Celebrate Penn Engineering's 2024 Doctoral Graduates. Additional information is available on the Penn Engineering Commencement website.
Celebrate the Penn Engineering 2024 Master's Graduates. Additional information is available on the Penn Engineering Commencement website.
Penn Engineering invites all alumni, family and friends to join us for the dedication of two new hallway installations that honor the past while inspiring the future. Join Dean Kumar to reconnect with classmates and hear remarks from notable alumni. Breakfast will be provided at 9:00am, program begins at 9:45 a.m. Click to see the […]
Celebrate the Penn Engineering Undergraduate Class of 2024. Additional information is available on the Penn Engineering Commencement website.
On Monday, May 20, 2024, from 12:15-2:15 p.m., Penn Engineering will host an Open House for the School’s returning graduates and their families throughout the first floors of the main Engineering complex, immediately following the University Ceremony. Included are photo booth opportunities, a t-shirt giveaway (including a live t-shirt press!), and light refreshments. Please join […]
*This seminar will be held in-person in Wu and Chen as well as virtually via Zoom. ABSTRACT Over the past year, the large language model has achieved significant milestones, approaching human-like intelligence across various domains. However, there has been limited investigation into large-scale 3D reconstruction in the literature. In this talk, I will primarily focus […]
The Department of Bioengineering at the University of Pennsylvania and Dr. Rob Mauck are pleased to announce the Doctoral Dissertation Defense of Elisabeth Lemmon. Title: Biologic Delivery to Preserve Joint Health and Promote Tissue Repair Date: May 28, 2024 Time: 10:00 AM Location: JMB Class of ’62 Auditorium Zoom link - https://upenn.zoom.us/j/93923840583?pwd=Tjl5bE1rMEFESlJKRm9ROEYzSU1VZz09 Please email elemmon@vet.upenn.edu for the zoom […]
Low-rank matrix completion is a well-studied problem, for which a rich theory exists, mainly from the optimization and statistical points of view. However, the majority of the theoretical analysis in the literature assumes random observation patterns. On the other hand, the pattern of observed entries depends on the nature of each application, and is usually […]
Silicon's advanced fabrication processes have enabled the miniaturization of complex electronic systems, enhancing performance and efficiency. Recent technological developments have further expanded silicon's utility to integrate photonic systems, merging electronic and photonic technologies on a single chip. This integration has opened new avenues for high-speed communication and computation, attracting significant interest from both research and […]
Contact interactions, including adhesion and friction, are critical to the design of many engineered systems. Currently, most systems rely on materials with static mechanical properties, requiring careful selection of materials to realize effective systems for specialized tasks. However, with advances in smart materials, system design is no longer limited to materials with static properties. There […]
Given the widespread use of deep learning models in safety-critical applications, ensuring that the decisions of such models are robust against adversarial exploitation is of fundamental importance. In this thesis, we discuss recent progress toward designing algorithms that exhibit desirable robustness properties. First, we discuss the problem of adversarial examples in computer vision, for which […]