This event is presented by the Wharton Accountable AI Lab and co-sponsored by the Wharton AI & Analytics Initiative; Penn Engineering; the Center for Technology, Innovation & Competition; and the Perry World House. The Penn AI Governance […]
We have made exciting progress in AI by massive models on massive amounts of data center compute. However, the demands for AI are rapidly expanding. I identify how to maximize […]
This will be a hybrid event with in-person attendance in Wu and Chen and virtual attendance on Zoom. ABSTRACT As the population ages, the need grows for AI agents to […]
In today’s data-driven landscape, vast unstructured data sources — like documents and electronic health records (EHRs) — demand advanced AI tools to unlock their full potential. Generative AI, powered by large language models (LLMs), is becoming indispensable for […]
Abstract: Despite recent advances in catalytic conversion of plastic waste into high-value chemicals, the interactions between the polymers and catalysts, which are highly porous nanomaterials, are not well understood. Fundamental […]
The theory of homogenization provides a systematic approach to the derivation of macroscale constitutive laws, obviating the need to repeatedly resolve complex microstructure. However, the unit cell problem which defines […]
Abstract: Large Language Models (LLMs) are vulnerable to adversarial attacks, which bypass common safeguards put in place to prevent these models from generating harmful output. Notably, these attacks can be […]
This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. ABSTRACT As AI-enabled systems become integral to critical domains, their robustness is increasingly […]
Abstract: Electrifying the chemical industry has been much touted as a path to a low-carbon future, but nearly all pathways of interest are electrochemical reductions. If we want water-to-hydrogen, CO2-to-chemicals, […]
With finite resources to complete tasks like monitoring, coverage, and search, the challenge lies in identifying and performing tasks that can change both in frequency and location. One potential solution […]
This talk presents the Advanced Research Projects Agency-Energy (ARPA-E) and how stakeholders at the University of Pennsylvania can engage in a dialog with the funding agency. ARPA-E advances high-risk high-impact […]
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 […]