This free, half-day event for undergraduates is hosted by the National Science Foundation Artificial Intelligence-driven RNA BioFoundry (AIRFoundry). Led by experts from the University of Pennsylvania and University of Puerto Rico, Mayagüez, the […]
From silo discharge and granular avalanches to the erosion of granular beds, granular materials play a central role in many industrial and environmental processes. While significant advances have been made […]
Abstract: Global transition to clean energy relies on the development of efficient hydrogen storage materials and hydrogen evolution reaction (HER) catalysts—two primary chemistries investigated in this thesis. MXenes, a family […]
Generative models are revolutionizing our world, with the ability to generate photorealistic visual content that are indistinguishable from reality. Despite their overwhelming presence in the cyber world, they haven’t been […]
Join President J. Larry Jameson and Provost John L. Jackson, Jr. along with the Penn AI Council for the launch of Penn AI. Senior Vice Provost for Research Dawn Bonnell […]
Abstract: Machine learning applications are increasingly reliant on black-box pretrained models. To ensure safe use of these models, techniques such as unlearning, guardrails, and watermarking have been proposed to curb […]
This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. ABSTRACT What do diffusion models/flow matching, Gaussian splatting and efficient transformer architectures have […]
Abstract: Recent technical advances are leading to a rapid transformation of the chemical palette available in cells, thus making it conceivable to produce nearly any organic molecule of interest—from biofuels […]
One of our key research areas focuses on developing innovative nanoplatforms for cancer diagnosis, treatment, and therapy-response monitoring. We aim to understand material-biosystem interactions and design nanoparticles capable of delivering […]
Zoom link: https://upenn.zoom.us/j/98220304722 Abstract I will present recent work by my research group on the design and analysis of stochastic-gradient-based algorithms for solving nonconvex constrained optimization problems, which may […]
