This will be a hybrid event with in-person attendance in Levine 307 and virtual attendance on Zoom. ABSTRACT The Spring 2025 GRASP SFI Student Lightning Talks will highlight the research of three GRASP Lab Master's or early PhD students whose presentation topics have been nominated by their faculty advisors and voted on by their GRASP peers. […]
Quantum Dots: From Curiosity to Technological Impact The combination of quantum effects, nanometer dimensions and a chemical synthesis make quantum dots a platform for exploring new size-dependent fundamental properties and a sandbox for developing new applications. This talk will cover the origin story of chemically synthesized quantum dots, their basic physics, the synthesis that unlocked […]
Particle assemblies form interconnected pockets of empty space that are hot spots for activity in many applications and natural phenomenon that deal with particulate matter. In my lab we explore the use of interlinked soft microparticle assemblies as scaffolds for cell culture in vitro and to promote regenerative wound healing in vivo. The open space that is created […]
Over the past decade, large-scale pre-training followed by alignment has revolutionized natural language processing and computer vision. Yet, robotics remains constrained by the scarcity of real-world data. In this talk, I will present our systematic approach to overcoming this bottleneck by building increasingly rich world models from data. I will first introduce our distilled feature […]
Zoom link: https://upenn.zoom.us/j/98220304722 Abstract: Modern ML models produce valuable predictions across various applications, influencing people’s lives, opportunities, and scientific advancements. However, these systems can fail in unexpected ways, generating unreliable inferences and perpetuating biases present in the data. These issues are particularly troubling in high-stakes applications, where models are trained on increasingly diverse, incomplete, and […]
Artificial intelligence (AI) is transforming scientific discovery, particularly in materials science, by accelerating the prediction and design of materials with desired properties. Traditional physics-based modeling of atomic systems is computationally prohibitive for large-scale problems, and AI addresses this challenge by learning the underlying physics from data, thereby accelerating discoveries. In this talk I will present […]
Flexible rod-like structures such as nanotubes and nanowires have found significant interest in nanoelectronic applications. Likewise, with the recent advancement in soft robotics and additive manufacturing, an important goal is to optimally design architected slender metamaterials and further derive their effective mechanical properties through homogenization techniques. However, modeling such structures as a flexible continuum body […]
Coupling of spins and light can enable photon-mediated scaling and control in quantum technologies, as demonstrated in trapped atom, ion, and solid-state spin qubits. Molecular analogs of such systems hold promise as a nascent qubit platform that can leverage the tools of synthetic chemistry to tailor quantum properties and integrate in nanoscale devices but have […]
Cyber-physical systems (CPS), powered by emerging artificial intelligence (AI) technologies, have become integral to various critical domains such as the Internet of Things (IoTs), medical devices, and autonomous vehicles. A unique aspect of these systems lies in their interactions with the physical world, by perceiving environments through heterogeneous modalities (perception), processing digital data with intelligence […]
Abstract: Controlling language models is key to unlocking their full potential and making them useful for downstream tasks. Successfully deploying these models often requires both task-specific customization and rigorous auditing of their behavior. In this talk, I will begin by introducing a customization method called Prefix-Tuning, which adapts language models by updating only 0.1% of […]
