Lecture series aims to demystify, celebrate tenure

Shortly after being awarded tenure in July, Cem Tasan was asked to give a talk about what it took to earn the appointment. 
 
Tasan, the Thomas B. King Associate Professor of Metallurgy in the MIT Department of Materials Science and Engineering (DMSE), would speak directly to his peers, his students, and others in his department and could take any angle he wished. He could talk about the research he did. The relationships and collaborations he made. The students he advised. The dinners he missed at home.
 
Tasan jumped at the chance. One reason: Academic tenure, a permanent status as a professor and researcher, is not widely understood. Its principal purpose is to safeguard academic freedom, allowing faculty to pursue research and innovation without corporate or political pressure.
 
“The tenure process is really at the core of an academic institution’s being. At the same time, it’s a process that’s a little bit hidden,” Tasan said of the grueling series of reviews of a researcher’s scholarship, teaching, and service. That’s not because it’s a secret — MIT and other higher-ed institutions lay out the process in detail — “it’s just that people who are not in a tenure track position don’t have much time to think about it.” 
 
“Any activity that we could think of to provide a better glimpse of what’s going on there helps us explain why we are the way we are,” Tasan said.
 
A new series, called Tenure Talks, debuted this fall with three presentations, each featuring one of DMSE’s newest tenured faculty members: Tasan, James LeBeau, and Robert Macfarlane, all appointed in July, along with 11 others in the School of Engineering. The brainchild of DMSE head Jeffrey Grossman, the series aims to acknowledge the unique human experiences behind the tenure process and celebrate them.
 
“It’s asking these extraordinary individuals who have done extraordinary research and teaching and service to reflect on the work they’ve done and the path they’ve taken and tell the story of the impact that they’ve made,” Grossman says. 
 
As DMSE plans to continue the series with a new batch of tenured professors in 2023 and beyond, the 2022 speakers reflect on sharing how they got to where they are and the value to themselves, students, and the wider MIT community. 

Different journeys, different stories

First, there’s the knowledge transfer from one generation of scholars to another. 
 
“This seven-year journey has had a lot of ups and downs,” Tasan said, speaking of his time at MIT on the tenure track. “If you can be honest about some of the challenges and some of the solutions that you come up with, other people can benefit from that. And that’s good for our society, and that’s good for our community.”
 
Each talk represented not just a different tenure story, but a different storytelling approach. Tasan, a metals expert, split his presentation in two parts. One was on his lab’s research in in-situ testing of metals and using those insights to develop damage-resistant alloys. A second, more personal section covered strategies he adopted to increase the chances of success in academic research and life.
 
Macfarlane used his academic transformation from a trained chemist to a materials scientist to explain the groundbreaking, multidisciplinary work he and his research group are doing in programmable matter. And LeBeau detailed innovative data analysis techniques he and his team are developing in electron microscopy to better understand material properties.
 
LeBeau said the different approaches illustrate that no route to tenure is the same, and that different problems require different solutions. “There are multiple ways to be successful. I think each of us followed our own path,” he said. “You don’t want to be a follower in this profession.”
 
And every journey will have its difficulties, Tasan said. “There’s no path that’s full of roses,” Tasan said. “But if you work hard and you’re in an environment which helps you grow, then things will be fine too.” 
 
Prafull Pandey, a postdoc in Tasan’s group, found Tasan’s talk about the rigors of academic life helpful. His top takeaway was a tip on how to balance work and home life. Tasan said careful organization and prioritization are key. 
 
“He’s very disciplined,” Pandey says. He playfully muses: “Sometimes I get curious, whenever I send him an email, I get the reply — whether it is three in the morning or five or eight or nine at night. When does he sleep?”

It takes a research lab

Aside from giving guidance to aspiring scholars, the talks serve another useful function, Grossman says. They give people the chance to see the full arc of a researcher’s work and the impact it’s making.
 
“I think that was great for both faculty and students to see, ‘Oh, this isn’t just a paper or a project. This is a vision, a research vision — and it’s moving the needle in the field,’” Grossman says.
 
For Macfarlane, sharing his story was a chance to highlight how different people with different perspectives can come together and do important work. He recalled his early days at DMSE as a chemist transitioning to materials science, which incorporates elements from multiple fields, including chemistry. Chemists and materials scientists use different words for the same things, he found, or they use the same words and mean different things.  
 
“The tenure process for me was one of reconciling, and finding that middle ground, and using it as a way to tackle new research questions that I probably would not have thought of other ways,” Macfarlane said.
 
Today the Macfarlane Lab draws from a deep knowledge of chemistry and materials science as well as the variety of disciplines represented by its grad students and postdocs to enable new ways of developing materials.
 
LeBeau also stressed the importance of working together for a common purpose.
 
“Our groups are nothing without our students and postdocs,” LeBeau said. “I try to reiterate to the students, ‘You’re not working for me. You’re working with me.’ And I think that is a very important message to get across.”
 
Following each talk was a reception where students, faculty, and staff could mingle. Pablo Leon, a DMSE graduate student in Professor Rafael Gómez-Bombarelli’s lab, attended all three events. For him, they were a great way to get to know the department’s faculty better — to hear them talk about their research and the decisions they made. 
 
“They highlighted ‘This is a cool professor’ but also ‘Here are their journeys, and this is how they got here.’ Such a big thing,” Leon said. “Then also I have friends in their groups — I feel like I know them a little bit more when they’re talking about their research. I’m like, ‘Yeah, I remember that from the talk.’”

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Brandon Ogbunu is a radical collaborator

Learning has always come naturally to Brandon Ogbunu. When he was a child growing up in Manhattan, his mother, a teacher, instilled in him an appreciation for school, the sciences, and curiosity. At work, she taught mathematics, social studies, and special education. At home, she taught her son to embrace art, literature, and sports in addition to science, laying the groundwork for a well-rounded approach to learning that would inform the rest of his career.

Ogbunu grew up during the AIDS epidemic. Witnessing the devastating effects of the virus kindled an interest in disease. Although he describes himself as “a bit of an underachiever” in high school, he found his identity as a scholar during his time at Howard University. He majored in chemistry due to its reputation as the “central science” and voraciously read books on math, economics, and history to gain a more nuanced understanding of the topic. Toward the end of his undergraduate program, Ogbunu learned more about the intersection between inequality and public health and began to consider how forces like poverty can drive the spread of diseases like HIV, tuberculosis, and malaria.

After graduating from Howard in 2002, he traveled to Kenya on a Fulbright fellowship. There, while studying the chemical ecology of malaria, he became captivated by evolution. “I fell in love with it as kind of a governing viewpoint on how the natural world works,” he says.

When he returned to the United States, Ogbunu studied medicine at Yale University, but found himself somewhat overwhelmed with career options. There were many ways to approach the problem of disease, but would he do so as a physician? An evolutionary biologist? A computer scientist? An economist? After his time in Kenya, he knew that whatever path he took, evolutionary reasoning — an approach to research that focuses on the practical applications of evolutionary theory — would have to be at the center of it.

It was then that Ogbunu took an interest in Professor Paul Turner’s virology lab. Turner, a professor in the Yale Department of Ecology and Evolutionary Biology, had just published a paper that addressed virus evolution through the lens of game theory. “I was like, this is exactly the kind of lab I want to be in,” Ogbunu recalls.

Ogbunu completed his PhD in microbiology in 2010. His dissertation revolved around a concept called “evolvability” — the capacity of organisms to evolve — in the context of infectious disease.

From there, Ogbunu decided to cultivate his interest in data science with a postdoctoral fellowship at the Broad Institute of MIT and Harvard and Harvard University, where he studied population genetics under the supervision of Daniel Hartl.

It was during this postdoctoral training that Ogbunu first encountered professor of chemistry Matthew Shoulders, who at the time was a junior faculty member at MIT. The two scientists instantly hit it off. “We each gave each other a new language to describe the problems we were thinking about,” Ogbunu says of their shared interest in protein evolution. “We could have a conversation with the person across the aisle. And I found that to be a model for the way that I collaborate in general.”

After completing his postdoc training, Ogbunu taught for two years at Brown University, and in 2020, he joined the Yale faculty as an assistant professor in the Department of Ecology and Evolutionary Biology.

Ogbunu’s current research takes place at the intersection of evolutionary biology, genetics, and epidemiology. His lab uses experimental evolution, mathematical modeling, and computational biology to investigate disease across scales: from the biophysics of proteins involved in drug resistance, to the social determinants driving epidemics at the population level.

Ogbunu decided to apply for the Martin Luther King Jr. (MLK) Visiting Scholars and Professors program because, during his time at the Broad Institute, he grew to admire the interdisciplinary culture of MIT. “I believe in disciplines, and I believe in expertise,” Ogbunu explains, “but I don't believe that you need to be relegated to any kind of singular domain. You should be able to think broadly.” He also appreciated MIT’s focus on the practical applications of scholarship. “Whatever it is you’re making,” he says, “be it literature, or poetry, or biomolecules — everybody likes to make things.”

Creative intersections

At MIT, Ogbunu is working in the Department of Chemistry alongside Shoulders, whose lab focuses on understanding the mechanisms of protein folding and evolution. “I really try to maximize connection time,” Ogbunu says of his day-to-day work at MIT. He spends his time collaborating with graduate students and postdocs in the Shoulders Laboratory, writing manuscripts and developing proposals with Shoulders himself, and attending meetings and seminars in various departments across campus.

Ogbunu is also embracing his artistic side through collaborations with fellow MLK Visiting Scholars. “The MLK Fellows are the most impressive people I’ve ever been around,” he says. “The opportunity to be in a cohort with them is really truly an honor.”

With Wasalu Jaco, widely known by his stage name Lupe Fiasco, Ogbunu has been exploring the relationship between rap and evolution and between music and data science. Ogbunu also hopes to collaborate with Eunice Ferreira, with whom he shares a passion for theater arts. In fact, Ogbunu was recently appointed to the board of the Catalyst Collaborative, a collaboration between MIT and Central Square Theater. He considers this appointment to be one of the great honors of his career.

“I like cutting-edge, provocative, and progressive ideas in a number of realms,” Ogbunu says of his love for the arts. “I love creative intersections between science and society. And I love creative, cool people who are trying to make the world a better place.”

Ogbunu’s preferred creative outlet is writing. He has written for a number of publications, including Scientific American, Undark, and the Boston Review, and currently serves as an Ideas contributor at WIRED magazine. Ogbunu views science writing as part of the “scientific instrument,” and he uses it as an avenue to explore new ideas. Much of his work also deals with issues of diversity, discrimination, and accessibility in science.

“I’m interested in influencing who gets to become a scientist,” he says. “That’s a very deep and important part of my identity.” Ogbunu’s mother, whom he identifies as his greatest inspiration, was extremely gifted, but it was difficult for a woman of her generation to pursue a career in science. Ogbunu wants to do his best to ensure that the opportunities that were unavailable to her are available to others. “Even in 2022 and beyond, there will be people who don’t have access and don’t have opportunity,” he says. “I think their lack of access is a great shame for everyone.”

In the future, Ogbunu would like to add “mechanistic depth” to his research by thinking about disease evolution on a more molecular level. He also plans to continue embracing his multidisciplinary approach to learning. “I want to lean into my multiplicity and no longer hide from it, and no longer apologize for it,” he says. “I want to work in all these disciplines, but via radical collaboration. That’s the thing that I pride myself on: the art of collaboration.”

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Living the history of Cairo

A bit of turbulence in the job market can affect people in different ways. Consider the Egyptian scholar Taqiyy al-Din Ahmad ibn 'Ali al-Maqrizi (1364-1442). In the early 1400s, after about a quarter-century of frustration in seeking short-lived administrative jobs and wealthy patrons in Cairo, al-Maqrizi became fed up for good. He retreated to his house, started writing, and more or less did not stop for 30 years.

What resulted is the most expansive corpus of historical writing of its time, over 30 distinct works, including several histories of Egypt, biographical dictionaries, works of religious scholarship, and his “Khitat,” an architectural and political history of Cairo. Al-Maqrizi is Egypt’s best-known historian and a primary source unlike any other for medieval Egypt. That includes Mamluk Egypt, an imperial period starting in 1250, though his work covers the time since 640, when the city known today as Cairo was founded by the conquering Arabs.

Al-Maqrizi was also a critic of the world around him — and not just because his own administrative career foundered, or because a key patron was executed around 1412, at which point he became a full-time historian. Al-Maqrizi felt he was witnessing a larger period of imperial decline, which colored his work.

“His critique of the rule of Egypt left al-Maqrizi to fear for the future of the country, so he devoted the last 30 years of his life to writing the history of Egypt,” says MIT Professor Nasser Rabbat, author of a new biography of al-Maqrizi.

In the book, “Writing Egypt: Al-Maqrizi and His Historical Project,” just published by Edinburgh University Press, Rabbat examines al-Maqrizi’s personal life, scholarship, and politics, characterizing him as an intellectual with a strong moral sensibility.

“No one, really no one at the time, dared be as critical as al-Maqrizi,” says Rabbat, who is the Aga Khan Professor and the director of the Aga Khan Program for Islamic Architecture in MIT’s School of Architecture and Planning. “This is not only a chronicler reporting to us the information of the time, which is what most historians of the medieval Islamic period would do. This is someone who had the mission to show us what the ruling class [was] doing to ruin the economy and the urbanism of the country — their venality, their corruption, their bad politics.”

When your mentor is Ibn Khaldun

Rabbat, an architect and architectural historian, first encountered the work of al-Maqrizi as a graduate student a few decades ago, when he realized the “Khitat” was a work of incomparable detail about Cairo’s past, including its buildings. Over time, Rabbat also began to understand that al-Maqrizi had dissident impulses evident in many of his works.

“I’m attracted to him as a rebel,” says Rabbat, a public proponent of the Arab Spring movement of 2011 and beyond. And there are additional idiosyncracies in al-Maqrizi’s work; he was, Rabbat writes in the book, “one of only a few scholars of his time to express in writing distinct tender feelings toward the women in his life, most especially his mother.”

Al-Maqrizi came from a well-off scholarly family. In Cairo he knew and studied with the Tunisian-born scholar Ibn Khaldun, the most renowned Arab intellectual of the entire Middle Ages, whose work encompasses what we now regard as history, sociology, and economics. Among other things, Ibn Khaldun interpreted the history of empires and kingdoms as a series of rise-and-fall episodes. In Rabbat’s interpretation, al-Maqrizi’s work bears the influence of Ibn Khaldun.

In the “Khitat,” for instance, al-Maqrizi regards Cairo as having gone through five distinct periods of history since 640, and interprets the physical environment around him as being tied to these epochs.

“Ibn Khaldun told him that civilization goes through cycles, it rises and falls, and rises again and falls,” Rabbat says. “I think al-Maqrizi arranged the ‘Khitat’ according to that.” He continues: “Al-Maqrizi theorizes ‘kharab,’ the Arabic word for ‘ruin,’ so instead of writing about the fall of the dynasty or the disintegration of the political order, his frame of reference is the ‘ruination of the city,’ standing for the ruination of the political system. What he’s seeing as the rise and fall or the fate of the dynasty is instilled in the rise and fall of the city. This I think he learned from Ibn Khaldun.”

The “Khitat” largely reflects its author’s encyclopediac knowledge of, and intense feelings for, his home city. In the book, Rabbat calls him “a pioneer in the study of urban history,” whose texts predated many European works in this area.

“It’s a book that’s really aimed at telling you, this is the story of this city, and it’s also the story of its buildings, its waterworks, its streets, the whole thing is bringing all of that together to give us an idea of the city that he loves,” Rabbat says. “And he’s lamenting its disintegration.”

Traveling across time

To be sure, Al-Maqrizi wrote volume after volume about Egyptian history generally, not just about Cairo — as well as his biographical dictionaries and a series of works about the Prophet Mohammed. He was a pious person who made five pilgrimmages to Mecca after age 50, which would have meant weeks riding camels on each trip.

Still, across his works, Rabbat finds many signs of al-Maqrizi’s disenchantment with the political order, such as his description of one medieval Egyptian dissident as a “saint.”

“He is not a fighting man,” Rabbat says. “But he’s saying, we need rebels to remove the corrupt Mamluk rulers. Writing was one way for al-Maqziri to express not just his disenchantment, but his political critique.”

That interpretation of Egyptian history was both personal and political, mixing thwarted ambitions and an intellectual’s understanding of history’s ebbs and flows.

“It had something to do with his disappointment and his broken pride,” Rabbat says. “Because he thought of himself as a great person, and he did not receive the kind of respect from the ruling class that he was expecting.”

Over time, al-Maqrizi’s work was translated into Turkish, and by the 19th century Europeans had started reading him. More recently, as Rabbat chronicles, al-Maqrizi has become a touchstone figure for poets and writers. Al-Maqrizi deeply influenced the acclaimed writer Gamal al-Ghitani, whose 1980 novel “Khitat al-Ghitani” is partly an homage to the original “Khitat.” Al-Maqrizi is even a character in the 2016 novel “The Time-Travels of the Man who Sold Pickles and Sweet,” by Khayri Shalabi.

“The [contemporary] Egyptians also discovered in him a proto-citizen, someone who is concerned about the country,” Rabbat says. “What caught my attention is how novelists and poets use al-Maqrizi — as an alter ego, a doppelganger.”

“Writing Egypt” has been well received by other scholars. Walid Saleh, a professor in the University of Toronto’s Department for the Study of Religion, has called the book a “masterpiece,” and “one of the best assessments of an Arab intellectual to appear this decade.” Li Guo, a professor in the Arabic Studies Program at the University of Notre Dame, has written that the book’s “carefully charted trajectory of al-Maqrizi’s monumental project and its impact on Ottoman historiography, Orientalism, and modern Egyptian historical writing is informative and inspirational.”

To study al-Maqrizi is not to be hagiographic about him; scholars have found that al-Maqrizi lifted passages from other writers, as Rabbat also details in the book. Overall, though, Rabbat says he wants to place more attention on the distinctive aspects of al-Maqrizi: his moral bearings, and willingness to write frankly in troubled times.

“This is what al-Maqrizi means to us today,” Rabbat says. “I am hoping this book will make people discover him as something other than merely the primary source that everyone uses for this period of Egypt.”

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Unpacking the “black box” to build better AI models

When deep learning models are deployed in the real world, perhaps to detect financial fraud from credit card activity or identify cancer in medical images, they are often able to outperform humans.

But what exactly are these deep learning models learning? Does a model trained to spot skin cancer in clinical images, for example, actually learn the colors and textures of cancerous tissue, or is it flagging some other features or patterns?

These powerful machine-learning models are typically based on artificial neural networks that can have millions of nodes that process data to make predictions. Due to their complexity, researchers often call these models “black boxes” because even the scientists who build them don’t understand everything that is going on under the hood.

Stefanie Jegelka isn’t satisfied with that “black box” explanation. A newly tenured associate professor in the MIT Department of Electrical Engineering and Computer Science, Jegelka is digging deep into deep learning to understand what these models can learn and how they behave, and how to build certain prior information into these models.

“At the end of the day, what a deep-learning model will learn depends on so many factors. But building an understanding that is relevant in practice will help us design better models, and also help us understand what is going on inside them so we know when we can deploy a model and when we can’t. That is critically important,” says Jegelka, who is also a member of the Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Institute for Data, Systems, and Society (IDSS).

Jegelka is particularly interested in optimizing machine-learning models when input data are in the form of graphs. Graph data pose specific challenges: For instance, information in the data consists of both information about individual nodes and edges, as well as the structure — what is connected to what. In addition, graphs have mathematical symmetries that need to be respected by the machine-learning model so that, for instance, the same graph always leads to the same prediction. Building such symmetries into a machine-learning model is usually not easy.

Take molecules, for instance. Molecules can be represented as graphs, with vertices that correspond to atoms and edges that correspond to chemical bonds between them. Drug companies may want to use deep learning to rapidly predict the properties of many molecules, narrowing down the number they must physically test in the lab.

Jegelka studies methods to build mathematical machine-learning models that can effectively take graph data as an input and output something else, in this case a prediction of a molecule’s chemical properties. This is particularly challenging since a molecule’s properties are determined not only by the atoms within it, but also by the connections between them.  

Other examples of machine learning on graphs include traffic routing, chip design, and recommender systems.

Designing these models is made even more difficult by the fact that data used to train them are often different from data the models see in practice. Perhaps the model was trained using small molecular graphs or traffic networks, but the graphs it sees once deployed are larger or more complex.

In this case, what can researchers expect this model to learn, and will it still work in practice if the real-world data are different?

“Your model is not going to be able to learn everything because of some hardness problems in computer science, but what you can learn and what you can’t learn depends on how you set the model up,” Jegelka says.

She approaches this question by combining her passion for algorithms and discrete mathematics with her excitement for machine learning.

From butterflies to bioinformatics

Jegelka grew up in a small town in Germany and became interested in science when she was a high school student; a supportive teacher encouraged her to participate in an international science competition. She and her teammates from the U.S. and Singapore won an award for a website they created about butterflies, in three languages.

“For our project, we took images of wings with a scanning electron microscope at a local university of applied sciences. I also got the opportunity to use a high-speed camera at Mercedes Benz — this camera usually filmed combustion engines — which I used to capture a slow-motion video of the movement of a butterfly’s wings. That was the first time I really got in touch with science and exploration,” she recalls.

Intrigued by both biology and mathematics, Jegelka decided to study bioinformatics at the University of Tübingen and the University of Texas at Austin. She had a few opportunities to conduct research as an undergraduate, including an internship in computational neuroscience at Georgetown University, but wasn’t sure what career to follow.

When she returned for her final year of college, Jegelka moved in with two roommates who were working as research assistants at the Max Planck Institute in Tübingen.

“They were working on machine learning, and that sounded really cool to me. I had to write my bachelor’s thesis, so I asked at the institute if they had a project for me. I started working on machine learning at the Max Planck Institute and I loved it. I learned so much there, and it was a great place for research,” she says.

She stayed on at the Max Planck Institute to complete a master’s thesis, and then embarked on a PhD in machine learning at the Max Planck Institute and the Swiss Federal Institute of Technology.

During her PhD, she explored how concepts from discrete mathematics can help improve machine-learning techniques.

Teaching models to learn

The more Jegelka learned about machine learning, the more intrigued she became by the challenges of understanding how models behave, and how to steer this behavior.

“You can do so much with machine learning, but only if you have the right model and data. It is not just a black-box thing where you throw it at the data and it works. You actually have to think about it, its properties, and what you want the model to learn and do,” she says.

After completing a postdoc at the University of California at Berkeley, Jegelka was hooked on research and decided to pursue a career in academia. She joined the faculty at MIT in 2015 as an assistant professor.

“What I really loved about MIT, from the very beginning, was that the people really care deeply about research and creativity. That is what I appreciate the most about MIT. The people here really value originality and depth in research,” she says.

That focus on creativity has enabled Jegelka to explore a broad range of topics.

In collaboration with other faculty at MIT, she studies machine-learning applications in biology, imaging, computer vision, and materials science.

But what really drives Jegelka is probing the fundamentals of machine learning, and most recently, the issue of robustness. Often, a model performs well on training data, but its performance deteriorates when it is deployed on slightly different data. Building prior knowledge into a model can make it more reliable, but understanding what information the model needs to be successful and how to build it in is not so simple, she says.

She is also exploring methods to improve the performance of machine-learning models for image classification.

Image classification models are everywhere, from the facial recognition systems on mobile phones to tools that identify fake accounts on social media. These models need massive amounts of data for training, but since it is expensive for humans to hand-label millions of images, researchers often use unlabeled datasets to pretrain models instead.

These models then reuse the representations they have learned when they are fine-tuned later for a specific task.

Ideally, researchers want the model to learn as much as it can during pretraining, so it can apply that knowledge to its downstream task. But in practice, these models often learn only a few simple correlations — like that one image has sunshine and one has shade — and use these “shortcuts” to classify images.

“We showed that this is a problem in ‘contrastive learning,’ which is a standard technique for pre-training, both theoretically and empirically. But we also show that you can influence the kinds of information the model will learn to represent by modifying the types of data you show the model. This is one step toward understanding what models are actually going to do in practice,” she says.

Researchers still don’t understand everything that goes on inside a deep-learning model, or details about how they can influence what a model learns and how it behaves, but Jegelka looks forward to continue exploring these topics.

“Often in machine learning, we see something happen in practice and we try to understand it theoretically. This is a huge challenge. You want to build an understanding that matches what you see in practice, so that you can do better. We are still just at the beginning of understanding this,” she says.

Outside the lab, Jegelka is a fan of music, art, traveling, and cycling. But these days, she enjoys spending most of her free time with her preschool-aged daughter.

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Riddle solved: Why was Roman concrete so durable?

The ancient Romans were masters of engineering, constructing vast networks of roads, aqueducts, ports, and massive buildings, whose remains have survived for two millennia. Many of these structures were built with concrete: Rome’s famed Pantheon, which has the world’s largest unreinforced concrete dome and was dedicated in A.D. 128, is still intact, and some ancient Roman aqueducts still deliver water to Rome today. Meanwhile, many modern concrete structures have crumbled after a few decades.

Researchers have spent decades trying to figure out the secret of this ultradurable ancient construction material, particularly in structures that endured especially harsh conditions, such as docks, sewers, and seawalls, or those constructed in seismically active locations.

Now, a team of investigators from MIT, Harvard University, and laboratories in Italy and Switzerland, has made progress in this field, discovering ancient concrete-manufacturing strategies that incorporated several key self-healing functionalities. The findings are published today in the journal Science Advances, in a paper by MIT professor of civil and environmental engineering Admir Masic, former doctoral student Linda Seymour ’14, PhD ’21, and four others.

For many years, researchers have assumed that the key to the ancient concrete’s durability was based on one ingredient: pozzolanic material such as volcanic ash from the area of Pozzuoli, on the Bay of Naples. This specific kind of ash was even shipped all across the vast Roman empire to be used in construction, and was described as a key ingredient for concrete in accounts by architects and historians at the time.

Under closer examination, these ancient samples also contain small, distinctive, millimeter-scale bright white mineral features, which have been long recognized as a ubiquitous component of Roman concretes. These white chunks, often referred to as “lime clasts,” originate from lime, another key component of the ancient concrete mix. “Ever since I first began working with ancient Roman concrete, I’ve always been fascinated by these features,” says Masic. “These are not found in modern concrete formulations, so why are they present in these ancient materials?”

Previously disregarded as merely evidence of sloppy mixing practices, or poor-quality raw materials, the new study suggests that these tiny lime clasts gave the concrete a previously unrecognized self-healing capability. “The idea that the presence of these lime clasts was simply attributed to low quality control always bothered me,” says Masic. “If the Romans put so much effort into making an outstanding construction material, following all of the detailed recipes that had been optimized over the course of many centuries, why would they put so little effort into ensuring the production of a well-mixed final product? There has to be more to this story.”

Upon further characterization of these lime clasts, using high-resolution multiscale imaging and chemical mapping techniques pioneered in Masic’s research lab, the researchers gained new insights into the potential functionality of these lime clasts.

Historically, it had been assumed that when lime was incorporated into Roman concrete, it was first combined with water to form a highly reactive paste-like material, in a process known as slaking. But this process alone could not account for the presence of the lime clasts. Masic wondered: “Was it possible that the Romans might have actually directly used lime in its more reactive form, known as quicklime?”

Studying samples of this ancient concrete, he and his team determined that the white inclusions were, indeed, made out of various forms of calcium carbonate. And spectroscopic examination provided clues that these had been formed at extreme temperatures, as would be expected from the exothermic reaction produced by using quicklime instead of, or in addition to, the slaked lime in the mixture. Hot mixing, the team has now concluded, was actually the key to the super-durable nature.

“The benefits of hot mixing are twofold,” Masic says. “First, when the overall concrete is heated to high temperatures, it allows chemistries that are not possible if you only used slaked lime, producing high-temperature-associated compounds that would not otherwise form. Second, this increased temperature significantly reduces curing and setting times since all the reactions are accelerated, allowing for much faster construction.”

During the hot mixing process, the lime clasts develop a characteristically brittle nanoparticulate architecture, creating an easily fractured and reactive calcium source, which, as the team proposed, could provide a critical self-healing functionality. As soon as tiny cracks start to form within the concrete, they can preferentially travel through the high-surface-area lime clasts. This material can then react with water, creating a calcium-saturated solution, which can recrystallize as calcium carbonate and quickly fill the crack, or react with pozzolanic materials to further strengthen the composite material. These reactions take place spontaneously and therefore automatically heal the cracks before they spread. Previous support for this hypothesis was found through the examination of other Roman concrete samples that exhibited calcite-filled cracks.

To prove that this was indeed the mechanism responsible for the durability of the Roman concrete, the team produced samples of hot-mixed concrete that incorporated both ancient and modern formulations, deliberately cracked them, and then ran water through the cracks. Sure enough: Within two weeks the cracks had completely healed and the water could no longer flow. An identical chunk of concrete made without quicklime never healed, and the water just kept flowing through the sample. As a result of these successful tests, the team is working to commercialize this modified cement material.

“It’s exciting to think about how these more durable concrete formulations could expand not only the service life of these materials, but also how it could improve the durability of 3D-printed concrete formulations,” says Masic.

Through the extended functional lifespan and the development of lighter-weight concrete forms, he hopes that these efforts could help reduce the environmental impact of cement production, which currently accounts for about 8 percent of global greenhouse gas emissions. Along with other new formulations, such as concrete that can actually absorb carbon dioxide from the air, another current research focus of the Masic lab, these improvements could help to reduce concrete’s global climate impact.

The research team included Janille Maragh at MIT, Paolo Sabatini at DMAT in Italy, Michel Di Tommaso at the Instituto Meccanica dei Materiali in Switzerland, and James Weaver at the Wyss Institute for Biologically Inspired Engineering at Harvard University. The work was carried out with the assistance of the Archeological Museum of Priverno in Italy.

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Portraiture at the intersection of art, science, and society

“For me, this project is about making science visible in society,” says Herlinde Koelbl, a renowned German photo artist whose portrait series, “Fascination of Science,” is now on display at MIT. 

Koelbl set herself the goal to photograph scientists and to show their motivation, influences, and ways of thinking — through the eyes of an artist. The portraits juxtapose the subjects’ faces with scientific concepts, advice, or reflections playfully inscribed on their palms. Individually, each picture or phrase speaks to the researcher’s personal quest for knowledge — everything from nucleotide base pairings and “learn from failures!” to “make malaria history!” and a sailing vessel beset by sea creatures — but collectively, the broad sweep of disciplines and backgrounds represented in the portraits reveals the interconnectedness of the scientific endeavor across institutions, geography, and subject matter.  

The MIT venue for Koelbl’s work is the Public Galleries of the Koch Institute for Integrative Cancer Research, a research center that combines MIT’s rich traditions of interdisciplinary inquiry and technological innovation with discovery-based biological research to develop new insights, tools, and technologies to fight cancer.

Through Koelbl’s lens, MIT’s “mind and hand” motto is made visible, along with the diversity of ideas that fuel society’s collective fascination with science. The exhibit includes portraits of MIT scientists Sangeeta Bhatia, Ed Boyden, Sallie “Penny” Chisholm, Wolfgang Ketterle, Robert Langer, and Robert Weinberg, along with other internationally acclaimed scientists such as George Church, Jennifer Doudna, Emmanuelle Charpentier, and 2022 Nobel laureate Carolyn Bertozzi. 

Visitors are welcome to view Koelbl’s work at the Koch Institute’s Public Galleries (open to the public on weekdays 8 a.m. - 6 p.m.) through Jan. 27.  

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New MIT internships expand research opportunities in Africa

With new support from the Office of the Associate Provost for International Activities, MIT International Science and Technology Initiatives (MISTI) and the MIT-Africa program are expanding internship opportunities for MIT students at universities and leading academic research centers in Africa. This past summer, MISTI supported 10 MIT student interns at African universities, significantly more than in any previous year.

“These internships are an opportunity to better merge the research ecosystem of MIT with academia-based research systems in Africa,” says Evan Lieberman, the Total Professor of Political Science and Contemporary Africa and faculty director for MISTI.

For decades, MISTI has helped MIT students to learn and explore through international experiential learning opportunities and internships in industries like health care, education, agriculture, and energy. MISTI’s MIT-Africa Seed Fund supports collaborative research between MIT faculty and Africa-based researchers, and the new student research internship opportunities are part of a broader vision for deeper engagement between MIT and research institutions across the African continent.

While Africa is home to 12.5 percent of the world’s population, it generates less than 1 percent of scientific research output in the form of academic journal publications, according to the African Academy of Sciences. Research internships are one way that MIT can build mutually beneficial partnerships across Africa’s research ecosystem, to advance knowledge and spawn innovation in fields important to MIT and its African counterparts, including health care, biotechnology, urban planning, sustainable energy, and education.

Ari Jacobovits, managing director of MIT-Africa, notes that the new internships provide additional funding to the lab hosting the MIT intern, enabling them to hire a counterpart student research intern from the local university. This support can make the internships more financially feasible for host institutions and helps to grow the research pipeline.

With the support of MIT, State University of Zanzibar (SUZA) lecturers Raya Ahmada and Abubakar Bakar were able to hire local students to work alongside MIT graduate students Mel Isidor and Rajan Hoyle. Together the students collaborated over a summer on a mapping project designed to plan and protect Zanzibar's coastal economy.

“It’s been really exciting to work with research peers in a setting where we can all learn alongside one another and develop this project together,” says Hoyle.

Using low-cost drone technology, the students and their local counterparts worked to create detailed maps of Zanzibar to support community planning around resilience projects designed to combat coastal flooding and deforestation and assess climate-related impacts to seaweed farming activities. 

“I really appreciated learning about how engagement happens in this particular context and how community members understand local environmental challenges and conditions based on research and lived experience,” says Isidor. “This is beneficial for us whether we're working in an international context or in the United States.”

For biology major Shaida Nishat, her internship at the University of Cape Town allowed her to work in a vital sphere of public health and provided her with the chance to work with a diverse, international team headed by Associate Professor Salome Maswine, head of the global surgery division and a widely-renowned expert in global surgery, a multidisciplinary field in the sphere of global health focused on improved and equitable surgical outcomes.

“It broadened my perspective as to how an effort like global surgery ties so many nations together through a common goal that would benefit them all,” says Nishat, who plans to pursue a career in public health.

For computer science sophomore Antonio L. Ortiz Bigio, the MISTI research internship in Africa was an incomparable experience, culturally and professionally. Bigio interned at the Robotics Autonomous Intelligence and Learning Laboratory at the University of Witwatersrand in Johannesburg, led by Professor Benjamin Rosman, where he developed software to enable a robot to play chess. The experience has inspired Bigio to continue to pursue robotics and machine learning.

Participating faculty at the host institutions welcomed their MIT interns, and were impressed by their capabilities. Both Rosman and Maswime described their MIT interns as hard-working and valued team members, who had helped to advance their own work.  

Building strong global partnerships, whether through faculty research, student internships, or other initiatives, takes time and cultivation, explains Jacobovits. Each successful collaboration helps to seed future exchanges and builds interest at MIT and peer institutions in creative partnerships. As MIT continues to deepen its connections to institutions and researchers across Africa, says Jacobovits, “students like Shaida, Rajan, Mel, and Antonio are really effective ambassadors in building those networks.”

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