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    • CIS Seminar: “Tackling climate change with machine learning”

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    Zoom - Email CIS for link cherylh@cis.upenn.edu

    Machine learning can be a powerful tool in helping society reduce greenhouse gas emissions and adapt to a changing climate. In this talk, we will explore opportunities and challenges in AI-for-climate, from optimizing electrical grids to monitoring crop yield, and how these impactful problems can also drive methodological innovations in machine learning.

    • Fall 2021 GRASP SFI: Lucas Manuelli, NVIDIA, “Robot Manipulation with Learned Representations”

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    Levine 307 3330 Walnut Street, Philadelphia, PA, United States

    We would like to have robots which can perform useful manipulation tasks in real-world environments. This requires robots that can perceive the world with both precision and semantic understanding, methods for communicating desired tasks to these systems, and closed loop visual feedback controllers for robustly executing manipulation tasks. This is hard to achieve with previous […]

    CBE Seminar: “From Molecular Simplicity to Supramolecular Complexity: Low Symmetry Packings of Ionic Spherical Micelles”

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

    Abstract A delicate balance of noncovalent interactions drives hydrated molecular amphiphiles to self-assemble into lyotropic liquid crystals (LLCs) of varied topologies, the exquisite nanodomain structures of which suggest applications as separations membranes, mesoporous materials synthesis templates, and therapeutic delivery vehicles. Based on hard sphere colloidal crystals, spherical micelles are intuitively expected to form high symmetry […]

    MSE Seminar: “Data-driven materials design in the quantum regime: motif-centric learning framework and local-symmetry-guided material discovery”

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

    Materials design in the quantum regime call for the integration of multi-tier materials information that go beyond atomic structures. Especially, many quantum behaviors are greatly controlled by local symmetries and local bonding environments. In this talk, motivated by Pauling’s rules, Dr. Yan will show that local bonding environments (motifs) can be incorporated in a graph-based […]

    Fall 2021 GRASP Seminar: Gregory S. Chirikjian, “Robot Imagination: Affordance-Based Reasoning about Unknown Objects”

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    Levine 307 3330 Walnut Street, Philadelphia, PA, United States

    Today’s robots are very brittle in their intelligence. This follows from a legacy of industrial robotics where robots pick and place known parts repetitively. For humanoid robots to function as servants in the home and in hospitals they will need to demonstrate higher intelligence, and must be able to function in ways that go beyond […]

    CIs Seminar: “Modeling cancer progression with neural networks”

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

    The exponential growth of biological datasets in recent years has increased the dependency of cancer research on AI and computational analysis. Cancer evolves through the accumulation of genetic events over time, which are represented through different types of data. Integration of machine learning methods with temporal modeling and genomic methods has the potential to improve our […]

    GRASP on Robotics: “Toward Object Manipulation Without Explicit Models”

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

    *This will be a HYBRID Event with in-person attendance in Wu & Chen Auditorium and Virtual attendance via Zoom Webinar here.  The prevalent approach to object manipulation is based on the availability of explicit 3D object models. By estimating the pose of such object models in a scene, a robot can readily reason about how […]

    PICS Colloquium: “Computational and Experimental Modeling of Membrane Distillation”

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    PICS Conference Room 534 - A Wing , 5th Floor 3401 Walnut Street, Philadelphia, PA, United States

    Abstract: Computational fluid dynamics simulations and experiments were conducted to study the performance of distillation membrane process for water treatment and desalination applications. Polarizations and fouling/scaling in a direct contact membrane distillation module were examined. Laminar and turbulent flow regimes in the feed and permeate channels were considered. The hydrophobic membrane separates feed and permeate […]

    Keeping Up the Good Work: Honoring 40 Years of Excellence in Diversity

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    Heilmeier Hall (Room 100), Towne Building 220 South 33rd Street, Philadelphia, PA, United States

    This year marks the 40th anniversary of Penn Engineering's diversity efforts and we invite you to join us on Friday, December 3, at 3:00 p.m. EST to celebrate Penn Engineering’s new Office of Diversity, Equity, and Inclusion (ODEI), formerly known as the Office of Minority Programs. We plan to meet in Heilmeier Hall (Towne 100) […]

    MEAM Seminar: “Continuum Mechanics of Non-equilibrium Phenomena: A Journey Through Space and Time Scales”

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

    The fascinating diversity of material behavior at the macroscopic scale, including plasticity, phase transformations, viscoelasticity or diffusion, can only emerge from the underlying atomistic or particle behavior. Yet, the direct connection between these two scales for non-equilibrium phenomena remains an extremely challenging quest from both a theoretical and computational perspective. This knowledge gap currently hinders […]

    ESE Fall Colloquium Seminar – “Alpha-loss: A Tunable Class of Loss Functions for Robust Learning”

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    Zoom - Meeting ID 916 0331 6605

    Machine learning has dramatically enhanced the role of automated decision making across a variety of domains. There are three ingredients that are at the heart of designing of sound ML algorithms: data, learning architectures, and loss functions. In this talk, we focus on loss functions and the role of information theory in understanding the choice […]

    CIS Seminar: “Synthetic Data: Anonymisation Groundhog Day”

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    Zoom - Email CIS for link cherylh@cis.upenn.edu

    Synthetic data has been advertised as a silver-bullet solution to privacy-preserving data publishing that addresses the shortcomings of traditional anonymisation techniques. The promise is that synthetic data drawn from generative models preserves the statistical properties of the original dataset but, at the same time, provides perfect protection against privacy attacks. In this work, we present the first […]