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(December 20, 2013)

Brief description: An intelligent designer
Academic Community: The University of Chicago

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I built Scholarly Insider to provide you with an engaging, feature-rich and intellectual-driven community. In my free time, I enjoy reading philosophical literature, hiking and kickin' it with friends.

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  • By Brian December 20, 2013
    Many new lectures have been added to OpenCourse Channels! They're very informative videos! Enjoy!
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    This site is growing step-by-step; it would be very helpful if you all post content to get this going strong!
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Maurine Kornfeld, AB’42, AM’48, wishes she could make it back for more University of Chicago reunions, but they tend to conflict with her swim meets.

The 97-year-old Kornfeld, who set her first world record at age 90, was inducted into the International Masters Swimming Hall of Fame in 2018. She has set seven long-course and 20 short-course international masters records in the individual medley, freestyle and backstroke. (A long-course, or Olympic-size pool, is 50 meters; a short-course pool is 25 yards.) At the 2017 World Masters Championships in Budapest, she was the oldest woman competing in the meet, setting a world record in the 95–99 age group in the 800-meter freestyle. In four world championships, she has won 14 gold and four silver medals.

Today she swims with the Rose Bowl Aquatics team in Pasadena, driving four times a week from her home in the Hollywood Hills. Her favorite event is the 200-meter backstroke, but a greater attraction for her is the camaraderie.

“I want to get up at five in the morning to see my swim pals,” she said. “Meeting and connecting with people who are different from oneself, who are younger, different ethnic backgrounds, all kinds of occupations—it’s both amazing and wonderful. It’s a little like being back at the University of Chicago.”

Her studies at UChicago made as big of an impression on Kornfeld as her fellow students. She remembers taking The History of Ideas with University President Robert Maynard Hutchins and Prof. Mortimer Adler: “It was a pretty heady experience.”

UChicago fostered a love of literature, evident at her Hall of Fame induction ceremony last September when she quoted Robert Browning’s poem “Rabbi Ben Ezra”: “Grow old along with me. The best is yet to be. The last of life, for which the first is made.” Later in the speech she mused: “I’m so glad they say it’s healthy to swim, because even if it weren’t, I’d do it.”

But when she started competing in 1987, she was just trying to find a time to work out. Her full-time job as a social worker left her Saturday mornings free, but when she went to the pool at the YMCA in Glendale, California, the staff told her it was closed for masters swimming practice. If she wanted to swim at that time, she’d have to join the team.

Despite having no competitive experience at all, she called the coach.

“He said, ‘What’s your stroke?’” and I said, “‘None in particular.’”

At her first practice, she had no idea what the coach meant when he told her to swim a 50. “Fortunately he pointed to the end of the pool and back,” she said—25 yards each way. “He kept shouting at me, ‘put your face down.’ I didn’t know anything about goggles. I just liked to swim.”

She stuck with it, and two months later the coach told her she’d be swimming in her first meet. As the only swimmer in the 65–69-year-old novice division, she won two blue ribbons: in the 50-yard freestyle and the 50-yard backstroke, which were the only strokes she knew.

When she’s not swimming, Kornfeld works as a docent at the Los Angeles County Museum of Art—a role she stumbled into when she was there doing research for an art history course she was taking. She also gives tours at Los Angeles’s Union Station, the Frank Lloyd Wright–designed Hollyhock House and the House of Blues.

Her only frustration: “There are always more things to do than there’s time to do them.”

—This story first appeared on the University of Chicago Magazine website.

December 31, 1969

Four University of Chicago Law School alumni will clerk for U.S. Supreme Court justices during the 2019-20 term. At least one Law School graduate has clerked on the High Court for at least part of each term since 1972, but this year’s numbers are notable because they coincide with record growth in overall clerkship employment among Law School graduates.

Kelly Holt, JD’17, and Stephen Yelderman, JD’10, will clerk for Justice Neil Gorsuch; Mica Moore, JD’17, will clerk for Justice Elena Kagan; and Caroline Cook, JD’16, will clerk for Justice Clarence Thomas. They will follow Madeline Lansky, JD’16, who is clerking for Thomas this term, and Aimee Brown, JD’14, who is clerking for Justice Samuel Alito and now-retired Justice Anthony Kennedy. All six alumni clerked on the U.S. Court of Appeals before earning their Supreme Court spots.

“These are four extraordinary lawyers who were each tremendously successful students at the Law School and whose futures couldn’t be brighter,” said Lior Strahilevitz, the Sidley Austin Professor of Law, who co-chairs the faculty clerkship committee with Jonathan Masur, the John P. Wilson Professor of Law. “Supreme Court justices are hardly alone in noting the remarkable quality of our graduates. Throughout the federal and state judiciaries, Chicago students and alumni are in especially high demand.”     

It is typical for the Law School to have multiple alumni clerking on the Supreme Court at once: In 37 of the past 47 years, two or more clerks on the Supreme Court have been graduates of the Law School. In 15 of those years, four or more Supreme Clerks have been Chicago alumni—including in 1993, when there were eight, and 1994, when there were seven. There were four at one time as recently as 2017.

Law School alumni traditionally have done well securing clerkships on the lower courts, too, but expanded efforts to counsel aspiring clerks have further boosted those numbers in recent years. In 2018, 27 percent of students entered state or federal clerkships immediately after graduation—the highest figure in recent memory, and more than double the 12.9 percent who entered clerkships immediately after graduation in 2013.

“More and more of our students come to law school hoping to clerk,” said Masur, “and they’re right to want to. Clerkships are great jobs, great learning experiences and great opportunities to find a lifelong mentor. They can also jump-start a student’s career. Our goal as a clerkship committee is to tell students about the advantages of clerking and then to help find a clerkship for each and every student who wants one.”

The faculty clerkship committee expanded several years ago to include Profs. Genevieve Lakier, John Rappaport and Daniel Hemel. Every member of the committee is a former clerk, and they share their deep knowledge of the experience, the judges and the application process with students, guiding them during law school and, often, for several years after.

The Law School also works to expose students to the judiciary through programs like the Edward H. Levi Distinguished Visiting Jurist lecture series. Since the program began in 2013, more than two dozen judges have visited the Law School, delivering lunch talks and often meeting with a small group of students and faculty. Recent visiting jurists have included Merrick Garland, Chief Judge of the D.C. Circuit;  Michelle Friedland of the Ninth Circuit, Timothy Tymkovich, Chief Judge of the Tenth Circuit; Cheryl Krause of the Third Circuit; Jeffrey S. Sutton of the Sixth Circuit; John Z.  Lee of the U.S. District Court for the Northern District of Illinois, and Beryl Howell, chief judge of the US District Court for the District of Columbia.

Clerkships on lower courts are an important step for students seeking to clerk on the Supreme Court. Holt, who currently works at Jones Day, clerked for Judge J. Harvie Wilkinson III on the Fourth Circuit after graduation. Yelderman, currently a law professor at the University of Notre Dame, clerked for Gorsuch on the Tenth Circuit in 2010. Moore, who is clerking for Vince Chhabria on the U.S. District Court for the Northern District of California, previously clerked for Judge William Fletcher on the Ninth Circuit in 2017. And Cook, who is clerking for Judge Gregory Katsas on the D.C. Circuit, clerked for Judge Diane Sykes on the Seventh Circuit in 2016.

But the clerkship experience also is valuable for students entering careers in big law firms and other areas of the profession.

“So much of law school is about learning how judges decide cases,” said Masur. “What better way to gain that knowledge than to work closely with a judge? Whether a student’s destination is public interest or a large law firm, transactional practice or litigation, I can hardly think of a more valuable way to spend a year after graduation.”

Adapted from a story that first appeared on the University of Chicago Law School website.

December 31, 1969

Organic electronics could allow companies to print electronics like paper or incorporate them into clothing to power wearable electronics—if there were only better ways to control their electronic structure.

To help address this challenge, Nick Jackson, a postdoctoral fellow in the University of Chicago’s Institute for Molecular Engineering, developed a faster way of creating molecular models by using machine learning. The models dramatically accelerate the screening of potential new organic materials for electronics, and could also be useful in other areas of materials science research.

Many believe organic electronics have the potential to revolutionize technology with their high cost-efficiency and versatility, but the current manufacturing processes used to produce these materials are sensitive, and the internal structures are extremely complex. This makes it difficult for scientists to predict the final structure and efficiency of the material based on manufacturing conditions.

Shortly after Jackson began his appointment under Juan de Pablo, the Liew Family Professor in Molecular Engineering at the University of Chicago, he had the idea to tackle such problems with machine learning. He uses this technique—a way of training a computer to learn a pattern without being explicitly programmed—to help make predictions about how the molecules will assemble.

Many materials for organic electronics are built via a technique called vapor deposition. In this process, scientists evaporate an organic molecule and allow it to slowly condense on a surface, producing a film. By manipulating certain deposition conditions, the scientists can finely tune the way the molecules pack in the film.

“It’s kind of like a game of Tetris,” said Jackson, who is a Maria Goeppert Mayer Fellow at Argonne National Laboratory. “The molecules can orient themselves in different ways, and our research aims to determine how that structure influences the electronic properties of the material.”

The packing of the molecules in the film affects the material’s charge mobility, a measure of how easily charges can move inside it. The charge mobility plays a role in the efficiency of the material as a device. In order to optimize the process, collaborating with scientist Venkatram Vishwanath of the Argonne Leadership Computing Facility, the team ran extremely detailed computer simulations of the vapor deposition process.

“We have models that simulate the behavior of all of the electrons around each molecule at nanoscopic length and time scales,” said Jackson, “but these models are computationally intensive, and therefore take a very long time to run.”

To simulate entire devices, often containing millions of molecules, scientists must develop “coarser” models. One way to make a calculation less computationally expensive is to pull back on how detailed the simulation is—in this case, modeling electrons in groups of molecules rather than individually. These coarse models can reduce computation time from hours to minutes; but the challenge is in making sure the coarse models can truly predict the physical results.

This is where the machine learning comes in. Using an artificial neural network, the machine learning algorithm learns to extrapolate from coarse to more detailed models—training itself to come to the same result using the coarse model as the detailed model.

The resulting coarse model allows the scientists to screen many, many more arrangements than before—up to two to three orders of magnitude more. Armed with these predictions, experimentalists can then test them in the laboratory and more quickly develop new materials.

Materials scientists have used machine learning before to find relationships between molecular structure and device performance, but Jackson’s approach is unique, as it aims to do this by enhancing the interaction between models of different length and time scales.

Although the targeted goal of this research is to screen vapor-deposited organic electronics, it has potential applications in many kinds of polymer research, and even fields such as protein science. “Anything where you are trying to interpolate between a fine and coarse model,” he added.

Citation: “Electronic Structure at Coarse-Grained Resolutions from Supervised Machine Learning.” Jackson et al, Science Advances, March 22, 2019. Doi: 10.1126/sciadv.aav1190

Funding: Argonne Laboratory Directed Research and Development, U.S. Department of Energy

—Article originally appeared on the Argonne National Laboratory website

December 31, 1969