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ESE Ph.D. Thesis Defense: “Graph Neural Networks for Communication in Multi-Agent Systems”

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

Communication networks support a wide range of applications in multi-agent systems by solving core problems such as routing, scheduling, and resource allocation. In this thesis, we focus on data-driven routing and scheduling strategies using local information subject to constraints using Graph Neural Networks (GNNs). First, we study information routing in communication networks with constant channel […]

MEAM Master’s Thesis Defense: “Learning a Vision-Based Footstep Planner for Hierarchical Walking Control on Unstructured Terrain”

David Rittenhouse Laboratory Building, Room 4C4 209 S. 33rd Street, Philadelphia, PA, United States

Bipedal robots demonstrate high potential in navigating challenging terrains through dynamic ground contact. However, current frameworks often depend solely on proprioception or use manually designed visual processing pipelines, which are fragile in real-world settings and complicate real-time footstep planning in unstructured environments. To overcome this problem, this work proposes a vision-based hierarchical control framework that […]

MEAM Master’s Thesis Defense: “A Computational Model of Caenorhabditis elegans Locomotion”

Towne 319 220 S. 33rd Street, Philadelphia, United States

Since discovered in 1897, the nematode Caenorhabditis elegans has surfaced as an excellent model organism for medical and genetic research. The worm propels itself through viscous-dominated creeping flows via undulatory motion. Moreover, experiments have revealed that the netamode’s swimming gait alters as a function of fluid viscosity. In the current research, we proposed a new […]

ESE Ph.D. Thesis Defense: “Multiferroic Resonators for Wireless Power Transfer and Magnetic Field Sensing in Biomedical Systems”

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

Micro-electromechanical systems (MEMS) composed of magnetostrictive and piezoelectric materials can translate information between the electrical and magnetic domains while exploiting mechanical resonance enhancement. Multiferroic MEMS devices such as these can be designed to perform magnetic field sensing and wireless power transfer (WPT) while maintaining device sizes on the order of 0.125 mm 2 . This […]

MEAM Ph.D. Thesis Defense: “Real-Time Perception and Mixed-Integer Footstep Control for Underactuated Bipedal Walking on Rough Terrain”

Towne 319 220 S. 33rd Street, Philadelphia, United States

The promise of bipedal robots is to go where people go, serving as surrogates for human labor in dangerous, unstructured environments. For the most part, this promise remains unrealized. The primary challenge for controlling bipedal locomotion is underactuation. Standing on a single leg limits control authority, requiring appropriate foot placement to generate or absorb momentum […]

CBE Doctoral Dissertation Defense: “Bridging Transcription and Signaling to Study c-MYC Function and Regulation in Cancer Cells” (Reshma Kalyan Sundaram)

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

Abstract: The transcription factor c-MYC (MYC) is a master regulator of gene expression and is frequently deregulated in human cancers. Despite the prevalent role of MYC in cancers, no MYC inhibitors are currently available for clinical use. In this work, we investigated the molecular mechanisms underlying MYC’s transcriptional function and deregulation using an integrated approach […]

CBE Doctoral Dissertation Defense: “Leveraging confinement and surface effects to control polymer phase behavior and transport phenomena in polymer-infiltrated nanoparticle films” (Trevor Devine)

Vagelos Institute for Energy Science and Technology, Room 121 231 S 34th Street, Philadelphia, PA, United States

Abstract: Highly loaded, polymer-infiltrated nanoparticle films (PINFs) enable the synergistic combination of polymers with the functionality of nanoscale fillers. Extensive studies have found that their behavior deviates markedly from bulk polymers due to extreme confinement and high interfacial area within the interstitial pore network. However, incorporating polymer blends in these PINFs (blend-PINFs) is unexplored. Confinement […]

MSE Ph.D. Thesis: “Metasurfaces For Environmental Refractive Index Sensing: Design, Fabrication And Interrogation”

Towne 327 the Active Learning Classroom

Metasurfaces are artificial materials composed of sub-wavelength building blocks whose size, shape, periodicity and composition are tailored to engineer their optical response and achieve arbitrary control of their interactions with light. Their phase discontinuities or resonances are critically dependent upon the local dielectric or refractive index environment, thus making metasurfaces excellent candidates as refractive index […]

ESE Ph.D. Thesis Defense: “Tunable Dielectric Nanocrystal Metasurfaces for Colorimetric Sensing”

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

Optical metasurfaces enable strong light–matter interactions, making them ideal platforms for high–figure-of-merit (FOM) sensing. When fabricated from colloidal nanocrystal dispersions, these metasurfaces offer unique advantages in fabrication flexibility, reconfigurability, and cost-effectiveness. However, conventional fabrication approaches often rely on toxic material systems. In this thesis, we enhance the FOM of titanium dioxide (TiO₂)-based dielectric metasurfaces by […]

ESE Ph.D. Thesis Defense: “Statistical Limits and Efficient Algorithms for Learning-Enabled Control”

Amy Gutmann Hall, Room 414 3333 Chestnut Street, Philadelphia, United States

As the adoption of large-scale learning for control continues to grow, developing sample-efficient algorithms has become critical. Yet, even in simple settings, algorithms achieving optimal sample complexity for specific problem instances often remain unknown. Motivated by this limitation, we discuss recent progress toward understanding sample-efficient methods in learning-enabled control. We first examine the statistical limits […]