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CHESTNUT HILL, MASS The Atlantic Coast Conference announced the 2023 All-ACC Fencing Academic Team on Monday afternoon. Academic requirements for selection to the All-ACC Academic Team are a 3.0-grade point average for the previous semester and a 3.0 cumulative average during one's academic career. In addition, student-athletes must compete in either the ACC Championship or NCAA Championship this season in the sport of fencing.

There were 19 Eagles represented on this year's Fencing All-Academic team, 10 from the BC Men's Team and nine from the Women's Team.

Boston College Fencing 2023 All-ACC Academic Fencing Team Selections Full List:

Men:(Name, Weapon, Class, Major)Sanjeet Brar, Sabre, Fr., Computer ScienceBalint Czaha, Sabre, Fr., ManagementDaniel Gaidar, Epee, Jr., Computer ScienceRyan Ho, Foil, So., UndeclaredBin Huang, Foil, Sr., ManagementLevi Hughes, Epee, So., EconomicsInigo Rivera, Sabre, Jr., ManagementBrian Wang, Foil, Sr., ManagementZachary Westen, Epee, Sr., PhilosophyColin Yu, Epee, Jr., Management

Women:(Name, Weapon, Class, Major)Taylor Cho, Foil, So., EconomicsSamantha Davidson, Foil, Sr. Environmental ScienceGreta DeBack, Foil, Fr., Political ScienceGianina DiDonato, Epee, Sr., PhilosophyKatarina Hone, Sabre, Sr., International StudiesAnisha Kundu, Epee, So., ManagementRachel Liu, Sabre, Jr., HistoryEmma Su, Sabre, Fr., BiologySamantha Yeh, Foil, Jr., Management

Read more:

ACC Announces 2023 All-ACC Fencing Academic Team - Boston College Athletics

Six times a year the Cordes Teaching and Faculty Support Center publishes a newsletter of advice for first-year faculty at the U of A. Newsletters for spring 2023 are posted in partnership with the University of Arkansas Libraries and Special Collections using ScholarWorks, a nationwide repository for academic works. Advice is provided from faculty at the U of A in the newsletter to aid in a successful first year as a faculty member.

For February 2023 the theme was advice on how to overcome obstacles to engage in research and service. Contributors were Jack Kern, professor ofhealth, human performance and recreation; Rebecca Miles, clinical assistant professor of marketing;Molly Jensen, clinical associate professor of marketing;Carole Shook, teaching assistant professor of information systems; andPaul Calleja, associate dean for administration inthe College of Education and Health Professions. Accessthe newsletter.

For March 2023 the theme was advice from this year's teaching award winners on connecting with students. Contributors were Susan Gauch, professor of computer science and computer engineering;Hope Ballentine, teaching assistant professor in the Eleanor Mann School of Nursing; Heather Walker, teaching assistant professor of chemical engineering;Alex Nunn, assistant professorof law;and Jared Phillips, teaching assistant professor of international and global studies. Access the newsletter.

For April 2023 the theme was the value in mentoring honors students. Contributors were Molly Rapert, associate professor of marketing; Paul Adams, professor of chemistry/biochemistry and cellular and molecular biology;Kelly Sullivan, associate professor of industrial engineering; Kelly Way, associate professor of human environmental sciences; Rachel Glade, director of the Communication Sciences and Disorders Program;andNoah Billig, associate professor of landscape architecture.Access the newsletter.

The Cordes Center for Teaching and Faculty Support was founded in 1992. Numerous programs are offered each semester, both in person and on Zoom. The newsletter was designed to provide advice from campus teaching leaders to aid those who are new in academia or the U of A. For more information, visit the TFSC website at:www.teaching.uark.edu.

Excerpt from:

Fast Five With Cordes Teaching and Faculty Support Center ... - University of Arkansas Newswire

The U.S. Department of Energys (DOE) Argonne National Laboratory is making exciting advances in quantum information science (QIS). QIS explores how tiny particles sense and relay information in new ways. The research could lead to a quantum computer that performs previously impossible calculations or an exceptionally secure network for transmitting data.

The recent milestones play out on small scales: across the space of a few seconds or across a single layer of atoms. Though measured in minuscule increments, each advance contributes to new ways to harness quantum mechanics for computing, communication and sensing.

Quantum information research has been mostly about the science until recently. Now, especially over the past decade, theres been increased interest in turning the science into technology. Supratik Guha

Argonne is a hub for quantum technology research, pioneering work that dates back to Argonne emeritus scientist Paul Benioffs groundbreaking theoretical proposal for a quantum computer in the 1980s. Today, research continues through Argonnes QIS research and its leadership of Q-NEXT, a DOE National Quantum Information Science Research Center. Here are three ways Argonne research has been pushing the frontiers of QIS.

In the quantum world, information can be conveyed via a single electron the part of an atom that carries a negative electric charge or a particle of light. The ability to store and manipulate such particles requires the development of materials that can be controlled at subatomic levels. Argonne scientists have assembled a material based on copper and carbon monoxide molecules to mimic graphene, a promising but difficult-to-make host for quantum data.

This novel quantum test bed confirmed predictions about the behavior of electrons in graphene.

Its incredibly rare for an experimental system to match theoretical predictions so perfectly, said Dan Trainer, who worked on the project while he was a postdoctoral appointee at Argonne.

To both assemble and study the material, Trainer and colleagues used a scanning tunneling microscope at Argonnes Center for Nanoscale Materials, a DOE Office of Science user facility.

Researchers also have made important strides with other materials that could be used for quantum applications. A team at Argonne and the University of Chicago created a record-breaking qubit the quantum version of a computer bit from the accessible and inexpensive compound silicon carbide. Qubits can be difficult to read efficiently, and their signals are notoriously fleeting, lasting on the order of milliseconds. The qubit was able to be read on demand, and its quantum state stayed intact for over five seconds.

In another study, Argonne researchers demonstrated the use of pure diamond membranes as platforms for storing and processing quantum information. DOEs Small Business Innovation Research (SBIR) and Small Business Technology Transfer (STTR) awards are funding further research on a method to commercially produce this quantum diamond material. The diamond concept is part of broader research aimed at exploiting defects in crystals for quantum systems. Diamond membranes belong to a group of materials, solid-state spin qubits, that was featured on the cover of a special issue of the journal Nature Reviews Materials.

Quantum computers and related technologies rely on a fundamental understanding of how atoms and their constituents behave, and how they might be tuned to represent data in a quantum system. Computer simulations can reveal the dynamics of quantum objects in ways no experiment could match. In one study, researchers showed how missing atoms known as vacancies in crystalline materials could be transformed into quantum information.

By performing computer simulations at the atomic scale with high-performance computers, we can watch defects forming, moving, disappearing and rotating in a sample over time at different temperatures, said Elizabeth Lee, a postdoctoral researcher in the UChicago Pritzker School of Molecular Engineering who worked on the project. This is something that cannot be done experimentally, at present.

In another study, Argonne researchers used quantum computers to simulate quantum materials. The study tackled the problem of noisy calculations on quantum computers, a problem where interference from the hardware causes the computer to return slightly different results for the same operation. By simulating different states of qubits in a quantum computing system, the researchers arrived at a proposed method for improving its accuracy on calculations.

Both of these studies drew, in part, on resources provided by the Argonne Leadership Computing Facility, a DOE Office of Science user facility.

Argonne convenes some of the worlds foremost experts in QIS. By partnering on activities as varied as workshops, movie screenings and undergraduate fellowships, the lab is fostering crucial conversations and collaborations in this burgeoning field.

Partnerships are key: Q-NEXT has drawn more than 20 from industry and academia, most recently Amazon Web Services, the Massachusetts Institute of Technology and JPMorgan Chase.

A recent report from Q-NEXT, A Roadmap for Quantum Interconnects, laid out the necessary work ahead to develop the technologies for distributing quantum information between systems and across distances to enable quantum computing, communications and sensing.

Quantum information research has been mostly about the science until recently, said Supratik Guha, Q-NEXT chief technology officer, discussing the roadmap. Now, especially over the past decade, theres been increased interest in turning the science into technology.

Argonne will soon officially open theArgonne Quantum Foundry, a national resource for creating and delivering high-quality materials forquantumdevices.It is one of two national foundries that will support Q-NEXT research. The opening of a secondfoundry at DOEs SLAC National Accelerator Laboratory is imminent.

The foundries will have a positive impact not just for research, but also for thequantumecosystem, providing a robust supply chain of materials from which industry and other U.S. stakeholders will benefit, said Q-NEXT Director David Awschalom, who is also an Argonne senior scientist, the Liew Family Professor of Molecular Engineering and vice dean for research and infrastructure at the University of Chicago Pritzker School of Molecular Engineering, and the director of the ChicagoQuantumExchange. We expect that, as a unique facility in the Midwest, the ArgonneQuantumFoundrywill accelerate progress inquantuminformation science both for the region and the nation.

Read the rest here:

How Argonne is pushing the boundaries of quantum technology ... - Argonne National Laboratory

The Team Behind the Tool

Moore has spent much of his career looking for ways to battle sepsis. Recognizing the diagnostic potential of AI, he sought to collaborate with UVA experts.

He phoned a friend, UVA Engineerings Rich Nguyen.

Nguyen, an assistant professor in the Department of Computer Science, who also has an appointment in the School of Data Science, specializes in AI. He put together the cross-disciplinary team.

Were aiming in this collaboration for the computer scientists and the data scientists to be embedded into the clinical settings, Nguyen said.

The two fourth-year students have served as his research assistants.

Edwards, the statistics major, is minoring in computer science and social entrepreneurship. Boner, a Rodman Scholar, gained experience as a software research intern and as an extern with Cisco before starting on the sepsis project.

As part of their work, the students spent time in the medical ICU, making rounds with medical teams under the direction of Drs. Taison Bell and Kyle Enfield.

Behind the computer, The team has developed a data engineering pipeline, Nguyen said. They perform statistical and computational analysis on large-scale clinical data, which allows for fast experimentation with different machine learning models.

The team also includes Joy Qiu, a 2020 School of Data Science alumna, who works at the Center for Advanced Medical Analytics in the UVA School of Medicine.

Computer science alumni Matthew Pillari, a 2022 graduate, and Navid Jahromi, a 2021 graduate, were previously on the project. Pillari is now a machine learning engineer at Imagen, while Jahromi is a software engineer at Palantir Technologies.

Its important to note that no health care decisions have yet been made based on the tool.

Thats because the AI is still learning. And in order to learn, the AI is dipping into a vast archive of biometrics. The data is essentially played back, as if in real time, starting with the beginning of a patients stay.

Were feeding the AI a bunch of datasets, Boner said. The model is learning to match those data to tell us either, yes, the patient had bloodstream infection, or no, they didnt have bloodstream infection. We have that ground truth from the medical records. And, so, the AI is learning patterns in the time series that we have, and patterns in the way that a patients condition is changing over time, that might suggest bloodstream infection.

The effort is looking closely at specific types of patients, such as transplant recipients, because they can have differing physiological responses to infection, Moore said.

Thats resulted in some new discoveries.

Transplant patients are immunocompromised, the doctor explained. Thats due to receiving anti-rejection medicines. They are thought to not mount the same clinical signature of physiological response to infection as immunocompetent patients.

Our data suggest that they do, in fact, mount a robust response. But its likely not the same response as an immunocompetent patient. This finding may help us better identify bloodstream infections in this patient population.

One dilemma for doctors caring for transplant patients is intervention versus risk. Overuse of antibiotics, for example, can lead to antibiotic resistance and other unintended effects.

Having AI that can read the nuanced differences among individuals would allow for better-informed, more personalized care.

Like the technology itself, the students have been doing a lot of deep learning.

Edwards said she learned about the challenges associated with using AI in medicine. Being able to gain the direct insights of doctors and other medical professionals boosted her own understanding, she said. In turn, she hopes that translates to the tool.

Within our research, I focus specifically on explainable artificial intelligence, she said. Explainability refers to an AI models ability to explain its behavior in human terms. Many of the most powerful machine learning models are so complex that the way they make predictions isnt clearly understood. Explainability is critical for building trust in a machine learning model, and its especially important in a clinical setting where lives are at stake.

She added that, no matter where her career ends up taking her, she hopes to continue working at the intersection of technology and social impact.

Boner, in addition to contributing to the AIs deep-learning layers, wrote a conference paper with Nguyen and Moore as part of an undergraduate consortium.

Through this project, Ive learned, first and foremost, how to do research, Boner said. Ive collaborated with both technical and non-technical researchers toward a common goal, which has been very valuable.

He plans to pursue a doctorate in computer science at Duke University, where hell be focusing on interpretable AI for health care applications.

Moore praised both students many contributions to the project.

Louisa and Zack have been integral members of our research team, Moore said. Not only are they extremely talented and technically gifted in computer science and AI, but they are also intellectually curious and bring a fresh set of eyes and ideas to the problem of infection detection in the ICU. They have been a pleasure to work with, and Ive learned a lot from them.

Currently, the AI has the combined wisdom of 40,500 anonymized patient records, consisting of 4.1 million laboratory measurements, from which to draw.

Continued here:

Class of '23: UVA Developed AI To Spot Early Sepsis. 2 Undergrads ... - UVA Today