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Peter Hamlington, Department of Mechanical Engineering, University of Colorado Boulder The Structure and Dynamics of Puffing Plumes The near-field characteristics of highly buoyant plumes, commonly referred to as lazy plumes, remain relatively poorly understood across a range of flow conditions, particularly compared to our understanding of far-field characteristics. Buoyant plumes...

Dorit Hammerling, Department of Applied Mathematics and Statistics, Colorado School of Mines Lossy Data Compression and the Community Earth System Model Climate models such as the Community Earth System Model (CESM) typically produce enormous amounts of output data, and storage capacities have not increased as rapidly as processor speeds over...

Bri-Mathias Hodge; Department of Electrical, Computer, and Energy Engineering; University of Colorado Boulder Designing a Sustainable and Reliable Future: Simulating Next Generation Energy Systems Power and energy systems worldwide are changing rapidly in the face of the global challenge of decarbonization and the subsequent addition of more distributed and variable...

Steffen Borgwardt, Department of Mathematics, University of Colorado Denver Transitions between Clusterings Clustering is one of the fundamental tasks in data analytics and machine learning. In many situations, different partitions of the same data set become relevant. For example, different algorithms for the same clustering task may return dramatically different...

Xudong Chen; Department of Electrical, Computer and Energy Engineering; University of Colorado Boulder Structure Theory for Nonholonomic Ensemble Systems Ensemble control deals with the problem of using a common control input to simultaneously steer a large population (in the limit, a continuum) of individual control systems. In this talk, we...

Farhad Pourkamali-Anaraki, Department of Mathematical and Statistical Sciences, University of Colorado Denver Evaluation of Classification Models in Limited Data Scenarios with Application to Additive Manufacturing Scientific observations and experiments provide valuable data to build machine learning (ML) models that reveal links between input variables and quantities of interest. Specifically, adopting...

Daniel Larremore, Department of Computer Science, University of Colorado Boulder Estimating the Mitigation Potential of Screening Programs for Infectious Diseases The premise of screening programs for infectious diseases is that screening tests taken on the individual level have effects on population transmission. How can we estimate those effects? What data...

Applied Mathematics Colloquium - George Karniadakis George Karniadakis, Department of Applied Mathematics, Brown University From Neural PDEs to Neural Operators: Blending data and physics for fast predictions Abstract: We will review physics-informed neural network and summarize available extensions for applications in computational mechanics and beyond. We will also introduce new...

Alex Townsend, Department of Mathematics, Cornell University The art and science of low-rank techniques Matrices and tensors that appear in computational mathematics are so often well-approximated by low-rank objects. Since random ("average") matrices are almost surely of full rank, mathematics needs to explain the abundance of low-rank structures. We will...

Habib Ammari, Department of Mathematics, Eidgenössische Technische Hochschule Zürich, Switzerland Functional analytic methods for discrete approximations of subwavelength resonator systems In this lecture, the speaker will review mathematical and computational frameworks to elucidate physical mechanisms for manipulating waves in a robust way at scales beyond the diffraction limit using subwavelength...