Research, teaching and outreach in Physics at UW–Madison
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Maxim Vavilov named Vilas Associate
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The Office of the Vice Chancellor for Research and Graduate Education has announced 26 faculty winners of the Vilas Associates Competition, including physics professor Maxim Vavilov. The competition recognizes “new and ongoing research of the highest quality and significance.” Tenure-track assistant professors and tenured faculty within 20 years of their tenure date are eligible.
The award is funded by the William F. Vilas Estate Trust.
Recipients are chosen competitively by the divisional research committees on the basis of a detailed proposal. Winners receive up to two-ninths of research salary support (including the associated fringe costs) for the summers of 2022 and 2023, as well as a $12,500 flexible research fund in each of the two fiscal years. Faculty paid on an annual basis are not eligible for the summer salary support but are eligible for the flexible fund portion of this award.
Coral skeleton formation rate determines resilience to acidifying oceans
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A new University of Wisconsin–Madison study has implications for predicting coral reef survival and developing mitigation strategies against having their bony skeletons weakened by ocean acidification.
Though coral reefs make up less than one percent of the ocean floor, these ecosystems are among the most biodiverse on the planet — with over a million species estimated to be associated with reefs.
The coral species that make up these reefs are known to be differently sensitive or resilient to ocean acidification — the result of increasing atmospheric carbon dioxide levels. But scientists are not sure why.
In the study, researchers show that the crystallization rate of coral skeletons differs across species and is correlated with their resilience to acidification.
“Finding solutions that are science-based is a priority,” says physics professor Pupa Gilbert, shown here with samples of scleractinian coral along the Lake Monona shoreline in Madison. | Photo: Jeff Miller
“Many agencies keep putting out reports in which they say, ‘Yes, coral reefs are threatened,’ with no idea what to do,” says Pupa Gilbert, a physics professor at UW–Madison and senior author of the study that was published Jan. 17 in the Journal of the American Chemical Society. “Finding solutions that are science-based is a priority, and having a quantitative idea of exactly what’s happening with climate change to coral reefs and skeletons is really important.”
Reef-forming corals are marine animals that produce a hard skeleton made up of the mostly insoluble crystalline material aragonite. Aragonite forms when precursors made up of a more soluble form, amorphous calcium carbonate, are deposited onto the growing skeleton and then crystallize.
The team studied three genera of coral and took an in-depth look at the components of their growing skeletons. They used a technique that Gilbert pioneered called PEEM spectromicroscopy, which detects the different forms of calcium carbonate with the greatest sensitivity to date.
When they used these spectromicroscopy images to compare the thickness of amorphous precursors to the crystalline form, they found that Acropora, which is more sensitive to acidification, had a much thicker band of amorphous calcium carbonate than Stylophora, which is less sensitive.
A third genus of unknown sensitivity, Turbinaria, had an even thinner amorphous precursor layer than Stylophora, suggesting it should be the most resilient of the three to ocean acidification.
Coral skeletons were studied with PEEM spectromicroscopy, which identifies the calcium spectrum associated with each imaging pixel, then renders it in false color depending on the form of calcium. Blue is aragonite, the insoluble, crystalline form of calcium carbonate; the other colors represent one of the two amorphous precursor forms, a mix of the two, or a mix of aragonite and precursor form. Acropora spp. (left), has more non-blue pixels compared to Turbinaria spp. (right), indicating that Acropora has more of the soluble, non-crystalline form in its growing skeleton. | Pupa Gilbert and team in JACS
The thicker the band of uncrystallized minerals, the slower the crystallization process.
“If the surface of the coral skeleton, where all this amorphous calcium carbonate is being deposited by the living animal, crystallizes quickly, then that particular species is resilient to ocean acidification; if it crystallizes slowly, then it’s vulnerable,” Gilbert says. “For once, it’s a really simple mechanism.”
The mechanism may have worked out to be simple, but the data analysis required to process and interpret the PEEM images is anything but. Each pixel of imaging data acquired has a calcium spectrum that needs to be analyzed, which results in millions of data points. Processing the data includes many decision-making points, plus massive computing power.
The team has tried to automate the analysis or use machine-learning techniques, but those methods have not worked out. Instead, Gilbert has found that humans making decisions are the best data processors.
Gilbert did not want to base conclusions off the decision-making of just one or two people. So she hired a group of UW–Madison undergraduates, most of whom came from the Mercile J. Lee Scholars Program, which works to attract and retain talented students from underrepresented groups. This team provided a large and diverse group of decision makers.
Gilbert and her research team met several times a week via Zoom, where students were assigned the same dataset to process in parallel and discuss at their next meeting. The Cnidarians — named after the phylum to which corals belong — include current and former UW–Madison undergraduates: Celeo Matute Diaz, Jorge Rivera Colon, Asiya Ahmed, Virginia Quach, Gabi Barreiro Pujol, Isabelle LeCloux, Sydney Davison, Connor Klaus, Jaden Sengkhamee, Evan Walch and Benjamin Fordyce; and graduate students Cayla Stifler, and Connor Schmidt. Schmidt was also the lead author of the study. | Provided by Pupa Gilbert
Dubbed the Cnidarians — from the phylum to which corals, anemones and jellyfish belong — this group of students became integral members of the team. They met several times a week via Zoom, when Gilbert would assign multiple students the same dataset to process in parallel and discuss at their next meeting.
“If multiple people come up with precisely the same solution even though they make different decisions, that means our analysis is robust and reliable,” Gilbert says. “The Cnidarians’ contributions were so useful that 13 of them are co-authors on this study.”
THIS STUDY WAS SUPPORTED BY THE DEPARTMENT OF ENERGY (DE-FG02-07ER15899 AND DE-AC02-05CHH11231), THE NATIONAL SCIENCE FOUNDATION (DMR-1603192) AND THE EUROPEAN RESEARCH COUNCIL (755876).
Alex Levchenko named Humboldt Fellow
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UW–Madison physics professor Alex Levchenko has been named a Humboldt Fellow for Experienced Researchers. Sponsored by the Alexander von Humboldt Foundation, the fellowship enabled highly-qualified scientists and scholars from abroad to spend time conducting research at a partner university in Germany.
Levchenko was nominated by the Max Planck Institute for Solid State Research in Stuttgart, where he will be affiliated with the Quantum Many Body Theory Department. His research topic will be “Effects of Strong Coupling Fluctuations, Criticality, and Topology in Superconductors.”
Machine Learning meets Physics
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Machine learning and artificial intelligence are certainly not new to physics research — physicists have been using and improving these techniques for several decades.
In the last few years, though, machine learning has been having a bit of an explosion in physics, which makes it a perfect topic on which to collaborate within the department, the university, and even across the world.
“In the last five years in my field, cosmology, if you look at how many papers are posted, it went from practically zero to one per day or so,” says assistant professor Moritz Münchmeyer. “It’s a very, very active field, but it’s still in an early stage: There are almost no success stories of using machine learning on real data in cosmology.”
Münchmeyer, who joined the department in January, arrived at a good time. Professor Gary Shiu was a driving force in starting the virtual seminar series “Physics ∩ ML” early in the pandemic, which now has thousands of people on the mailing list and hundreds attending the weekly or bi-weekly seminars by Zoom. As it turned out, physicists across fields were eager to apply their methods to the study of machine learning techniques.
“So it was natural in the physics department to organize the people who work on machine learning and bring them together to exchange ideas, to learn from each other, and to get inspired,” Münchmeyer says. “Gary and I decided to start an initiative here to more efficiently focus department activities in machine learning.”
Currently, that initiative includes Münchmeyer, Shiu, Tulika Bose, Sridhara Dasu, Matthew Herndon, and Pupa Gilbert, and their research group members. They watch the Physics ∩ ML seminar together, then discuss it afterwards. On weeks that the virtual seminar is not scheduled, the group hosts a local speaker — from physics or elsewhere on campus — who is doing work in the realm of machine learning.
In the next few years, the Machine Learning group in physics looks to build on the momentum the field currently has. For example, they hope to secure funding to hire postdoctoral fellows who can work within a group or across groups in the department. Also, the hiring of Kyle Cranmer — one of the best-known researchers in machine learning for physics — as Director of the American Family Data Science Institute and as a physics faculty member, will immediately connect machine learning activities in this department with those in computer sciences, statistics, and the Information School, as well other areas on campus.
“There are many people [on campus] actively working on machine learning for the physical sciences, but there was not a lot of communication so far, and we are trying to change that,” Münchmeyer says.
Machine Learning Initiatives in the Department (so far!)
Kevin Black, Tulika Bose, Sridhara Dasu, Matthew Herndon and the CMS collaboration at CERN use machine learning techniques to improve the sensitivity of new physics searches and increase the accuracy of measurements.
Pupa Gilbert uses machine learning to understand patterns in nanocrystal orientations (detected with her synchrotron methods) and fracture mechanics (detected at the atomic scale with molecular dynamics methods developed by her collaborator at MIT).
Moritz Münchmeyer develops machine learning techniques to extract information about fundamental physics from the massive amount of complicated data of current and upcoming cosmological surveys.
Gary Shiu develops data science methods to tackle computationally complex systems in cosmology, string theory, particle physics, and statistical mechanics. His work suggests that Topological Data Analysis (TDA) can be integrated into machine learning approaches to make AI interpretable — a necessity for learning physical laws from complex, high dimensional data.
Shimon Kolkowitz earns NSF CAREER award
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Shimon Kolkowitz
Shimon Kolkowitz has already developed one of the most precise atomic clocks ever. Now, the UW–Madison physics professor has been awarded a Faculty Early Career Development (CAREER) award from the National Science Foundation (NSF) to use his atomic clocks to potentially answer some big questions about the physics of our universe.
The five-year, $800,000 in total award will cover research expenses, graduate student support, and outreach projects based on the research.
“I am honored and proud to receive an NSF CAREER award, which will help my research group expand our experimental efforts and build upon our recent results,” Kolkowitz says. “This award will support research into new ways to harness the remarkable precision of optical atomic clocks for exciting physics applications such as searching for dark matter and detecting gravitational waves.”
From one sphere of supercooled strontium atoms, Kolkowitz’s group multiplexes them into six separate spheres, each of which can be used as an atomic clock.
Atomic clocks are so precise because they take advantage of the natural vibration frequencies of atoms, which are identical for all atoms of a particular element. Kolkowitz and his research group have developed atomic clocks that can detect the difference in these frequencies between two clocks that would only disagree with each other by one second after 300 billion years, the tiniest detectable frequency changes to date. These clocks, then, can measure effects that shifts their frequency by only 0.00000000000000001%, opening the possibility of using them in the search for new physics.
A significant advancement in Kolkowitz’s clocks is that they are multiplexed, with six or more separate clocks in one
vacuum chamber, effectively placing each clock in the same environment. Mutliplexing means that comparisons between the clocks, and not their individual accuracy, is what matters — and allows the group to use commercially available, robust and portable lasers in their measurements. Though the clocks are not yet ready to be used to detect gravitational waves, Kolkowitz says the current setup “looks a bit like how you would eventually do that,” and will allow him to test out and demonstrate the concept.
In the spirit of the Wisconsin Idea and the NSF’s “broader impacts” to benefit society beyond scientific merit, with this award, Kolkowitz will focus efforts on quantum science outreach with pre-college students.
“We’ll be developing new demos and hands-on activities designed to introduce K-12 students to modern physics concepts,” Kolkowitz says. “We’ll use these activities to engage students at live shows and interactive events as part of The Wonders of Physics outreach program, with an emphasis on reaching rural and Native American communities in Wisconsin.”
NSF established these awards to help scientists and engineers develop simultaneously their contributions to research and education early in their careers. CAREER funds are awarded by the federal agency to junior-level faculty at colleges and universities.
Bucket brigades and proton gates: Researchers shed new light on water’s role in photosynthesis
Photosystem II is a protein in plants, algae and cyanobacteria that uses sunlight to break water down into its atomic components, unlocking hydrogen and oxygen. A longstanding question about this process is how water molecules are funneled into the center of Photosystem II, where water is split to produce the oxygen we breathe. A better understanding of this process could inform the next generation of artificial photosynthetic systemsthat produce clean and renewable energy from sunlight and water.
In a paper published last week in Nature Communications, an international collaboration between scientists at the Department of Energy’s Lawrence Berkeley National Laboratory (LBNL), SLAC National Accelerator Laboratory and several other institutions uncovers how the protein takes in water and how hydrogen is removed in order to release the oxygen molecules.
Uwe Bergmann
“Plants use the energy from sunlight to split two water molecules and produce the oxygen we breath. The study shows for the first time atomic-resolution snapshots of the likely channel and gate, where the water molecules arrive to the catalytic center to be split apart, and the channel where the protons are shuttled out during the splitting,” says Uwe Bergmann, the Martin L. Perl professor in ultrafast x-ray science at UW–Madison. “This information will help our understanding of one of the most fundamental reactions on earth, and how we might use sunlight in the future to create fuels.”
At SLAC’s Linac Coherent Light Source (LCLS) X-ray laser, the team illuminated samples from cyanobacteria with ultrafast pulses of X-rays to collect both X-ray crystallography and spectroscopy data to simultaneously map the protein structure and how electrons flow in the protein. Through this technique, they are able to test competing theories of how Photosystem II splits water into oxygen. Over the past few years, the team has used this method to observe various steps of this water-splitting cycle at the temperature at which it occurs in nature.
Scientists at UW–Madison have been instrumental to developing these and related x-ray imaging methods over the last decade.
The center of the protein acts as a catalyst, which drives certain chemical reactions to happen in a highly efficient manner. This research seeks to unlock how nature has optimized this catalytic process over millions of years of evolution. A cluster of four manganese atoms and one calcium atom are connected by oxygen atoms, and surrounded by water and the outer layers of the protein. In the step the scientists looked at, water flows through a pathway into the center of the protein, where one water molecule ultimately forms a bridge between a manganese atom and a calcium atom. The researchers showed that this water molecule likely provides one of the oxygen atoms in the oxygen molecule produced at the end of the cycle.
The proposed proton gate around D1-E65, D2-E312, and D1-R334 in the open and closed state. | In Nature Communications, https://doi.org/10.1038/s41467-021-26781-z
Last year, the researchers discovered that Photosystem II ferries water into the center as if through a bucket brigade: Water molecules move in many small steps from one end of the pathway to the other. They also showed that the calcium atom within the center could be involved in shuttling the water in. In this most recent study, the researchers pinpoint, for the first time, the exact pathway where this process unfolds.
“This might prevent water from interacting with the center prematurely, resulting in unwanted intermediates such as peroxide that can cause damage to the enzyme,” said Jan Kern, staff scientist at LBNL and one of the corresponding authors.
The researchers also showed that there is another pathway dedicated to removing hydrogen protons generated during the water-splitting reaction. In the proton pathway, they discovered the existence of a “proton gate,” which blocks the proton from coming back to the center.
“These results show where and how the water molecules enter the catalytic site, and where the protons are released, advancing our understanding of how two waters may come together to form the oxygen we breathe,” said Junko Yano, senior scientist at LBNL and one of the corresponding authors. “It demonstrates that it is just not enough to determine the structure of the main catalytic center, but it is also important to understand how the entire protein carries out the reaction.”
In addition to SLAC and LBNL, the collaboration includes researchers from Uppsala University in Sweden; Humboldt University of Berlin; and the University of Wisconsin-Madison.
LCLS is a DOE Office of Science user facility. This research was supported by the Office of Science.
Magellanic Stream arcing over Milky Way may be five times closer than previously thought
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Our galaxy is not alone. Swirling around the Milky Way are several smaller, dwarf galaxies — the biggest of which are the Small and Large Magellanic Clouds, visible in the night sky of the Southern Hemisphere.
Scott Lucchini
During their dance around the Milky Way over billions of years, the Magellanic Clouds’ gravity has ripped from each of them an enormous arc of gas — the Magellanic Stream. The stream helps tell the history of how the Milky Way and its closest galaxies came to be and what their future looks like.
New astronomical models developed by scientists at the University of Wisconsin–Madison and the Space Telescope Science Institute recreate the birth of the Magellanic Stream over the last 3.5 billion years. Using the latest data on the structure of the gas, the researchers discovered that the stream may be five times closer to Earth than previously thought.
The findings suggest that the stream may collide with the Milky Way far sooner than expected, helping fuel new star formation in our galaxy.
“The Magellanic Stream origin has been a big mystery for the last 50 years. We proposed a new solution with our models,” says Scott Lucchini, a graduate student in physics in Elena D’Onghia’s group at UW–Madison and lead author of the paper. “The surprising part was that the models brought the stream much closer to the Milky Way.”
The Large and Small Magellanic Clouds as they would appear if the gas around them was visible to the naked eye. | Credits: Scott Lucchini (simulation), Colin Legg (background)
Undergraduate quantum science research fellowship launches
The Open Quantum Initiative (OQI), a working group of students, researchers, educators, and leaders across the Chicago Quantum Exchange (CQE), announced the launch of the OQI Undergraduate Fellowship as part of their effort to advocate for and contribute to the development of a diverse and inclusive quantum workforce.
The primary mission of the OQI is to champion the development of a more inclusive quantum community. Science, technology, engineering, and mathematics (STEM) fields remain overwhelmingly white and male—only about 20% of bachelor’s degrees in physics, engineering, and computer science go to women, a mere 6% of all STEM bachelor’s degrees are awarded to African American students, and 12% of all STEM bachelor’s degrees are awarded to Hispanic students. But as the field of quantum science is still relatively new compared to other STEM subjects, groups like the OQI see a chance to make the foundations of the field diverse and accessible to all from the start.
“In many respects, we are building a national workforce from the ground up,” says David Awschalom, the Liew Family Professor in Molecular Engineering and Physics at the University of Chicago, senior scientist at Argonne National Laboratory, director of the Chicago Quantum Exchange, and director of Q-NEXT, a Department of Energy quantum information science center led by Argonne. “There are incredible opportunities here to make the field of quantum engineering as inclusive and equitable as possible from the very beginning, creating a strong ecosystem for the future.”
At the heart of the OQI’s effort is a new fellowship starting in summer 2022. For 10 weeks, fellows will live and work at a CQE member or partner institution, completing a research project in quantum information science and engineering under the guidance of a mentor. Students will have numerous opportunities to interact with the other fellows in their cohort during the summer research period and throughout the following academic year.
Through this fellowship, the students can expand their understanding of quantum science, receive career guidance, and grow their professional networks with leaders in academia and industry. The OQI will also aim to provide future research experiences in subsequent summers, as well as provide opportunities to mentor future fellows, helping to build a larger, diverse quantum community over time.
With the support of CQE’s member and partner institutions, including the University of Chicago, Argonne, Fermilab, University of Illinois Urbana-Champaign, University of Wisconsin-Madison, Northwestern University, and The Ohio State University, along with the NSF Quantum Leap Challenge Institute for Hybrid Quantum Architectures and Networks (HQAN) and Q-NEXT, this fellowship helps to establish diversity, equity, and inclusion as priorities central to the development of the quantum ecosystem.
The OQI launched the fellowship alongside a workshop on September 22 and 23. The OQI workshop, titled “Building a Diverse Quantum Ecosystem,” brought together CQE students, researchers, and professionals from across different institutions, including industry, to discuss the prevailing issues and barriers in quantum information science as the field develops. Institutional changemakers also shared what they have learned from their own efforts to increase representation. A panel on education and workforce development at the upcoming Chicago Quantum Summit on Nov. 4 will continue the discussion on building inclusive onramps for the quantum information science field.
“For quantum science and engineering to achieve its full potential, it must be accessible to all,” says Kayla Lee, Academic Alliance Lead at IBM Quantum and keynote speaker of the OQI workshop. “The OQI Undergraduate Fellowship provides explicit support for historically marginalized communities, which is crucial to increasing quantum engagement in a way that creates a more diverse and equitable field.”
Applications for the OQI Undergraduate Fellowship are open now.
Study of high-energy particles leads PhD student Alex Wang to Department of Energy national lab
In 2012, scientists at CERN’s Large Hadron Collider announced they had observed the Higgs boson particle, verifying many of the theories of physics that rely on its existence.
Alex Wang
Since then, scientists have continued to search for the properties of the Higgs boson and for related particles, including an extremely rare case where two Higgs boson particles appear at the same time, called di-Higgs production.
“We’ve had some searches for di-Higgs right now, but we don’t see anything significant yet,” said Alex Wang, a PhD student in experimental high energy physics at UW–Madison. “It could be because it doesn’t exist, which would be interesting. But it also could just be because, according to the Standard Model theory, it’s very rare.”
Wang will have a chance to aid in the search for di-Higgs production in more ways than one. Starting in November, he will spend a year at the SLAC National Accelerator Laboratory as an awardee in the Department of Energy Office of Science Graduate Student Research Program.
The program funds outstanding graduate students to pursue thesis research at Department of Energy (DOE) laboratories. Students work with a DOE scientist on projects addressing societal challenges at the national and international scale.
At the SLAC National Accelerator Laboratory, Wang will primarily work on hardware for a planned upgrade of the ATLAS detector, one of the many detectors that record properties of collisions produced by the Large Hadron Collider. Right now, ATLAS collects an already massive amount of data, including some events related to the Higgs boson particle. However, Higgs boson events are extremely rare.
In the future, the upgraded High-Luminosity Large Hadron Collider (HL-LHC) will enable ATLAS to collect even more data and help physicists to study particles like the Higgs boson in more detail. This will make it more feasible for researchers to look for extremely rare events such as di-Higgs production, Wang said. The ATLAS detector itself will also be upgraded to adjust for the new HL-LHC environment.
“I’m pretty excited to go there because SLAC is essentially where they’ll be assembling the innermost part of the ATLAS detector for the future upgrade,” Wang said. “So, I think it’s going to be a really central place in the future years, at least for this upgrade project.”
Increasing the amount of data a sensor collects can also cause problems, such as radiation damage to the sensors and more challenges sorting out meaningful data from background noise. Wang will help validate the performance of some of the sensors destined for the upgraded ATLAS detector.
“I’m also pretty excited because for the data analysis I’m doing right now, it’s mainly working in front of a computer, so it will be nice to have some experience working with my hands,” Wang said.
At SLAC, he will also spend time searching for evidence of di-Higgs production.
Wang’s thesis research at UW–Madison also revolves around the Higgs boson particle. He sifts through data from the Large Hadron Collider to tease out which events are “signals” related to the Higgs boson, versus events that are “backgrounds” irrelevant to his work.
One approach Wang uses is to predict how many signal events researchers expect to see, and then determine if the number of events recorded in the Large Hadron Collider is consistent with that prediction.
“If we get a number that’s consistent with our predictions, then that supports the existing model of physics that we have,” Wang said. “But for example, if you see that the theory predicts we’d have 10 events, but in reality, we see 100 events, then that could be an indication that there’s some new physics going on. So that would be a potential for discoveries.”
The Department of Energy formally approved the U.S. contribution to the High-Luminosity Large Hadron Collider accelerator upgrade project earlier this year. The HL-LHC is expected to start producing data in 2027 and continue through the 2030s. Depending on what the future holds, Wang may be able to use data from the upgraded ATLAS detector to find evidence of di-Higgs production. If that happens, he also will have helped build the machine that made it possible.
UW Physics alum Kyle Cranmer chosen to lead American Family Insurance Data Science Institute
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Cramer, who received his PhD in Physics in 2005 from UW–Madison, will be a faculty member in the Department of Physics in addition to Director of the American Family Data Science Institute
Kyle Cranmer, a University of Wisconsin–Madison alumnus who played a significant role in the discovery of the Higgs boson, will become the next director of the American Family Insurance Data Science Institute.
“We are excited to welcome Kyle back to UW–Madison, where he earned his PhD in physics in 2005,” says Amy Wendt, associate vice chancellor for research in the physical sciences. “Kyle brings a background to the position of director that will facilitate research synergies throughout campus, connecting data scientists and domain experts working to address present-day challenges ranging from health care to education, the sciences and beyond.”
Founded in 2019, the institute is working to advance discoveries that benefit society through data science research, the translation of fundamental research into practical applications, and collaboration across disciplines. The institute is a campus focal point for integrating data science into research, and one of its top priorities is to build a thriving data science community at UW–Madison.
Cranmer is currently a physics professor at New York University and will assume leadership of the institute on July 1, 2022, joining the faculty in the UW–Madison Department of Physics, with an affiliate appointment in Statistics. Brian Yandell, the David R. Anderson Founding Director of the data science institute, has served since 2019.
Cranmer arrived at data science through his contributions to the search for the Higgs boson, a fundamental particle that in the 1960s had been theorized to exist and is responsible for giving objects in the universe their mass.
Finding evidence for the particle required navigating enormous amounts of data generated by trillions of high-energy particle collisions. Cranmer developed a method for collaborative statistical modeling that allowed thousands of scientists to work together to seek, and eventually find, strong evidence for the Higgs boson in 2012.
Drawing on his experiences reaching across traditional academic boundaries, Cranmer aims to build partnerships between people working on data science methodology and those working in the humanities and the natural, physical and social sciences. | CONTRIBUTED PHOTO
“Shortly after the discovery, I pivoted to thinking more broadly about data science and machine learning for the physical sciences, identifying synergies and opportunities, and shaping that discussion internationally,” says Cranmer. His research has expanded beyond particle physics and is influencing astrophysics, cosmology, computational neuroscience, evolutionary biology and other fields.
At NYU, Cranmer is executive director of the Moore-Sloan Data Science Environment, associated faculty at the Center for Data Science, and is affiliated with the core machine learning group. His awards and honors include the Presidential Early Career Award for Science and Engineering in 2007 and the National Science Foundation’s Career Award in 2009. He was elected a 2021 Fellow of the American Physical Society.
Understanding and addressing the impact data science has on society, and the disproportionate effects it can have on marginalized people, is central to Cranmer’s vision.
One of Cranmer’s goals for the American Family Insurance Data Science Institute is to broaden engagement in data science across campus. Drawing on his own experiences reaching across traditional academic boundaries, he aims to build partnerships between people working on data science methodology and those working in the humanities and the natural, physical and social sciences. Understanding and addressing the impact data science has on society, and the disproportionate effects it can have on marginalized people, is central to his vision for this work.
“Issues around equity, inclusion and bias, and how that impacts society, those are very real problems I think everyone can appreciate,” says Cranmer. “But the way that they manifest themselves technically is much more subtle. Raising awareness of just how subtle and challenging those problems are, I think, is going to be useful for broadening the discussion across campus.”
Cranmer grew up in Arkansas and was in the first graduating class of a public, residential high school for math, science and the arts. He describes the school as a “melting pot” where students interested in computer science, physics, math and engineering collaborated on projects that today might be considered data science. Frustrated by a lack of extracurricular activities at his brand-new school, Cranmer got involved in school politics and student government.
“That was one of my first calls for leadership,” he says. “I came into the school and there was nothing set up at all — no student clubs, no activities. That was a very influential moment for me — realizing that you can be part of the solution and shape the environment around you to make it better.”
Cranmer looks forward to connecting and sharing ideas with people and research centers at UW–Madison. He stresses the importance of building trust, both within and outside the university, by demonstrating the potential for data science to positively affect people’s lives and the world.
“With experience as a national leader in data science, Kyle is well prepared to guide the institute in partnerships with enterprise thought leaders,” says Wendt. “His own research focus on data science methods that broaden participation to advance discovery in particle physics is truly rooted in the Wisconsin Idea.”
For Cranmer, contributing to the Wisconsin Idea is an exciting aspect of his new role. He sees opportunities at UW–Madison to engage with the community in research, such as working with the Division of Extension and farmers on problems like agricultural sustainability, carbon capture and climate change.
“This kind of capability is very, very unique, and there are several different entry points for the Data Science Institute to be involved in such research,” says Cranmer. “The role of data science would be really compelling.”
Following his years of experience shaping the first wave of data science at NYU, Cranmer looks forward to leading an institute that is well positioned to have real-world impact.
“I think that’s a pretty exciting thing to be a part of.”
