Presenter: Dr. Ke Du, Associate Professor of Chemical and Environmental Engineering, University of California, Riverside Description: Miniaturized micro- and nanofluidic systems, integrated with biochemistry, microscopy, nanomaterials, and computer vision algorithms, […]
Presented by: Bree McEwan Description: One of the potential use cases of virtual reality is to create spaces where humans can interact with each other or virtual agents across distances. However, […]
Vision encoders have demonstrated significant performance gains in visual generation and multimodal reasoning. These improvements are primarily attributed to the scaling of data, model capacity, and compute. However, this progress is becoming less accessible due to a lack of transparency in data curation and training recipes. In combination with the high compute requirements of foundation-scale […]
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 […]
Kings of Infinite Space: Courageous Compassion Among Men in Soledad Prison “I could be bounded in a nutshell, and count myself king of infinite space…” –Hamlet When I reflect on […]