Committee Members: Sue Ann Bidstrup Allen, Advisor; Raymond Gorte, John Vohs and Mark Allen.
Committee: Sue Ann Bidstrup Allen, Advisor; Raymond Gorte, John Vohs and Mark Allen
This era of the internet of things is poised to experience explosive growth in the number of interconnected smart electronic devices. Machine learning algorithms, such as neural networks, are expected to play an indispensable role in analyzing the data gathered by these devices, and in many cases, will also facilitate informed device responses. However, the […]
Autonomous flight through unknown environments in the presence of obstacles is a challenging problem for micro aerial vehicles (MAVs). A majority of the current state-of-art research focuses on modeling obstacles as opaque objects that can be easily sensed by optical sensors such as cameras or LiDARs. Since obstacles may not always be opaque, particularly in […]
Committee: Robert Riggleman, PhD (co-advisor); Russell Composto, PhD (co-advisor); Ravi Radhakrishan, PhD; and Jeff Meth, PhD
Low temperature synthesis of high quality 2D materials directly on flexible substrates remains a fundamental limitation towards realization of robust, strainable electronics possessing the unique physical properties of atomically thin structures. Here, we describe room temperature synthesis of uniform, stoichiometric amorphous MoS2, WSe2, and other transition metal dichalcogenides and subsequent large area (>5 cm2) photonic […]
A reception on inclusion will be held for new Penn Engineering doctoral students to connect them to their peers and supporting structures within the school. Please join the Dean, Deputy Dean, the Director of the Office of Diversity and Inclusion, faculty and staff leaders including chairs, graduate group chairs and coordinators, and leaders of student groups. […]
Abstract: We aim to establish and experimentally test mathematical models of embryogenesis. While the foundation of this research is based on models of isolated developmental events, the ultimate challenge is to formulate and understand dynamical systems encompassing multiple stages of development and multiple levels of regulation. These range from specific chemical reactions in single cells […]
Compressive Sensing is an acquisition technique which relies on the sparsity of the underlying signals, to enable sampling below the classical Nyquist rate. To do so, the signals must be acquired in an incoherent way with respect to the sparsity basis, which is classically obtained in practice by acquiring the signal through projection on a […]
