Amy Orsborn – UW News

Three UW scientists named Sloan Fellows

UW News staff — Tue, 18 Feb 2025 15:21:25 +0000

Three UW faculty members have been awarded fellowships from Sloan Foundation. The new fellows are Amy L. Orsborn,
assistant professor of electrical & computer engineering and bioengineering, Dianne J. Xiao, an assistant professor of chemistry, and Amy X. Zhang, an assistant professor of computer science. Photo: ��Ӱ�Ӵ�ý

Three ��Ӱ�Ӵ�ý faculty members have been awarded early-career fellowships from the Alfred P. Sloan Foundation. The new Sloan Fellows, announced Feb. 18, are , the Clare Boothe Luce assistant professor of electrical & computer engineering and bioengineering, , an assistant professor of chemistry, and , an assistant professor of computer science in the Paul G. Allen School of Computer Science & Engineering.��

Since the first Sloan Research Fellowships were awarded in 1955, and including this year’s fellows, 131 faculty from ��Ӱ�Ӵ�ý have received a Sloan Research Fellowship, according to the Sloan Foundation.��

Sloan Fellowships are open to scholars in seven scientific and technical fields — chemistry, computer science, Earth system science, economics, mathematics, neuroscience and physics — and honor early-career researchers whose achievements mark them among the next generation of scientific leaders.��

The 126  were selected by researchers and faculty in the scientific community. Candidates are nominated by their peers, and fellows are selected by independent panels of senior scholars based on each candidate’s research accomplishments, creativity and potential to become a leader in their field. Each fellow will receive $75,000 to apply toward research endeavors.��

This year’s fellows come from 51 institutions across the United States and Canada.��

Orsborn’s research aims to understand how neurons in our brains work together to let us learn to move in many different ways. She uses engineering technologies like brain-computer interfaces to manipulate how neural activity relates to movement, which gives researchers new ways to link neural activity to computations related to how they believe the brain may perform. She also uses collaborations with theorists to build models that help researchers bridge from experimental data to computational principles.��

“We can quickly adapt our tennis skills to the pickleball court, but it also takes years to perfect a piano concerto,” Orsborn said. “Our flexibility likely comes from our brain’s ability to learn in many ways, but we don’t understand how neurons actually implement different learning computations. I hope to build bridges between computational principles and biological implementation, which will ultimately help us build therapies to restore movements lost due to injuries like stroke.”��

Xiao’s research program designs new porous materials to address unsolved challenges in clean energy and chemical sustainability. These include developing new porous adsorbents that can use renewable electricity to drive chemical processes, as well as new porous catalysts that can convert sustainable feedstocks into useful products.��

“Porous materials are the bedrock of industrial heterogeneous catalysis and chemical separations. Many of the chemicals we use in our daily lives have, at some point, been purified or chemically transformed within nano-sized pores,” Xiao said. “Going forward, new breakthroughs in porous materials synthesis are needed to harness renewable energy sources and chemical feedstocks. With the support of this award, along with the collaborative ecosystem at the UW, we hope to realize these synthetic breakthroughs faster, better and more cheaply.”��

Zhang’s research reimagines the design of online social platforms to empower the public to take control of their online experiences. Inspired by offline public institutions and political theory, she creates novel social computing systems for collaborative governance of online communities and AI. She also develops tools for personal and collective customization on social media and approaches for encouraging pro-social public discourse.��

“Digital platforms comprise socio-technical infrastructure that are crucial to the lives of millions, yet today they are governed and designed by a select few,” Zhang said. “As a result, many people do not see themselves represented in the decisions made and possible configurations supported by the major platforms they use. But putting the onus on end users to figure it out themselves can be overwhelming. I develop toolkits and interactive techniques informed by user needs to scaffold the process of customization, enabling both flexibility and ease of use.”��

Contact Orsborn at aorsborn@uw.edu; Xiao at djxiao@uw.edu; and Zhang at axz@cs.uw.edu. ��

New NSF-funded institute to harness AI for accelerated discoveries in physics, astronomy and neuroscience

James Urton — Tue, 28 Sep 2021 16:44:13 +0000

Aerial view of ��Ӱ�Ӵ�ý campus in Seattle. Photo: Alex Alspaugh/��Ӱ�Ӵ�ý

Science is in the midst of a data deluge: Experiments are churning out more information than researchers can process. But a new endeavor, centered on artificial intelligence, will help scientists navigate this data-rich reality.

On Sept. 28, the National Science Foundation ��a $15 million, five-year grant to integrate AI tools into the scientific research and discovery process. The award will fund the Accelerated AI Algorithms for Data-Driven Discovery Institute — or A3D3 Institute — a partnership of nine universities, led by the ��Ӱ�Ӵ�ý.

The A3D3 Institute aims to accelerate the discovery pipeline by providing scientists with new, paradigm-shifting AI tools for analyzing the types of large and complex datasets that are an increasingly common feature of research — from medical laboratories to particle colliders.

Shih-Chieh Hsu Photo: ��Ӱ�Ӵ�ý

“I have been fortunate to work with an exceptional group of talented researchers, and am thrilled to continue to be a part of solving some of the most fundamental issues in science and engineering. The ultimate goal of A3D3 is to construct the institutional knowledge essential for real-time applications of AI in any scientific field,” said , a UW associate professor of physics and director of the A3D3 Institute. “A3D3 will empower scientists with new tools to deal with the coming data deluge through dedicated outreach efforts.”

The A3D3 Institute — part of the NSF’s Harnessing the Data Revolution program — is a collaboration among researchers at the ��Ӱ�Ӵ�ý; the University of Illinois at Urbana-Champaign; Duke University; the Massachusetts Institute of Technology; the University of Minnesota, Twin Cities; the California Institute of Technology; Purdue University; the University of California, San Diego; and the University of Wisconsin–Madison.

In addition to Hsu, other UW faculty involved with the A3D3 Institute are , professor of electrical and computer engineering; , assistant professor of bioengineering and of electrical and computer engineering; and , associate professor of applied mathematics and of electrical and computer engineering.

A3D3 will combine innovations in AI algorithms and computing platforms with research applications in physics, astronomy and neuroscience. Photo: Philip Harris/Massachusetts Institute of Technology

From detectors searching for gravitational waves to electrical sensors monitoring the activity of the brain, research is handing scientists ever-larger datasets to analyze. Experiments are generating more data in part because researchers are developing better tools, from sharper medical imaging techniques to more precise sensors for particle physics experiments. A single experiment at CERN’s , for example, 1 petabyte of data — that’s 1 million gigabytes — per second from tens of millions of collisions. But as datasets increase in size and complexity, the algorithms needed to analyze data and put the most relevant bits — or bytes — before the eyes of scientists run the risk of outstripping current computing capacity.

A3D3 research will focus on developing AI-based algorithms that can perform real-time analyses of large datasets in three data-rich fields: multi-messenger astrophysics, high-energy particle physics and neuroscience.

Scott Hauck Photo: ��Ӱ�Ӵ�ý

“The advancement of computing power from machine learning techniques on high-performance computing platforms is providing exciting new avenues for scientific discovery, while the unique challenges in high-speed and high-throughput data collection for science applications drive new demands for researchers,” said Hauck.

Multi-messenger astrophysics integrates observations of the cosmos from diverse sources — including gravitational wave detectors, neutrino detectors and telescopes — to identify and study sudden and often violent events in the cosmos like supernovae, stellar collisions and black hole mergers. A3D3 researchers will work to develop AI algorithms that can quickly identify these events and help astronomers to cross-correlate observations of the same event from different sources, building a more complete picture of the types of transient events in our sky.

High-energy physics experiments, such as those studied by Hsu at the Large Hadron Collider, have the potential to upend our understanding of the universe by discovering new types of particles — like candidate dark matter particles — as well as new fundamental forces. A3D3 efforts will focus on AI-fueled approaches to detect unexpected anomalies in collision data and “reconstruct” the particles underlying 40 million collisions per second that occur in high-energy experiments. These tools will streamline the downstream analysis processes, accelerating and simplifying the pipeline of discovery.

Amy Orsborn Photo: ��Ӱ�Ӵ�ý

In neuroscience, A3D3 efforts will center on understanding the complex neural networks within the human brain that govern motor functions and process sensory information.

“We can now measure more of the brain for longer periods of time. We need new tools to analyze these massive datasets,” said Orsborn, who is also a core staff scientist at the Washington National Primate Research Center. “Analyzing data quickly will also enable new experiments and therapies where we can intervene based on ongoing brain activity.”

Researchers need AI-based algorithms to analyze neural datasets in real time — such as electrical recordings from implanted electrodes and for a wide range of basic science studies. A3D3 researchers will focus on developing these types of tools, which can help decipher the neural underpinnings of behaviors like basic motor functions and responses to stimuli.

Eli Shlizerman Photo: ��Ӱ�Ӵ�ý

“Critically, A3D3 researchers will focus on developing scalable analysis tools, which can adapt not just to the datasets of today, but also to the massive and intricate datasets expected in the coming decades,” said Shlizerman.

With the rapid growth in the amount of data generated by scientific research, the A3D3 Institute also has its eyes on the future. The institute will pursue training and research opportunities for both graduate and undergraduate students, including students from backgrounds that are underrepresented in STEM communities. These endeavors will ensure that A3D3’s impact spreads and endures beyond its immediate goals, said Hsu.

For more information, contact Hsu at schsu@uw.edu.