and PV cells inhibit excitatory cells. SST cells only inhibit excitatory cell activity via connections, or “synapses,” on the spiny tendrils called dendrites that extend far out from the cell body, or “soma.” PV cells inhibit activity at the excitatory cell body itself. The key to improving reliability is enabling more activity at the cell body. To do that, SST neurons must therefore inhibit the inhibition provided by PV cells. Meanwhile, suppressing activity in the dendrites might reduce noise coming into the excitatory cell from synapses with other neurons.

“We demonstrate that the responsibility of modulating response reliability does not lie exclusively with one neuronal subtype,” the authors wrote in the study. “Instead, it is the co-operative dynamics between SST and PV [neurons] which is important for controlling the temporal fidelity of sensory processing. A potential biophysical function of the SSTàPV circuit may be to maximize the signal-to-noise ratio of excitatory neurons by minimizing noise in the synaptic inputs and maximizing spiking at the soma.”

Sur notes that the activity of SST neurons is not just modulated by automatic feedback from within this circuit. They might also be controlled by “top-down” inputs from other brain regions. For instance, if we realize a particular image or scene is important, we can volitionally concentrate on it. That may be implemented by signaling SST neurons to enforce greater reliability in excitatory cell activity.

In addition to Sur, Yildirim, and Rikhye, the paper’s other authors are Ming Hu and Vincent Breton-Provencher.

The National Eye Institute, The National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health, and the JPB Foundation funded the study.

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Using AI and old reports to understand new medical images

Getting a quick and accurate reading of an X-ray or some other medical images can be vital to a patient’s health and might even save a life. Obtaining such an assessment depends on the availability of a skilled radiologist and, consequently, a rapid response is not always possible. For that reason, says Ruizhi “Ray” Liao, a postdoc and a recent PhD graduate at MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL), “we want to train machines that are capable of reproducing what radiologists do every day.” Liao is first author of a new paper, written with other researchers at MIT and Boston-area hospitals, that is being presented this fall at MICCAI 2021, an international conference on medical image computing.

Although the idea of utilizing computers to interpret images is not new, the MIT-led group is drawing on an underused resource — the vast body of radiology reports that accompany medical images, written by radiologists in routine clinical practice — to improve the interpretive abilities of machine learning algorithms. The team is also utilizing a concept from information theory called mutual information — a statistical measure of the interdependence of two different variables — in order to boost the effectiveness of their approach.

Here’s how it works: First, a neural network is trained to determine the extent of a disease, such as pulmonary edema, by being presented with numerous X-ray images of patients’ lungs, along with a doctor’s rating of the severity of each case. That information is encapsulated within a collection of numbers. A separate neural network does the same for text, representing its information in a different collection of numbers. A third neural network then integrates the information between images and text in a coordinated way that maximizes the mutual information between the two datasets. “When the mutual information between images and text is high, that means that images are highly predictive of the text and the text is highly predictive of the images,” explains MIT Professor Polina Golland, a principal investigator at CSAIL.

Liao, Golland, and their colleagues have introduced another innovation that confers several advantages: Rather than working from entire images and radiology reports, they break the reports down to individual sentences and the portions of those images that the sentences pertain to. Doing things this way, Golland says, “estimates the severity of the disease more accurately than if you view the whole image and whole report. And because the model is examining smaller pieces of data, it can learn more readily and has more samples to train on.”

While Liao finds the computer science aspects of this project fascinating, a primary motivation for him is “to develop technology that is clinically meaningful and applicable to the real world.”

The model could have very broad applicability, according to Golland. “It could be used for any kind of imagery and associated text — inside or outside the medical realm. This general approach, moreover, could be applied beyond images and text, which is exciting to think about.”

Liao wrote the paper alongside MIT CSAIL postdoc Daniel Moyer and Golland; Miriam Cha and Keegan Quigley at MIT Lincoln Laboratory; William M. Wells at Harvard Medical School and MIT CSAIL; and clinical collaborators Seth Berkowitz and Steven Horng at Beth Israel Deaconess Medical Center.

The work was sponsored by the NIH NIBIB Neuroimaging Analysis Center, Wistron, MIT-IBM Watson AI Lab, MIT Deshpande Center for Technological Innovation, MIT Abdul Latif Jameel Clinic for Machine Learning in Health (J-Clinic), and MIT Lincoln Lab.

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Behind the scenes, brain circuit ensures vision remains reliable

When it comes to processing vision, the brain is full of noise. Information moves from the eyes through many connections in the brain. Ideally, the same image would be reliably represented the same way each time, but instead different groups of cells in the visual cortex can become stimulated by the same scenes. So how does the brain ultimately ensure fidelity in processing what we see? A team of neuroscientists in the Picower Institute for Learning and Memory at MIT found out by watching the brains of mice while they watched movies.

What the researchers discovered is that while groups of “excitatory” neurons respond when images appear, thereby representing them in the visual cortex, activity among two types of “inhibitory” neurons combines in a neatly arranged circuit behind the scenes to enforce the needed reliability. The researchers were not only able to see and analyze the patterns of these neurons working, but once they learned how the circuit operated they also took control of the inhibitory cells to directly manipulate how consistently excitatory cells represented images.

“The question of reliability is hugely important for information processing and particularly for representation — in making vision valid and reliable,” says Mriganka Sur, the Newton Professor of Neuroscience in MIT’s Department of Brain and Cognitive Sciences and senior author of the new study in the Journal of Neuroscience. “The same neurons should be firing in the same way when I look at something, so that the next time and every time I look at it, it’s represented consistently.”

Research scientist Murat Yildirim and former graduate student Rajeev Rikhye led the study, which required a number of technical feats. To watch hundreds of excitatory neurons and two different inhibitory neurons at work, for instance, they needed to engineer them to flash in distinct colors under different colors of laser light in their two-photon microscope. Taking control of the cells using a technology called “optogenetics” required adding even more genetic manipulations and laser colors. Moreover, to make sense of the cellular activity they were observing, the researchers created a computer model of the tripartite circuit.

“It was exciting to be able to combine all these experimental elements, including multiple different laser colors, to be able to answer this question,” Yildirim says.

Reliable representation

The team’s main observation was that as mice watched the same movies repeatedly, the reliability of representation among excitatory cells varied along with the activity levels of two different inhibitory neurons. When reliability was low, activity among parvalbumin-expressing (PV) inhibitory neurons was high and activity among somatostatin-expressing (SST) neurons was low. When reliability was high, PV activity was low and SST activity was high. They also saw that SST activity followed PV activity in time after excitatory activity had become unreliable.

PV neurons inhibit excitatory activity to control their gain, Sur says. If they didn’t, excitatory neurons would become saturated amid a flood of incoming images and fail to keep up. But this gain suppression apparently comes at the cost of making representation of the same scenes by the same cells less reliable, the study suggests. SST neurons meanwhile, can inhibit the activity of PV neurons. In the team’s computer model, they represented the tripartite circuit and were able to see that SST neuron inhibition of PV neurons kicks in when excitatory activity has become unreliable.

"This was highly innovative research for Rajeev's doctoral thesis," Sur says.

The team was able to directly show this dynamic by taking control of PV and SST cells with optogenetics. For instance, when they increased SST activity they could make unreliable neuron activity more reliable. And when they increased PV activity, they could ruin reliability if it was present.

Importantly, though, they also saw that SST neurons cannot enforce reliability without PV cells being in the mix. They hypothesize that this cooperation is required because of differences in how SST and PV cells inhibit excitatory cells. SST cells only inhibit excitatory cell activity via connections, or “synapses,” on the spiny tendrils called dendrites that extend far out from the cell body, or “soma.” PV cells inhibit activity at the excitatory cell body itself. The key to improving reliability is enabling more activity at the cell body. To do that, SST neurons must therefore inhibit the inhibition provided by PV cells. Meanwhile, suppressing activity in the dendrites might reduce noise coming into the excitatory cell from synapses with other neurons.

“We demonstrate that the responsibility of modulating response reliability does not lie exclusively with one neuronal subtype,” the authors wrote in the study. “Instead, it is the co-operative dynamics between SST and PV [neurons] which is important for controlling the temporal fidelity of sensory processing. A potential biophysical function of the SSTàPV circuit may be to maximize the signal-to-noise ratio of excitatory neurons by minimizing noise in the synaptic inputs and maximizing spiking at the soma.”

Sur notes that the activity of SST neurons is not just modulated by automatic feedback from within this circuit. They might also be controlled by “top-down” inputs from other brain regions. For instance, if we realize a particular image or scene is important, we can volitionally concentrate on it. That may be implemented by signaling SST neurons to enforce greater reliability in excitatory cell activity.

In addition to Sur, Yildirim, and Rikhye, the paper’s other authors are Ming Hu and Vincent Breton-Provencher.

The National Eye Institute, The National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health, and the JPB Foundation funded the study.

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Deep learning helps predict new drug combinations to fight Covid-19

The existential threat of Covid-19 has highlighted an acute need to develop working therapeutics against emerging health concerns. One of the luxuries deep learning has afforded us is the ability to modify the landscape as it unfolds — so long as we can keep up with the viral threat, and access the right data. 

As with all new medical maladies, oftentimes the data need time to catch up, and the virus takes no time to slow down, posing a difficult challenge as it can quickly mutate and become resistant to existing drugs. This led scientists from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Jameel Clinic for Machine Learning in Health to ask: How can we identify the right synergistic drug combinations for the rapidly spreading SARS-CoV-2? 

Typically, data scientists use deep learning to pick out drug combinations with large existing datasets for things like cancer and cardiovascular disease, but, understandably, they can’t be used for new illnesses with limited data.

Without the necessary facts and figures, the team needed a new approach: a neural network that wears two hats. Since drug synergy often occurs through inhibition of biological targets (like proteins or nucleic acids), the model jointly learns drug-target interaction and drug-drug synergy to mine new combinations. The drug-target predictor models the interaction between a drug and a set of known biological targets that are related to the chosen disease. The target-disease association predictor learns to understand a drug's antiviral activity, which means determining the virus yield in infected tissue cultures. Together, they can predict the synergy of two drugs. 

Two new drug combinations were found using this approach: remdesivir (currently approved by the FDA to treat Covid-19) and reserpine, as well as remdesivir and IQ-1S, which, in biological assays, proved powerful against the virus. The study has been published in the Proceedings of the National Academy of Sciences.

“By modeling interactions between drugs and biological targets, we can significantly decrease the dependence on combination synergy data,” says Wengong Jin SM '18, a postdoc at the Broad Institute of MIT and Harvard who recently completed his doctoral work in CSAIL, and who is the lead author on a new paper about the research. “In contrast to previous approaches using drug-target interaction as fixed descriptors, our method learns to predict drug-target interaction from molecular structures. This is advantageous since a large proportion of compounds have incomplete drug-target interaction information.” 

Using multiple medications to maximize potency, while also decreasing side effects, is practically ubiquitous for aforementioned cancer and cardiovascular disease, including a host of others such as tuberculosis, leprosy, and malaria. Using specialized drug cocktails can, quite importantly, reduce the grave and sometimes public threat of resistance (think methicillin-resistant Staphylococcus aureus known as “MRSA”), since many drug-resistant mutations are mutually exclusive. It’s much harder for a virus to develop two mutations at the same time and then become resistant to two drugs in a combination therapy. 

Importantly, the model isn’t limited to just one SARS-CoV-2 strain — it could also potentially be used for the increasingly contagious Delta variant or other variants of concern that may arise. To extend the model's efficacy against these strains, you’d only need additional drug combination synergy data for the relevant mutation(s). In addition, the team applied their approach to HIV and pancreatic cancer.

To further refine their biological modeling down the line, the team plans to incorporate additional information such as protein-protein interaction and gene regulatory networks. 

Another direction for future work they’re exploring is something called “active learning.” Many drug combination models are biased toward certain chemical spaces due to their limited size, so there's high uncertainty in predictions. Active learning helps guide the data collection process and improve accuracy in a wider chemical space. 

Jin wrote the paper alongside Jonathan M. Stokes, Banting Fellow at The Broad Institute of MIT and Harvard; Richard T. Eastman, a scientist at the National Center for Advancing Translational Sciences; Zina Itkin, a scientist at National Institutes of Health; Alexey V. Zakharo, informatics lead at the National Center for Advancing Translational Sciences (NCATS); James J. Collins, professor of biological engineering at MIT; and Tommi S. Jaakkola and Regina Barzilay, MIT professors of electrical engineering and computer science at MIT.

This project is supported by the Abdul Latif Jameel Clinic for Machine Learning in Health; the Defense Threat Reduction Agency; Patrick J. McGovern Foundation; the DARPA Accelerated Molecular Discovery program; and in part by the Intramural/Extramural Research Program of the National Center for Advancing Translational Sciences within the National Institutes of Health.

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