Presenter: Jason Yik, PhD Candidate, Harvard SEAS Description: Recent research on neuromorphic accelerators has investigated their efficiency and performance benefits for machine learning (ML) inference at the edge. This talk […]
Presenter: Akira Horiguchi, Visiting Assistant Professor, University of California, Davis Description: Many modern statistical applications involve a two-level sampling scheme that first samples subjects from a population and then samples observations on each subject. These schemes often are designed to learn both the population-level functional structures shared by the subjects and the functional characteristics specific […]
Presenter: Professor Yulia R. Gel, Virginia Tech Description: Multilayer networks continue to gain significant attention in many areas of study, particularly, due to their high utility in modeling interdependent systems such as critical infrastructures, human brain connectome, and socio-environmental ecosystems. However, clustering of multilayer networks, especially, using the information on higher order interactions of the […]
The United Nations (UN) and the Baskin School of Engineering at the University of California, Santa Cruz, are collaborating to bring the “Reboot the Earth” hackathon to the West Coast for the first time. This is a social event bringing together aspiring developers to create open source software solutions that address the climate crisis, including […]
Presenter: Hanna Kim, Assistant Professor, Psychology Department, UCSC Description: Understanding how an intervention works is a central question in behavioral and social research, following the demonstration of its overall effect. Traditional mediation analysis techniques often assume a homogeneous mechanism of effects, overlooking both validity concerns and subgroup variation in causal pathways. In this talk, I […]
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 […]
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
Presenter: Subhadeep Paul, Associate Professor, Ohio State University Description: In the first part of the talk, we consider the problem of Transfer Learning (TL) under heterogeneity from a source to […]
Presenter: Guannan Wang, Associate Professor, The College of William & Mary Description: Generative AI has emerged as a powerful tool for synthesizing biomedical images, offering new solutions to challenges such […]
Presenter: Yunyi Shen, Ph.D. Candidate, Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology Description: Practitioners often aim to infer an unobserved population trajectory using sample snapshots at […]
Presenter: Jiaqi Li, William H. Kruskal Instructor, University of Chicago Description:Modern machine learning (ML) algorithms achieve remarkable empirical success, yet providing rigorous statistical guarantees remains a major challenge, particularly in […]
Presenter: Qi Xu, Postdoctoral Researcher, Department of Statistics & Data Science, Carnegie Mellon University Description: Multi-modality data are increasingly common across science medicine and technology, such as imaging, text, sensors, […]
Presenter: Sifan Liu, Assistant Professor, Department of Statistical Science, Duke University Description:Mean-field variational inference (MFVI) approximates a target distribution with a product distribution in the standard coordinate system, offering a scalable approach to Bayesian inference but often severely underestimating uncertainty due to neglected dependence. We show that MFVI can be greatly improved when performed along […]
Join Baskin Engineering to celebrate National Engineers Week with a sweet stop at the Transform Your Future Pop-Up (Cookies Included!) đȘâ This yearâs Engineers Week theme, Transform Your Future, is a powerful reminder that engineering doesnât just shape our worldâit shapes our opportunities, our communities, and the futures we can imagine for ourselves. Swing by […]
Curious how being part of a research lab can supercharge your experience as a Baskin Engineer?  Join us for this informative event to learn about opportunities to solve open-ended problems, build deeper technical skills, and learn how to think like an engineer. Weâll kick things off with a quick overview of the kinds of research […]
Discover innovation at the Baskin Engineering Club Bash, an event celebrating National Engineers Week! Mark your calendars for Thursday, February 26, 12â2 PM in the BE Courtyard! The BE Club Bash brings together student organizations across all engineering disciplines to showcase their projects, demos, and interactive activities. Stop by to: Explore hands-on booths and demonstrations from student organizations Learn about engineering opportunities on […]
Presenter: Francois Ribalet, Research Associate Professor, School of Oceanography, University of Washington Description: François Ribalet will present new observational technologies and computational approaches for studying phytoplankton responses to ocean warming. Using SeaFlow, a custom-built automated flow cytometer deployed on over 100 research cruises, his team has collected nearly 850 billion cell measurements across global oceans. […]
Presenter: Amanda Coston, Assistant Professor, University of California Berkeley Description: Performance evaluation plays a central role in decisions about whether and how predictive algorithms should be deployed in high-stakes settings. Yet, in many real-world domains, evaluation is fundamentally difficult: the data available for assessment are often biased, incomplete, or noisy, and the act of deploying […]
Presenter: Amanda Coston, Assistant Professor, University of California Berkeley Description: Performance evaluation plays a central role in decisions about whether and how predictive algorithms should be deployed in high-stakes settings. […]
Presenter: Oscar Hernan Madrid Padilla, Assistant Professor, University of California, Los Angeles Description: In the first part of the talk, I will introduce TRansfer leArning via guideD horseshoE prioR (TRADER), […]