Published: April 7, 2021 By

Two Department of Electrical, Computer and Energy Engineering faculty members have won CAREER Awards from the National Science Foundation — a recognition of both their early career success and of their potential to serve as role models in research and education at CU Boulder. CAREER Awards provide $500,000 over five years to help advance his research.  

New imaging technique could help catch osteoarthritis early

About Shu-Wei Huang
Shu-Wei Huang headshotBefore joining the CU Boulder faculty in 2017, Huang was an assistant research professor at University of California Los Angeles and completed a postdoctoral fellowship at Columbia University. He holds PhD and MS degrees from the Massachusetts Institute of Technology and a BS in electrical engineering from National Taiwan University.

Osteoarthritis is a leading cause of pain and disability among U.S. adults, and the costs associated with diagnosis, treatment and lost wages nationwide are estimated to be in the billions each year.

Assistant Professor Shu-Wei Huang wants to develop imaging techniques to catch the disease in its early stages, when it still has the potential to be reversed.

In this common form of arthritis, the cartilage that protects the ends of the bones breaks down over time, often affecting the joints in the hands, knees and hips. Huang said scientists have identified some early stage biomarkers of osteoarthritis that occur before cartilage is permanently damaged, but current imaging techniques aren’t sensitive enough to “see” them.

“We need to develop a new imaging technology capable of providing microscopic information of articular cartilages that is inaccessible by the state-of-the-art musculoskeletal radiology, like CT scans, ultrasonography and MRIs,” he said.

Huang proposes combining two promising imaging techniques – photoacoustic microscopy and dual-comb spectroscopy – to establish the first dual-comb photoacoustic microscopy for deep- tissue musculoskeletal spectro-imaging.

On their own, each technique has limitations. However, when combined, Huang believes they will allow doctors to see deeper into the body more quickly, making diagnosis more efficient and cost-effective.

“In the future, these technologies could also be applicable to other research fields like surgical guidance, cancer assessment, transcranial neuroimaging and stimulation,” he added.

Huang plans to collaborate with researchers in CU Boulder’s Biomedical Engineering Program and on the CU Anschutz Medical Campus, where he is already involved in the AB Nexus initiative. That effort combines expertise in medical and clinical research at Anschutz with engineering and life sciences research at CU Boulder.

New framework will enable better control of large networked systems

About Xudong Chen
Xudong Chen headshotBefore coming to CU Boulder in 2016, Chen was a postdoctoral researcher in the Coordinated Science Lab at the University of Illinois at Urbana-Champaign. He earned his PhD in electrical engineering from Harvard University and his BS, in electronic engineering, from Tsinghua University in Beijing.

Multi-agent systems (MAS) are ubiquitous in nature and science, from flocks of birds and neurons in the brain, to social networks and quantum spin systems. That makes the question of how to control these natural or manmade systems a popular problem for engineers.

Assistant Professor Xudong Chen wants to develop a new framework for controlling large MAS that will make these networks more resilient and scalable. 

In his research proposal, Chen explained that existing approaches to controlling multi-agent systems rely on forming one big network, wherein the controller steers a few leading agents, with the rest of the agents sensing what the leader is doing and playing follow-the-leader. But as those networks get bigger, they also get more fragile and unwieldly.   

“The idea is, in fact, simple: Instead of controlling a large complex network, we steer a population of small ones,” Chen said.

In his proposed framework, agents of a MAS form independent networks of relatively small size.

“We then control the MAS by using a few common control inputs to simultaneously steer all of the individual networks,” Chen said. “The proposed framework will be able to accommodate arbitrarily many individual networks and, meanwhile, achieve controllability with a fixed number of control inputs.”

To establish the framework, his team will have to integrate ensemble control theory and networked control theory in an approach they’re calling “ensemble control of network motifs.” Chen said the focus on infinite ensembles of networked control systems makes the approach adaptable to various problems, including unmanned aerial systems, micro-robotic systems, quantum systems and biological networks.

Chen said he also looks forward to incorporating this approach into courses for both graduate and undergraduate students.

“This is an opportunity to integrate interdisciplinary research aspects (mathematics, systems and controls, and computer science) into the undergraduate curriculum at an early stage,” he said. “I plan to make a dedicated effort to engage students from various departments at CU Boulder.”