For many processes important for life such as cell division, cell migration, and the development of organs, the spatially and temporally correct formation of biological patterns is essential. To understand these processes, the principal task consists not in explaining how patterns form out of a homogeneous initial condition, but in explaining how simple patterns change into increasingly complex ones. Illuminating the mechanisms of this complex self-organization on various spatial and temporal scales is a key challenge for science. So-called “coarse-graining” techniques allow such multiscale systems to be simplified, such that they can be described with a reduced model at large length and time scales. “The price you pay for coarse-graining, however, is that important information about the patterns on small scales – like the pattern type – is lost. But the thing is that these patterns play a decisive role in biological systems. To give one example, they control important cellular processes,” explains Laeschkir Würthner, a member of the team led by LMU physicist Prof. Erwin Frey and the lead writer of a new study that overcomes this issue. In collaboration with the research group of Prof. Cees Dekker (TU Delft), Frey’s team has developed a new coarse-graining approach for so-called mass-conserving reaction-diffusion systems, in which the large-scale analysis of the total densities of the particles involved enables the prediction of patterns on small scales.

The scientists illustrated the potential of their approach with the Min protein system, a paradigmatic model for biological pattern formation. The bacterium E. coli uses various Min proteins circulating in a cell to determine at which location cell division takes place. A decisive factor here is that the proteins involved occur at different frequencies depending on their location in the cell and chemical state – which is to say, they have a variety of different densities. “We’ve now managed to reduce the complexity of this system by developing a theory that is based solely on the total densities of the proteins, such that we can completely mirror the dynamics of pattern formation,” says Frey. “This is a huge reduction. The numerical computations are now accomplished in a matter of minutes instead of months.”

The researchers were able to experimentally confirm theoretical predictions of the model, according to which distribution of the proteins depends on the geometry of the environment. They did this by reconstructing the Min protein system in an in-vitro flow cell, with the results showing the same protein patterns as were revealed in the simulation. “Such reconstruction of information at a small length scale from reduced dynamics at the macroscopic level opens up new pathways for a better understanding of complex multiscale systems, which occur in a broad range of physical systems,” says Frey.

Dr. Donald C. Wunsch II, the Mary K. Finley Missouri Distinguished Professor of Electrical and Computer Engineering at Missouri University of Science and Technology, has been appointed founding director of the university’s Kummer Institute Center for Artificial Intelligence and Autonomous Systems. Wunsch will begin his duties on Dec. 1, when he completes his appointment as a program director in the National Science Foundation’s Energy, Power, Control and Networks program. 

As founding director, Wunsch will lead the development of the new center’s mission, vision, and strategic plan to develop a nationally recognized research center focused on the rapidly evolving fields of artificial intelligence and autonomous systems. Ultimately, the center will deploy the latest machine learning and artificial intelligence techniques to advance the performance and intelligence of a range of robotic and autonomous solutions. Wunsch will also be responsible for leveraging the breadth of capabilities and expertise among S&T’s faculty to strengthen collaboration with and among several university-based research centers.

The center was founded to spur regional, national and global development in artificial intelligence and autonomous systems, in alignment with the vision of the Kummer Institute for Student Success, Research and Economic Development at Missouri S&T. Late St. Louis entrepreneur Fred Kummer, a Missouri S&T graduate, and his wife June donated $300 million to Missouri S&T in October 2020 to establish the Kummer Institute. Their donation is the largest single gift ever to any public or private university in Missouri and one of the largest to any university.

“Mr. Kummer recognized the potential artificial intelligence and autonomous systems have to truly change the world,” says Dr. Kamal Khayat, interim vice chancellor for research and innovation at S&T. “I am pleased to welcome someone as accomplished and capable as Dr. Wunsch to lead our institute’s innovative efforts in these two truly transformative disciplines. The insights and expertise he has acquired throughout his career will be an asset to the entire S&T community as he steps into this new role.”

Before joining S&T in 1999, from 1984 to 1993, Wunsch worked for Boeing, culminating in his role as a senior principal scientist. In 1993 he joined Texas Tech University as an assistant professor with a joint appointment to the departments of electrical and computer engineering and computer science; he was promoted to associate professor at Texas Tech in 1998. He joined the electrical and computer engineering department at S&T in 1999 and has courtesy appointments in system engineering, computer science, business administration and mathematics, and statistics. In 2005, Wunsch served as president of the International Neural Networks Society (INNS), which bestowed upon him its Gabor Award in 2015 and its Ada Lovelace Award in 2019. He is a Fellow of the INNS and the Institute of Electrical and Electronics Engineers (IEEE) and was twice the Charles Hedlund Distinguished Visiting Professor at the American University in Cairo. Wunsch has mentored 23 Ph.D. recipients in computer engineering, electrical engineering, systems engineering, and computer science.

Wunsch’s research has focused on unsupervised learning, also known as clustering, particularly hierarchical and real-time versions; adaptive resonance and reinforcement learning architectures; hardware and applications; and various multidisciplinary collaborations. He has more than 500 publications to his credit, including 12 books.

“I feel honored and grateful for the phenomenal opportunity to help develop the Kummer Institute Center for Artificial Intelligence and Autonomous Systems,” Wunsch says. “For over two decades, I’ve been amazed at the novelty, diversity, and impact of S&T research. I look forward to supporting collaborations across campus, across our region, and around the world as we grow and intensify our competitiveness in these incredibly transformational fields. I would like to hear from internal and external stakeholders about how AI and Autonomous Systems can help them achieve their goals.”  

Wunsch earned a doctorate in electrical engineering and a master’s degree in applied mathematics from the University of Washington in 1991 and 1987, respectively. He also earned an executive M.B.A. from Washington University in 2006 and a bachelor’s degree in applied mathematics from the University of New Mexico in 1984 and completed the Jesuit Core Honors Program at Seattle University in 1981.

The Center for Artificial Intelligence and Autonomous Systems is one of four new research centers established through the Kummer Institute. The Center for Advanced Manufacturing is led by Dr. Richard Billo, who joined S&T in January. National searches for founding directors continue for the Center for Advanced and Resilient Infrastructure and the Center for Resource Sustainability.