Don’t isolate. Congregate! Join Penn Engineering’s Office of Diversity, Equity, and Inclusion to meet six dynamic men and learn about how their bonds of friendship and NSBE affiliation benefited them personally and professionally. Hear their story and engage in Q&A for the first hour (7PM-8PM). Then, meet someone new in breakout groups (8PM-8:30PM). An additional […]
Abstract: The concept of “x-ray vision” is widely understood to be the ability to see through structures that are not transparent to the human eye. This concept would be a useful feature for surgeons and surgical robots, particularly when navigating complex anatomy. The Photoacoustic & Ultrasonic Systems Engineering (PULSE) Lab is developing imaging systems to […]
Abstract: Many-body systems from soap bubbles to suspensions to polymers learn the drives that push them far from equilibrium. This learning has been detected with thermodynamic properties, such as work absorption and strain. We progress beyond these macroscopic properties that were first defined for equilibrium contexts: We quantify statistical mechanical learning with representation learning, a […]
Fireside Chat with Dr. CJ Taylor Date: Friday, February 26th Time: 4:00 - 5:00 PM EST Join USABE on Friday, February 26th at 4 PM for a conversation with Dr. CJ Taylor, Associate Dean for Diversity, Equity, and Inclusion at Penn Engineering, to discuss his experiences in STEM and engineering and his role as a […]
Physical Sciences in Oncology Center PSOC@Penn Spring 2021 Webinar Series Mondays at 12:00 noon (EST) For webinar links, please contact manu@seas.upenn.edu.
Machine learning has led to powerful advances in robotics: deep learning for visual perception from raw images and deep reinforcement learning (RL) for learning controls from trial and error. Yet, these black-box techniques can often require large amounts of data, have results difficult to interpret, and fail catastrophically when dealing with out-of-distribution data. In this […]
Taming topological electronic phases is a fundamental challenge and an important milestone on the way towards novel electronic devices and topological quantum computation. Recent advances in fabrication techniques have made van der Waals (vdW) heterostructures one of the most active platforms for the experimental investigation of topological electronic phases in 2D. Moiré superlattices, which arise […]
Unlike the problem of safe task and motion planning in a completely known environment, the setting where the obstacles in a robot's workspace are not initially known and are incrementally revealed online has so far received little theoretical interest, with existing algorithms usually demanding constant deliberative replanning in the presence of unanticipated conditions. Moreover, even […]
Software is everywhere, and almost everywhere, software is broken. Some bugs just crash your printer; others hand an identity thief your bank account number; still others let nation-states spy on dissidents and persecute minorities. This talk outlines my work preventing bugs using a blend of programming languages techniques and systems design. First, I'll talk about […]
Abstract: For successful integration of autonomous systems such as drones and self-driving cars in our day-to-day life, they must be able to quickly adapt to ever-changing environments, and actively reason about their safety and that of other users and autonomous systems around them. Even though control-theoretic approaches have been used for decades now for the […]
Abstract Metal-organic frameworks (MOFs) are a versatile class of nanoporous materials synthesized in a “building-block” approach from inorganic nodes and organic linkers. By selecting appropriate building blocks, the structural and chemical properties of the resulting materials can be finely tuned, and this makes MOFs promising materials for applications such as gas storage, chemical separations, sensing, […]
Across healthcare, science, and engineering, we increasingly employ machine learning (ML) to automate decision-making that, in turn, affects our lives in profound ways. However, ML can fail, with significant and long-lasting consequences. Reliably measuring such failures is the first step towards building robust and trustworthy learning machines. Consider algorithmic fairness, where widely-deployed fairness metrics can […]