We present a new perspective on online learning that we refer to as gradient equilibrium: a sequence of iterates achieves gradient equilibrium if the average of gradients of losses along […]
Graph Neural Networks (GNNs) are the tool of choice for scalable and stable learning in graph-structured data applications involving geometric information. My research addresses the fundamental questions of how GNNs […]
Zoom link: https://upenn.zoom.us/j/98220304722
The compute demands of AI and robotics continue to rise due to the rapidly growing volume of data to be processed; the increasingly complex algorithms for higher quality of results; […]
Zoom link: https://upenn.zoom.us/j/98220304722
This Symposium celebrates Kurt Petersen for his pioneering research and development of micro-electromechanical systems (MEMS) technology – microscopic systems that merge mechanical and electrical functionality and which have wide ranging […]
