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    • Career Steps Before Graduation Seminar

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    Auditorium, LRSM Building 3231 Walnut Street, Philadelphia, PA, United States

    On Friday, April 12,2024, the Department of Materials Science and Engineering is hosting an information session dedicated to equipping you with insights on the essential steps to secure a career after graduation, with staff from UPenn Career Services and ISSS (International Student and Scholar Services) lending their expertise on prevailing job trends and providing guidance […]

    CBE Doctoral Dissertation Defense: “A Multifaceted Approach to CO2 Emissions Reductions and Removals” (Maxwell Pisciotta)

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    Wu and Chen Auditorium (Room 101), Levine Hall 3330 Walnut Street, Philadelphia, PA, United States

    Abstract: The scientific consensus is that climate change is not only actively occurring, but that it is irrevocably due to human activities associated with greenhouse gas emissions. Greenhouse gas emissions have been accumulating in the atmosphere since the beginning of the industrial revolution. This thesis specifically focuses on one greenhouse gas in particular, CO 2 […]

    BE Doctoral Dissertation Defense: “The Origin and Factors Affecting Differentiation of Progenitor Cells in Tendon-to-Bone Integration” (Tim Kamalitdinov)

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    Smilow Center for Translational Research in SCTR 11-146AB

    The Department of Bioengineering at the University of Pennsylvania and Dr. Nat Dyment are pleased to announce the Doctoral Dissertation Defense of Tim Kamalitdinov. Title: The Origin and Factors Affecting Differentiation of Progenitor Cells in Tendon-to-Bone Integration Date: April 16, 2024 Time: 9:00 AM Location: SCTR (Smilow Center for Translational Research) 12-146AB The public is welcome […]

    ESE PhD Thesis Defense: “Multiferroic Micro Electromechanical Systems for Magnetic Sensing and Wireless Power Transfer in Biomedical Applications”

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    Fisher Bennett Hall, Room 401 3340 Walnut Street, Philadelphia, PA, United States

    Multiferroic micro-electromechanical systems (MEMS) enable small, room temperature, low power magnetic sensing and wireless power transfer (WPT) in biomedical applications. Current biomagnetic sensing relies on sensitive magnetometers like superconducting quantum interference devices (SQUIDs), but their reliance on cryogenic temperatures is undesirable.   This thesis presents the theory, design, microfabrication, and characterization of multiferroic MEMS magnetic […]

    MEAM Seminar: “Cardiovascular Engineering – A ‘Personal’ Journey from Bench to Bedside”

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    Wu and Chen Auditorium (Room 101), Levine Hall 3330 Walnut Street, Philadelphia, PA, United States

    Over the past few decades, significant contributions have been made by engineers to healthcare. The successful translation of fundamental engineering concepts has helped improve patient care and diagnosis. This impact has been particularly evident in the field of cardiovascular medicine where the roles of fluid and solid mechanics, and imaging are critical. In ~45 years […]

    ESE Spring Seminar – “Scaling Deep Learning Up and Down”

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    Raisler Lounge (Room 225), Towne Building 220 South 33rd Street, Philadelphia, PA, United States

    Deep learning with neural networks has emerged as a key approach for discovering patterns and modeling relationships in complex data. AI systems powered by deep learning are used widely in applications across a broad spectrum of scales. There are strong needs for scaling deep learning both upward and downward. Scaling up highlights the pursuit of […]

    Webinar: “Engineering in the Age of AI”

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    Join Penn Engineering faculty to learn how to harness the power of AI for innovation. Dean Vijay Kumar will moderate a discussion with Michael Kearns, Professor and National Center Chair in Computer and Information Science (CIS); Surbhi Goel, Magerman Term Assistant Professor in CIS; and René Vidal, Rachleff University Professor, with joint appointments in Electrical […]

    ASSET Seminar: “Reasoning Myths about Language Models: What is Next?” (Dan Roth, University of Pennsylvania)

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    Raisler Lounge (Room 225), Towne Building 220 South 33rd Street, Philadelphia, PA, United States

    ABSTRACT:  The rapid progress made over the last few years in generating linguistically coherent natural language has blurred, in the mind of many, the difference between natural language generation, understanding, and the ability to reason with respect to the world. Nevertheless, robust support of high-level decisions that depend on natural language understanding, and one that […]

    BE Doctoral Dissertation Defense: “Deep Learning for Unpaired Domain Adaptive Medical Image Segmentation” (Yuemeng Li)

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    The Department of Bioengineering at the University of Pennsylvania and Dr. Yong Fan are pleased to announce the Doctoral Dissertation Defense of Yuemeng Li. Title: Deep Learning for Unpaired Domain Adaptive Medical Image Segmentation Date: April 17, 2024 Time: 1:00PM-3:00PM Location: BRB Auditorium Zoom link The public is welcome to attend.

    ESE PhD Thesis Defense: “Cellular Cosheaves, Graphic Statics, and Mechanics”

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    Greenberg Lounge (Room 114), Skirkanich Hall 210 South 33rd Street, Philadelphia, PA, United States

    Methods from algebraic topology enable simplifications and extensions of fundamental concepts in structural and mechanical engineering. Chief among these tools are cellular sheaves and cosheaves - abstract mathematical data structures over polyhedra and discrete spaces. The homology of cellular cosheaves (and cohomology of cellular sheaves) combines and distills distributed data into the most meaningful algebraic-topological […]

    Spring 2024 GRASP SFI: Karl Pertsch, University of California, Berkeley and Stanford University, “Building Open-Source Generalist Robot Policies”

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    Towne 337

    This will be a hybrid event with in-person attendance in Towne 337 and virtual attendance on Zoom. ABSTRACT Generalist robot policies, trained on large and diverse robot datasets, have the potential to transform how robot learning research is done: in the same way that current models in NLP are almost universally derived from pretrained large […]