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BE Seminar: “Dissecting Multicellular Therapeutic Responses Using a Large-scale Single-cell Profiling Platform” (Siyu Chen)

This event will be held virtually via Zoom (check email or contact ksas@seas.upenn.edu). Human diseases are fundamentally multicellular in nature with many different cell types contributing to disease progression and treatment response. However, how therapeutics impact each cell type in a heterogeneous population remains poorly understood because most studies are focused on isolated cell types […]

GRASP On Robotics: “Photoacoustic Vision for Surgical Robots”

Zoom

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 […]

MEAM Seminar: “Fusion for Robot Perception and Controls”

Zoom - Email MEAM for Link peterlit@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 […]

MEAM Ph.D. Thesis Defense: “Reactive Planning with Legged Robots in Unknown Environments”

Zoom - Email MEAM for Link peterlit@seas.upenn.edu

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 […]

Spring 2021 GRASP SFI: “Safe and Data-efficient Learning for Robotics”

Zoom

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 […]

CBE Seminar: “Metal-Organic Frameworks as Tunable Platforms for Gas Storage, Chemical Separations and Catalysis”

Zoom - Email CBE for link

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, […]

ESE Seminar: “High-Level Synthesis of Dynamically Scheduled Circuits”

Zoom - Email ESE for Link jbatter@seas.upenn.edu

The slowdown in transistor scaling and the end of Moore's law indicate a need to invest in new computing paradigms; specialized hardware devices, such as FPGAs and ASICs, are a promising solution as they can achieve high processing capabilities and energy efficiency. However, a major barrier to the global success of specialized computing is the […]

GRASP On Robotics: “Advancing Innovations for Robotic Teams in Complex Environments”

https://upenn.zoom.us/j/96715197752

Abstract: Complex real-world environments continue to present significant challenges for fielding robotic teams, which often face expansive spatial scales, difficult and dynamic terrain, degraded environmental conditions, and severe communication constraints. Breakthrough technologies call for integrated solutions across autonomy, perception, networking, mobility, and human teaming thrusts. As such, the DARPA OFFSET program and the DARPA Subterranean […]

ESE Seminar: “Reliable Machine Learning in Feedback Systems”

Zoom - Email ESE for Link jbatter@seas.upenn.edu

Machine learning techniques have been successful for processing complex information, and thus they have the potential to play an important role in data-driven decision-making and control. However, ensuring the reliability of these methods in feedback systems remains a challenge, since classic statistical and algorithmic guarantees do not always hold. In this talk, I will provide […]