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    • MSE Seminar: “Color From Colorless Materials: Harnessing Multi-reflection Interference in Microstructures”

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

    Many of the colors found in nature, such as those of iridescent, color-shifting organisms like beetles, butterflies, and birds, are structural colors. Structural coloration is often generated by optical interference occurring within nanoscale periodic structures, like diffraction gratings, photonic crystals, or thin films. In these cases, the periodicity of the structure is similar to the […]

    ESE Fall Seminar – “Deep Latent Variable Models for Compression and Natural Science”

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

    Latent variable models have been an integral part of probabilistic machine learning, ranging from simple mixture models to variational autoencoders to powerful diffusion probabilistic models at the center of recent media attention. Perhaps less well-appreciated is the intimate connection between latent variable models and data compression, and the potential of these models for advancing natural […]

    BE Seminar: “Synthetic reconstitution of complex cellular behavior” (Ahmad Khalil, Boston University)

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    216 Moore Building

    Cells use genetically-encoded molecular circuits to execute diverse biological functions. We are developing novel tools of synthetic biology that allow us to construct regulatory circuitry inside living cells that recapitulate complex functions like those seen in nature. In this talk, I will describe how we use this approach to achieve three objectives. First, I will […]

    CIS Seminar: “Neurosymbolic AI for Safety-Critical Agile Control”

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

    This talk overviews research at Caltech on designing hybrid or neurosymbolic AI systems that blend learning with symbolic structure, in order to achieve both the flexibility of the former and the formal interpretability and generalization power of the latter.  By having systems that are formally interpretable, one can employ a wide range of formal analysis […]

    Fall 2024 GRASP on Robotics: Antonio Loquercio, University of Pennsylvania, “Simulation: What made us intelligent will make our robots intelligent”

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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 and Chen and virtual attendance on Zoom. ABSTRACT Simulation-to-reality transfer is an emerging approach that enables robots to develop skills in simulated environments before applying them in the real world. This method has catalyzed numerous advancements in robotic learning, from locomotion to agile flight. […]

    PICS Colloquium: Mean flow and turbulence in unsteady urban canopy flows

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

    Advancing the current understanding and capability to predict atmospheric flow and related transport in urban areas is critical for many applications, including air quality modeling, urban climate, pedestrian comfort and structural resilience. Turbulence in these environments is rarely in equilibrium with the underlying surface and is typically characterized by strong departures from statistical stationarity. For […]

    MEAM Seminar: “Propulsive Advantages of Coordinating Multiple Jets by Colonial Marine Organisms”

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

    Salps and siphonophores are widespread marine animals that occur in centimeters to meters-long colonial chains and employ multiple, pulsed swimming jets. We use a combination of approaches including in situ and lab experiments, flow visualizations and custom high-speed camera systems to understand the morphology, kinematics and fluid mechanics that underpin efficient movement in these colonial […]

    ESE Fall Seminar – “Learning-NUM: Utility Maximization in Stochastic Queueing Networks”

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

    We consider the problem of network utility maximization (NUM) and propose a new Learning-NUM framework,  where the users’ utility functions are unknown apriori and the utility function values can be observed only after the corresponding traffic is delivered to the destination.   We start by considering linear utility functions and propose a priority-based network control policy, […]

    CIS Seminar: “Optimal Oblivious Reconfigurable Networks”

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

    As Moore's Law slows down, packet switch capabilities are falling behind datacenter demands. Recent hardware advances have enabled the new switching technology of nanosecond-scale rapid circuit switches. Combined with novel network designs, these have the potential to fully replace packet switches. This talk presents the Oblivious Reconfigurable Network (ORN) design paradigm which is ideally suited […]

    ESE Guest Seminar – “Safe Offline RL for Constrained Markov Decision Process: Theory and Practice”

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

    Many constrained sequential decision-making processes such as safe AV navigation, wireless network control, caching, cloud computing, etc., can be cast as Constrained Markov Decision Processes (CMDP). Reinforcement Learning (RL) algorithms have been used to learn optimal policies for unknown unconstrained MDP. Extending these RL algorithms to unknown CMDP, brings the additional challenge of not only […]

    ASSET Seminar: “Some Displaced Vignettes on Generalized Notions of Equivariance”

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

    Abstract: The explicit incorporation of task-specific inductive biases through symmetry has emerged as a crucial design precept in the development of high-performance machine learning models. Symmetry-aware neural networks, such as group equivariant networks, have achieved notable success in areas like protein and drug design, where capturing task-specific symmetries improves generalization. Recent efforts have focused on […]

    MEAM Ph.D. Thesis Defense: “Semantics-Driven Active Perception and Navigation with Aerial Robots”

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    Room 313, Singh Center for Nanotechnology 3205 Walnut Street, Philadelphia, PA, United States

    Autonomous aerial robots today are capable of safely navigating through cluttered, GPS-denied environments while constructing an accurate map that captures geometric features such as points, lines, and planes. Such maps are crucial for low-level planning and obstacle avoidance. However, beyond offering details on the density, layout, and dimensions of the environment, these maps provide limited […]