The new chair is in addition to four others in the sciences that she and the estate of her late husband, Steve Bepler, FCRH ’64, funded in 2017. To be titled the Kim B. and Stephen E. Bepler Chair in the Natural and Applied Sciences, the new position is expected to advance the University’s vision for excellence in science education by fueling new interdisciplinary research into today’s most pressing scientific challenges.

“I want to thank Kim Bepler on behalf of the generations of Fordham students who will benefit from her extraordinary generosity,” said Tania Tetlow, president of Fordham. “Kim understands the University’s needs as well as anyone, and has long been committed to high-impact philanthropy that furthers academic excellence and our Jesuit, Catholic mission. We are deeply grateful for her gift, and for her ongoing engagement with Fordham.”

The gift comes as Fordham is seeking to expand its STEM programs in response to students’ growing interest in the sciences. It will advance the University’s $350 million fundraising campaign, Cura Personalis | For Every Fordham Student, and its goal of supporting student-faculty research, cross-disciplinary problem solving, and other facets of academic excellence.

The new Bepler chair will enable the University to recruit an intellectual leader and well-established scholar and teacher and provide this person with robust research support, said Dennis Jacobs, Ph.D., provost of the University and senior vice president for academic affairs. The right chair holder could help attract other talent to the University while providing leadership on important scientific questions that bring multiple fields together, he said.

“Many of the most promising scientific discoveries of our day emerge in the interstitial spaces between disciplines—between biology and physics or between chemistry and math or computer science. Addressing the most complex and consequential problems facing society really requires an interdisciplinary approach,” he said, giving the examples of mitigating climate change, combatting infectious diseases, and reducing the devastating impact of neurological disorders.

For instance, he said, “when we initially fill the endowed chair, our greatest priority may be to recruit somebody who works on next-generation renewable sources of energy. Well into the future, Fordham may choose to recruit a Bepler chair who applies artificial intelligence to identify novel therapeutics or addresses other important issues and problems.”

Philanthropic Impact

The Beplers were already among the University’s most generous donors at the time of Steve Bepler’s untimely passing in 2016. They funded endowed chairs in theology and poetics and gave in support of the Fordham Founder’s Undergraduate Scholarship, the restoration of the University Church, a new organ for the church, deans’ discretionary funds, and many other areas.

Kim Bepler also recently made a major gift in support of the Joseph M. McShane, S.J. Campus Center project, another critical piece of the Cura Personalis campaign, and created the Fordham Ukraine Crisis Student Support Fund to help the University’s Ukrainian and Russian students facing financial peril because of the Russian invasion.

“With this bold and generous investment, Kim helps set the pace for leadership support,” said Roger A. Milici, Jr., vice president for development and University relations at Fordham. “Our Trustees have strongly supported all of Fordham’s recent fundraising campaigns: their gifts have accounted for 35% or more of each effort. Fordham’s philanthropic culture is dynamic, and we are committed to helping our mission partners use their wealth and generosity to improve the human condition.”

The four other Bepler chairs in the sciences—established as part of a $10.5 million gift—include a chair in biology, held by Silvia Finnemann, Ph.D., who studies the neurobiology of the human retina, and one in chemistry, held by Joshua Schrier, Ph.D., who is pursuing possibilities for automated scientific research.

The University is seeking to fill the other two chairs—one previously held by the mathematician Hans-Joachim Hein, Ph.D., and one that will be directed towards biophysics, Jacobs said.

The gifts to establish these four chairs, as well as the new chair, reflect Steve Bepler’s desire to give back to the University by investing in world-class science programs that he felt any world-class university needs, Kim Bepler said.

“Steve deeply loved Fordham, and it’s a privilege to be able to help realize his vision for the University and cement his legacy like this,” she said. “I’m honored to be counted among those who are supporting our extraordinary science faculty, with their dedication that so clearly shows the Jesuit principle of magis at work, and I’m excited to see how this professorship will help our science programs grow in new directions.”

Building Connections

Schrier said he decided to come to Fordham as a Bepler chair because of the University’s Jesuit identity and because the position offered greater freedom to not only pursue research but also involve undergraduate students in it.

The endowed chair creates a few different benefits, he said—it expands the faculty and creates capacity for new types of classes that might not be offered otherwise. And by allowing for exploratory, proof-of-concept projects, “it really kind of serves as seed money for doing creative and exciting things and then taking those initial results and showing them to federal funders,” he said.

“There’s just tremendous value for interdisciplinary work” in the applied sciences, said Schrier, whose own research applies computer simulations and machine learning to the search for applications for perovskites, a crystalline mineral.

“I hope that the holder of this position will be able to build connections and ties with different departments here at Fordham and show students how all of this type of work is connected,” he said. “I know I have a lot of fun talking to colleagues in math, talking to and working with colleagues in computer science and physics. I think interdisciplinary [work]is great.”

He spoke of a number of such projects, including his work with chemistry and computer science professors to develop teaching labs that expose chemistry students to data science, a model they published last year in the Journal of Chemical Education.

“I’m really excited about [the new Bepler chair], and I look forward to meeting the holder of the chair,” Schrier said, “because it’s always great to add to and build our intellectual community here at Fordham.”

The Kim and Steve Bepler chairs have contributed to an increase of more than threefold in the number of endowed chairs at Fordham over the past two decades. The new chair in the natural and applied sciences will bring that number to 73.

“Today’s events are designed for recognition, celebration, and appreciation of the numerous contributors to Fordham’s research accomplishments in the past two years,” said George Hong, Ph.D., chief research officer and associate vice president for academic affairs.

Hong said that Fordham has received about $16 million in faculty grants over the past nine months, which is an increase of 50.3% compared to the same period last year.

“As a research university, Fordham is committed to excellence in the creation of knowledge and is in constant pursuit of new lines of inquiry,” said Joseph McShane, S.J., president of Fordham, said during the virtual celebration. “Our faculty continue to distinguish themselves in this area. Today, today we highlight the truly extraordinary breadth and depth of their work.”

Earning Honors

Ten faculty members, representing two years of winners due to cancellations last year from the COVID-19 pandemic, were recognized with distinguished research awards.

“The distinguished research awards provide us with an opportunity to shine a spotlight on some of our most prolific colleagues, give visibility to the research achievements, and inspire others to follow in their footsteps,” Provost Dennis Jacobs said.

Recipients included Yuko Miki, associate professor of history and associate director of Latin American and Latinx Studies (LALSI), whose work focuses on Black and indigenous people in Brazil and the wider Atlantic world in the 19th century; David Budescu, Ph.D., Anne Anastasi Professor of Psychometrics and Quantitative Psychology, whose work has been on quantifying, judging, and communicating uncertainty; and, in the junior faculty category, Santiago Mejia, Ph.D., assistant professor of law and ethics in the Gabelli School of Business, whose work examines shareholder primacy and Socratic ignorance and its implications to applied ethics. (See below for a full list of recipients).

Diving Deeper

Eleven other faculty members presented in their recently published work in the humanities, social sciences, and interdisciplinary studies.

Jews and New York: ‘Virtually Identical’

Images of Jewish people and New York are inextricably tied together, according to Daniel Soyer, Ph.D., professor of history and co-author of Jewish New York: The Remarkable Story of a City and a People (NYU Press, 2017).

“The popular imagination associated Jews with New York—food names like deli and bagels … attitudes and manner, like speed, brusqueness, irony, and sarcasm; with certain industries—the garment industry, banking, or entertainment,” he said. “

Soyer quoted comedian Lenny Bruce, who joked, “the Jewish and New York essences are virtually identical, right?”

Soyer’s book examines the history of Jewish people in New York and their relationship to the city from 1654 to the current day. Other presentations included S. Elizabeth Penry, Ph.D., associate professor of history, on her book The People Are King: The Making of an Indigenous Andean Politics (Oxford University Press, 2019), and Kirk Bingaman, Ph.D., professor of pastoral mental health counseling in the Graduate School of Religion and Religious Education, on his book Pastoral and Spiritual Care in a Digital Age: The Future Is Now (Lexington Books, 2018).

Focus on Cities: The Reality Beyond the Politics

Annika Hinze, Ph.D, associate professor of political science and director of the Urban Studies Program, talked about her most recent work on the 10th and 11th editions of City Politics: The Political Economy of Urban America (Routledge, 11th edition forthcoming). She focused on how cities were portrayed by the Trump Administration versus what was happening on the ground.

“The realities of cities are really quite different—we’re not really talking about inner cities anymore,” she said. “Cities are, in many ways, mosaics of rich and poor. And yes, there are stark wealth discrepancies, growing pockets of poverty in cities, but there are also enormous oases of wealth in cities.”

When the COVID-19 pandemic hit, Hinze’s latest edition will show how urban density did not contribute to the spread of COVID-19, as many people thought, but rather it was overcrowding and concentrated poverty in cities that led to accelerated spread..

Other presentations included Nicholas Tampio, Ph.D., professor of political science, on his book Common Core: National Education Standards and the Threat to Democracy (Johns Hopkins University Press, 2018); Margo Jackson, Ph.D., professor and chair of the division of psychological and educational services in the Graduate School of Education on her book Career Development Interventions for Social Justice: Addressing Needs Across the Lifespan in Educational, Community, and Employment Contexts (Rowman and Littlefield, 2019); and Clara Rodriguez, Ph.D., professor of sociology on her book America, As Seen on TV: How Television Shapes Immigrant Expectations Around the Globe (NYU Press, 2018).

A Look into Migration

In her book Migration Crises and the Structure of International Cooperation (University of Georgia Press, 2019), Sarah Lockhart, Ph.D. assistant professor of political science, examined how countries often have agreements in place to manage the flow of trade, capital, and communication, but not people. While her work in this book specifically focused on voluntary migration, it also had implications for the impacts on forced migration and the lack of cooperation among nations .

“I actually have really serious concerns about the extent of cooperation … on measures of control, and what that means for the future, when states are better and better at controlling their borders, especially in the developing world,” she said. “And what does that mean for people when there are crises and there needs to be that kind of release valve of movement?”

Other presentations included: Tina Maschi, Ph.D., professor in the Graduate School of Social Service, on her book Forensic Social Work: A Psychosocial Legal Approach to Diverse Criminal Justice Populations and Settings (Springer Publishing Company, 2017), and Tanya Hernández, J.D., professor of law on her book Multiracials and Civil Rights: Mixed-Race Stories of Discrimination (NYU Press, 2018).

Sharing Reflections

The day’s keynote speakers—Daniel Alexander Jones, professor of theatre and 2019 Guggenheim Foundation Fellow, and Tony Award winner Clint Ramos, head of design and production and assistant professor of design—shared personal reflections on how the year’s events have shaped their lives, particularly their performance and creativity.

For Jones, breathing has always been an essential part of his work after one of his earliest teachers “initiated me into the work of aligning my breath to the cyclone of emotions I felt within.” However, seeing another Black man killed recently, he said, left him unable to “take a deep breath this morning without feeling the knot in my stomach at the killing of Daunte Wright by a police officer in Minnesota.”

Jones said the work of theatre teachers and performers is affected by their lived experiences and it’s up to them to share genuine stories for their audience.

“Our concern, as theater educators, encompasses whether or not in our real-time lived experiences, we are able to enact our wholeness as human beings, whether or not we are able to breathe fully and freely as independent beings in community and as citizens in a broad and complex society,” he said.

Ramos said that he feels his ability to be fully free has been constrained by his own desire to be accepted and understood, and that’s in addition to feeling like an outsider since he immigrated here.

“I actually don’t know who I am if I don’t anchor my self-identity with being an outsider,” he said. “There isn’t a day where I am not hyper-conscious of my existence in a space that contains me. And what that container looks like. These thoughts preface every single process that informs my actions and my decisions in this country.”

Interdisciplinary Future

Both keynote speakers said that their work is often interdisciplinary, bringing other fields into theatre education. Jones said he brings history into his teaching when he makes his students study the origins of words and phrases, and that they incorporate biology when they talk about emotions and rushes of feelings, like adrenaline.

That message of interdisciplinary connections summed up the day, according to Jonathan Crystal, vice provost.

“Another important purpose was really to hear what one another is working on and what they’re doing research on,” he said. “And it’s really great to have a place to come listen to colleagues talk about their research and find out that there are these points of overlap, and hopefully, it will result in some interdisciplinary activity over the next year.”

Distinguished Research Award Recipients

Humanities
2020: Kathryn Reklis, Ph.D., associate professor of theology, whose work included a project sponsored by the Henry Luce Foundation on Shaker art, design, and religion.
2021: Yuko Miki, Ph.D., associate professor of history and associate director of Latin American and Latinx Studies (LALSI), whose work is on Black and indigenous people in Brazil and the wider Atlantic world in the 19th century.

Interdisciplinary Studies
2020: Yi Ding, Ph.D., professor of school psychology in the Graduate School of Education, who received a $1.2 million grant from the U.S. Department of Education for a training program for school psychologists and early childhood special education teachers.
2021: Sophie Mitra, Ph.D., professor of Economics and co-director of the Disability Studies Minor, whose recent work includes documenting and understanding economic insecurity and identifying policies that combat it.

Sciences and Mathematics
2020: Thaier Hayajneh, Ph.D., professor of computer and information sciences and founder director of Fordham Center of Cybersecurity, whose $3 million grant from the National Security Agency will allow Fordham to help Historically Black Colleges and Universities and Minority-Serving Institutions build their own cybersecurity programs.
2021: Joshua Schrier, Ph.D., Kim B. and Stephen E. Bepler Chair and professor of chemistry, who highlighted his $7.4 million project funded by the Defense Advanced Research Projects Agency on perovskites.

Social Sciences
2020: Iftekhar Hasan, Ph.D., university professor and E. Gerald Corrigan Chair in International Business and Finance, whose recent work has included the examination of the role of female leadership in mayoral positions and resilience of local societies to crises.
2021: David Budescu, Ph.D., Anne Anastasi Professor of Psychometrics and Quantitative Psychology, whose work has been on quantifying, judging, and communicating uncertainty.

Junior Faculty
2020: Asato Ikeda, Ph.D., associate professor of art history, who published The Politics of Painting, Facism, and Japanese Art During WWII.
2021: Santiago Mejia, Ph.D., assistant professor of law and ethics in the Gabelli School of Business, whose work focuses on shareholder primacy and Socratic ignorance and its implications to applied ethics.

For Joshua Schrier, Ph.D., chemistry research is the next frontier.

“An emerging area of chemistry is finding ways to create a machine-readable representation of the things in the world, like the structures of molecules or chemical processes, and then using those digital representations for computer simulations and machine learning,” he said.

“Once we have the results of chemical experiments in a digital form, we can unleash the tools of data science to make smarter predictions. By combining this with robots that can conduct new experiments, we create the possibility for a virtuous cycle: Every new data point gives our model a better picture of the world, and algorithms can select new data points that improve that picture and dispatch experimental instructions to a robot to collect new data.”

Schrier joined the faculty in 2018 as the first Bepler Chair in Chemistry, and has devoted much of his time to his study “Discovering reactions and uncovering mechanisms of perovskite formation,” a $7.4 million project funded by the Defense Advanced Research Projects Agency.

Perovskites are a class of minerals that can be used in low-cost, high-performance solar cells, x-ray detectors, and lighting. The goal of the project is to develop software and hardware to automate scientific research, using perovskites as a test case.

Robot-Created Minerals

He and fellow researchers at Haverford College, Lawrence Berkeley National Laboratory, and MIT have developed a system dubbed RAPID (Robot-Accelerated Perovskite Investigation and Discovery) to create perovskite minerals. Perovskites are minerals composed of both inorganic and organic materials, which makes them are particularly attractive.

“You can replace the organic building unit with hundreds of thousands of different possible molecules. Every time you do that, you get a different crystal structure. It’s kind of like molecular Legos,” said Schrier.

“Our efforts are aimed at the early stage of materials development; we’re not making new solar cells themselves, but we are discovering the materials that will enable better solar cells. It’s like we’re not building a house, but we’re inventing new kinds of bricks you could use to build a house,” he said.

Exploring new structures is important, he said, because by changing the structure of the perovskites, you change the way they interact with light, their electrical properties, and their stability. This is important, he said, because one of the key limitations of existing perovskite solar cells is a lack of long-term stability.

In the three years since the project got underway, Schrier said they’ve synthesized roughly 70 perovskites and performed over 10,000 experiments. While that’s useful, he said, what’s equally important is that RAPID is learning how to do the experiments itself.

2020 Findings

In “Robot-Accelerated Perovskite Investigation and Discovery,” an article published in June 2020 by Chemistry of Materials, he and his colleagues detail how they adapted perovskite syntheses for the RAPID system. Given a set of starting ingredients, researchers were able to conduct 96 randomly chosen experiments in four hours. That created a data set that the computer was able to then use to predict the success of future experiments.

Although he’s based in New York City and RAPID is housed at the Lawrence Berkeley National Laboratory, Schrier is able to work with colleagues in California remotely and his students are likewise able to analyze data safely from their homes. This paper was one of the top-20 most-downloaded papers in 2020, according to the journal.

This initial set of experiments is sufficient to predict the results of any subsequent experiments for that chemical system with 80-90% accuracy. In subsequent work published in the Journal of Physical Chemistry C, Schrier and co-authors Mary Kate Caucci, FCRH ’20; Michael Tynes, FCRH ’17, GSAS ’20; and Aaron Dharna, FCRH ’16, GSAS ’20, were able to show that researchers can also extrapolate to entirely new sets of chemical ingredients that have never been seen before, with about 40% accuracy.

“With no knowledge about this new chemical system, just the things that we’ve learned about in the past about other chemical systems, being right 40% of the time is good enough,” Schrier said. “This gives us a higher probability of success on our first batch of 96 experiments. We don’t need to be perfect, we only need to find one success. To use an analogy, machine learning lets us pick better lottery tickets, and the robot lets us buy more lottery tickets. Putting them together gives us the best chance of winning.”

Randomness and Removing Bias

What’s surprised Schrier the most about recent findings is the effectiveness of randomness. Simply selecting the initial experiments randomly often yields better machine learning models than data chosen by human experts, he said.

This focus on randomness has important implications for artificial intelligence, because if human-generated data is used to create machine learning models, he said, we run the risk of creating machines that repeat our own biases. He explored the importance of removing human “fingerprints” in “Anthropogenic biases in chemical reaction data hinder exploratory inorganic synthesis,” which he published in 2019 in the journal Nature.

“This is at odds with the hypothesis-driven experiment design we teach students from grade school through university. What we’ve found is that humans tend to get stuck in a rut, and so instead of exploring all of the possibilities, they just focus on a few,” he said.

“The advantage of using robots is that they do what we tell them, even if it is just random. In this way, we remove our conceptual fingerprints from the data collection process and take a more unbiased look at the world.”

In the Classroom with Non-Science Majors

Although creating minerals from scratch is exciting, work with students is just as rewarding, Schrier said. In addition to mentoring six Fordham undergraduate research students, this fall, he taught a new course called Drug Discovery from Laboratory to the Clinic, which was especially fortuitous given the intense interest in the development of COVID-19 vaccines. The course is part of Fordham’s Manresa Scholars program and combines science with the Eloquentia Perfecta core.

Reading material for the class, which was for non-science majors, included analyses of Remdesivir, articles on clinical trials for hydroxychloroquine in the New England Journal of Medicine, analysis of the ethics of Moderna’s vaccine distribution plan, and information about the regulatory process of drug approval.

Outside speakers included a research scientist from the National Institute of Health and a pet-pharmaceutical startup entrepreneur who provided insights into the long path from basic research to sustainable business.

“The class just sort of wrote itself given the unfolding of world events that were occurring in the fall. The intersection of science, policy, business, and ethics is a fertile ground for engaging students,” he said.

“Fordham students have a rich intellectual toolbox for these types of discussions. In their core requirements, they’re taking philosophy, theology, economics, political science, and can apply this to the problem at hand. They’re quick to start a debate with, ‘No, no, no. Kant says you shouldn’t objectivize humans. We can’t do this.’”

Meanwhile, RAPID continues to churn out perovskites. Schrier is collaborating with Clavius Distinguished Professor of Computer Science“Mary Kate Caucci” “Michael Tynes” “Aaron Dharna” “Frank Hsu” “Yuanqing Tang”, to look at new ways of performing automated quality control for scientific experiments. He is also working with Rodolfo Keesey, FCRH ’20, in conducting data analysis geared toward using RAPID for other types of perovskite growth methods.

And in a collaboration with Fordham College at Rose Hill senior Lillian Cain and Michael Tynes that was published in a recent issue of the Journal of Chemical Education, Schrier described how algorithms for planning chemical experiments can be incorporated into a first-year general chemistry lab.

“We’re developing tools for doing science in a new way—not just perovskites—and it’s exciting to see Fordham students at the forefront of this new approach,” he said.

What are some of the reasons why you decided to attend Fordham?
I fell in love with Fordham’s campus and its location. I always wanted to go to school in or near a city, and Fordham had the best of both worlds. It had a beautiful campus and was located in New York City. Another reason I decided to go to Fordham was for its liberal arts curriculum and its Jesuit values, which emphasized the care and cultivation of the whole person. I had opportunities to take classes that wouldn’t normally be offered to chemistry majors.

What do you think you got at Fordham that you couldn’t have gotten elsewhere?
Fordham’s access to New York City provided a tremendous opportunity to [translate]what was being taught in class to learning beyond the classroom. I was able to go to the Metropolitan Museum of Art to see famous pieces I had just talked about in my art history course. I attended special exhibits for a history class. I did a tour at the Lower East Side Tenement Museum for a sociology class on migration, and I even had a biology lab take place in the New York Botanical Garden right across from campus.

Did you take any courses or have any experiences that helped put you on your current path?
Researching with Joshua Schrier [the Kim B. and Stephen E. Bepler Chair Professor of Chemistry at Fordham]had an incredible impact on placing me on my current path. He introduced a whole new perspective of science and chemistry. I got involved in conducting research later than typical chemistry students. I was initially intimidated [about getting]involved in research because I always felt I never knew enough, especially when it came to computational chemistry research.

Working with Professor Schrier, I realized I didn’t have to know everything right from the beginning. This was my first experience doing any form of chemical research, and I accomplished far more than I ever thought possible. I was introduced to many aspects of computational chemistry, including database mining, computer modeling, data curation, programming, supercomputing, and generating chemical data analysis. I collaborated with other scientists, attended my first conference at the MERCURY Consortium, and reviewed a manuscript for a textbook titled Machine Learning in Chemistry.

Researching with Professor Schrier inspired my scientific inquiry. I’ve come to appreciate the extraordinary fact that what we do in scientific research is continuously unique. Every moment in research was an opportunity to become closer to answering seemingly unsolvable questions or to positively impact society.

What are you optimistic about?
Although our efforts may sometimes feel insignificant, I am optimistic that our actions do have meaning and make a difference in the world. So, any action, however small, is quite powerful. I’m also optimistic about the compassion we can encounter from others, as well as the kindness we can deliver to others in our day-to-day lives.

In a recent conversation, Joshua Schrier, Ph.D., spoke about the science that has been taking place in his lab since he became the first Kim B. and Stephen E. Bepler Chair in Chemistry last fall. His research blends three scientific branches: quantum mechanics, chemistry, and computational science. This month, his research on biases in chemical reaction data was published in the journal Nature. Fordham News spoke to him about his work.

The Bepler endowed chair has allowed you more time to tackle research projects. That includes your $7.4 million project, “Discovering reactions and uncovering mechanisms of perovskite [mineral]  formation,” funded by the Defense Advanced Research Projects Agency. Tell me about this project. 

Most experiments are designed, conducted, and interpreted by humans. The goal of this project is to create the capability of having machine-specified experiments so that computer algorithms can select new experiments to perform that accelerate the scientific discovery process.

What does “machine-specified” mean? 

We want to give computer algorithms the ability to perform experiments in the real world. But to do this, we need to make sure that the specifications of what to do are completely unambiguous. Humans are pretty good about working with imprecise instructions about what to do. If I say, “Hey, let’s go to the zoo,” you would infer it’s the Bronx Zoo and that “us” includes you and I and other individuals within earshot. But a computer is not going to know what I meant: What zoo? What entrance? How do we get there? Who should go? We are working to develop software that allows people (or computers) to specify the experiments they want to be performed. The software turns that into a set of instructions in an unambiguous way. This might include a mixture of instructions for human operators and for machines—just like the way that specifying where you want to go in an Uber ride fills in the details of how to get there. Finally, we want to make it easy to collect all of the things that happen during the process so that we can learn from that data.

Like programming a self-driving car, but for science experiments? 

Yeah. That’s the high-level goal: a “self-driving” or autonomous laboratory. Just like a self-driving car, we have to be able to “steer” the experiments (specify what to do) and “see” the world. So we are also collecting as much information about everything that happens in the laboratory so that the algorithms can make sense of what is happening when devising new experiment plans. Experiment specifications are the steering wheel, so to speak. As new experiments are performed, machine-learning models get trained on the new data. This is a general problem across many areas of science—how do we use data to more efficiently get scientific insight? Because of the scale of the data, we use algorithms to sift through the data and identify anomalies, and use the insights latent in that data to devise the next round of experiment plans. 

There’s another part to your project: using this “self-driving laboratory” to develop as many different types of perovskites—minerals that help create solar cells—as possible, and then identify the most useful perovskites. 

Yes. Essentially, what we’ve cooked up—in collaboration with researchers at Lawrence Berkeley National Laboratory and Haverford College—is a way to do these types of [perovskite]syntheses using commercially-available laboratory robots. More specifically, organohalide perovskite materials are hybrid materials that have both organic and inorganic building units—and changing these changes their electronic and optical properties. As a result, there is a general interest in using perovskites for high performance, low-cost solar cells. We are using the robotic system [called RAPID]to try to discover new materials that will have higher performance. But just to be clear, our focus for now is on discovering new compounds. We don’t yet build devices from these discoveries, although we are expanding work in that direction [in collaboration with researchers from MIT]. It would be neat if we also found some really great high-performance perovskites—but even if we do not, we’ll still be able to learn rules about how they form, and demonstrate this toolbox which can be applied to other scientific problems.

Another ongoing research project is the National Science Foundation-funded “Dark Reaction Project.” What is that about?

“Dark reactions” sounds mysterious, right? But it’s a simple idea. Most of the experiments performed in laboratories are never reported. Journals tend to publish only a single example of “success.” So this vast, unreported collection of marginal successes and failures never gets exposed to the world. So by analogy to the astronomer’s “dark matter,” we like to think of “dark reactions” as this vast majority of scientific experiments that aren’t seen directly [in journal articles], but yet influences scientists’ decisions in a non-obvious way.

The good news is that scientists keep good laboratory notebooks, so the “dark reactions” are in principle available. This project is an initiative to harness the unpublished failures and marginal successes [dark reactions]in laboratory notebooks, turn them into digital data, and use that to advance hydrothermal synthesis of oxides. Once you digitize the results, you can use that database to build a machine-learning model. With that machine-learning model, you can recommend reactions to perform in the laboratory. 

So the machine-learning model is learning from “dark reactions,” or our mistakes—what not to do? 

Correct. And you can only do this if you’ve got the complete record of success and failures. 

If you look at all the published scientific literature, all you see are successes. You never see any of the failures. So if you’re trying to identify a mathematical function that divides success and failure—and that’s really all that you’re doing with machine-learning, is finding the mathematical function—then your algorithm is going to look at all of these examples in the published literature and say, “Oh, good news, everything is successful.” Because all the examples that it sees are only examples of success. 

Lastly, you have a paper that was recently published by Nature: “Anthropogenic biases in chemical reaction data hinder exploratory inorganic synthesis.” How does it relate to dark reactions? 

This work is supported by the same project from the National Science Foundation, and is a natural continuation. “Dark reactions” are the experiments that have been tried in the laboratory, but not reported because they are “failures” or marginal successes. But what about the “extra dark” reactions that don’t even get attempted? In practice, chemical experiments are planned by human scientists and thus are subject to a variety of human cognitive biases, heuristics, and social influences that might lead to some reactions being systematically excluded. What we were able to show in this study is that such biases are present in the chemical reaction literature, and that the underrepresented reactions are not being excluded for any “good” reason—it’s not because they are more expensive, or more difficult, or more prone to failure, but rather simply because humans tend to get stuck in a rut when planning reactions. This might just be a curiosity, except for the fact that these anthropogenic (human-generated) data are now being widely used to train machine-learning models to predict chemical syntheses. The hazard is that we end up making the machine in our own image, so to speak, rather than letting it perform as well as it could. We were able to show that indeed, human-selected experiments were inferior to randomly-generated experiments for building machine learning models, even if you gave the humans many more reaction data.  

This interview has been edited and condensed for clarity.