Title: Modeling Zoonotic Infectious Diseases from Wildlife to Humans Speaker: Prof. Linda J. S. Allen, P. W. Horn Distinguished Professor Emeritus Texas Tech University Abstract: Zoonotic infectious diseases are diseases transmitted from animals to […]
Title: Solving the Race in Backgammon Speaker: Prof. Arthur Benjamin Smallwood Family Professor of Mathematics Harvey Mudd College Abstract: Backgammon is perhaps the oldest game that is still […]
Title: Exploiting metric structure for more accurate classification Speaker: Mike Izbicki, Department of Mathematical Sciences, Claremont McKenna College Abstract: Classification problems often have many semantically similar classes. For example, the famous ImageNet dataset […]
Title: Interrupted Time Series Models for Assessing Complex Health Care Interventions Maricela Cruz, PhD Assistant Investigator Biostatistics Unit Kaiser Permanente Washington Health Research Institute Abstract: Assessing the impact of complex interventions on measurable health outcomes is a growing concern in health care and health policy. According to the 2018 Annual Review of Public Health, interrupted time […]
Title: Quantitative Approaches to Social Justice Prof. Chad Topaz (he/him/his) Co-Founder and Executive Director of Research, QSIDE Institute Professor of Mathematics, Williams College Abstract: Civil rights leader, educator, and investigative journalist Ida B. Wells said that "the way to right wrongs is to shine the light of truth upon them." This talk will demonstrate how […]
Title: Topic Models, Methods, and Medicine Speaker: Prof. Jamie Haddock (Harvey Mudd College) Abstract: There is currently an unprecedented demand for efficient, quantitative, and interpretable methods to study large-scale (often multi-modal) data. One key area of interest is that of topic modeling, which seeks to automatically learn latent trends or topics of complex data sets, […]
Abstract: This talk discusses multiple methods for clustering high-dimensional data, and explores the delicate balance between utilizing data density and data geometry. I will first present path-based spectral clustering, a […]
Abstract: Classification is a fundamental task in data science and machine learning, and in the past ten years there have been significant improvements on classification tasks (e.g. via deep learning). However, recently there have been a number of works demonstrating that these improved algorithms can be "fooled" using specially constructed adversarial examples. In turn, there […]
In this talk, we present reduced order models (ROMs) for turbulent flows, which are constructed by using ideas from large eddy simulation (LES) and variational multiscale (VMS) methods. First, we give a general introduction to reduced order modeling and emphasize the connection to classical Galerkin methods (e.g., the finite element method) and the central role […]
Abstract: The system of shallow water equations and related models are widely used in oceanography to model hazardous phenomena such as tsunamis and storm surges. Unfortunately, the inherent uncertainties in the system will inevitably damage the credibility of decision-making based on the deterministic model. The stochastic Galerkin (SG) method seeks a solution by applying the […]
Abstract: I will overview the following different wave phenomena in integrable nonlinear wave equations: (1) universal patterns in the dynamics of fluxon condensates in the semi-classical limit; (2) modulational instability of periodic travelling waves; (3) rogue waves on the background of periodic and double-periodic waves. Main examples include the sine-Gordon equation, the nonlinear […]
TBA
