Tag: Baskin Engineering
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AM Seminar: Data Driven Modeling for Scientific Discovery and Digital Twins
Presenter: Dongbin Xiu, Professor, Ohio State University Description:We present a data-driven modeling framework for scientific discovery, termed Flow Map Learning (FML). This framework enables the construction of accurate predictive models for complex systems that are not amenable to traditional modeling approaches. By leveraging data and the expressiveness of deep neural networks (DNNs), FML facilitates long-term…
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AM Seminar: Multiscale Modeling of Cellular Membranes and Oncogenic Proteins
Presenter: Liam Stanton, Professor, San Jose State University Description: In this talk, I will present a multiscale model for cellular membranes, which is trained on molecular dynamics simulations. The model is constructed within the formalism of dynamic density functional theory and can be extended to include features such as the presence of proteins and membrane…
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AM Seminar: Science in the Age of Foundation Models
Presenter: Dr. Danielle Robinson, AWS AI Description: In this talk, I will discuss the large impact of foundation models within the sciences with a particular focus on the importance of physical constraints and uncertainty quantification. First, I will detail our novel ProbConserv framework for enforcing hard constraints within black-box deep learning models. ProbConserv provides uncertainty…
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Kathleen Schmidt: Sequential Experimental Design for Materials Strength Model Calibration
Presenter: Katie Schmidt, UQ & Optimization Group Leader, Lawrence Livermore National Laboratory Description: Due to the time and expense associated with physical experiments, there is significant interest in optimal selection of the conditions for future experiments. Selection based on reduction in parameter uncertainty provides a natural path forward. We consider this type of optimal sequential…
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AM Seminar with Dr. Truong Vu
Presenter: Dr. Truong Vu, IPAM and MSU Description: We present a framework for the gradient flow of sharp-interface surface energies that couple to embedded curvature active agents. We use a penalty method to develop families of locally incompressible gradient flows that couple interface stretching or compression to local flux of interfacial mass. We establish the…
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Be Inspired: Explore Graduate Studies in STEM
Not sure if graduate school is right for you? Join us to learn what graduate school is really about and explore whether it’s the right path for you. We’ll cover topics such as qualifying exams, funding options, common misconceptions, and more! Click the link below to register for the event: https://ucsc.zoom.us/webinar/register/WN_31OHhwc7QPqJ7nSyiuAUNg
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Summer Live in the Schedule of Classes
The Summer Session Schedule of Classes goes live today. Explore course descriptions, prerequisites, and meeting times to start planning early for summer enrollment. Email summer@ucsc.edu with questions or call 831-459-5373.
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CSE Colloquium: Making Systems Secure with Information Flow
Presenter: Andrew Myers, Cornell University Abstract: Modern civilization depends on complex, interconnected software systems that must safeguard trustworthy or private data. We have ever-growing mountains of code yet lack principled ways to build large systems that are secure. What is missing is a way to securely build these systems compositionally: module by module and layer…
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CSE Colloquium – Neurosymbolic AI: from research to industry
Presenter: Luis Lamb, Catholic Institute of Technology Abstract: Neurosymbolic AI brings together the statistical nature of machine learning with the formal reasoning capabilities of symbolic AI. It seeks to offer a balanced approach to contemporary AI technologies, by combining the ability to learn from data, with the capacity to reason upon knowledge acquired from an environment.…
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CSE Colloquium – Flux: Refinement Types for Verified Rust Systems
Presenter: Ranjit Jhala, UCSD Abstract: Rust has risen as a language of choice for new systems code — from OS kernels to hypervisors, firmware and run-times — as it is memory safe and provides the sort of abstractions needed for efficient low-level systems implementation. We present Flux, a refinement type checker for Rust that shows how…