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Penn Engineering Class of 2020 Undergraduate and Master’s Graduate Recognition

Dean Vijay Kumar will address the Penn Engineering Class of 2020 undergraduate and master’s graduates and their loved ones. Join us to hear Dean Kumar’s address, view student photos, and watch congratulatory video messages submitted by students’ families and by Penn Engineering faculty and staff. Please visit this webpage to access the link to our […]

Penn Engineering Class of 2020 Doctoral Graduate Recognition

Join us to hear a message from the Dean of Penn Engineering, Dr. Vijay Kumar, and view a virtual roll call of the Class of 2020 doctoral graduates, complete with video messages from our graduates and members of the Penn Engineering faculty. The total run time of this virtual celebration is less than one hour. […]

ESE Ph.D. Thesis Defense


ESE Seminar: “Integrated Optical Phased Arrays: LiDAR, Augmented Reality, and Beyond”

Abstract By enabling optical microsystems with new functionalities, improved system performance, and reduced size, weight, and power, integrated photonics is positioned to enable next-generation optical technologies that facilitate revolutionary advances for numerous fields spanning science and engineering, including computing, sensing, communications, displays, quantum, and biology. An emerging class of integrated photonic systems is integrated optical […]

ESE Seminar: “Joint Wireless Communication and Sensing in Terahertz Spectrum”

Abstract Millimeter-wave and terahertz bands are emerging as the most promising spectrum to meet the data-rate and latency demands of future wireless applications, including virtual reality and autonomous cars. Moreover, large spectral availability and mm-scale wavelength provide the possibility for ubiquitous and high-resolution sensing. My research builds a foundation for joint communication and sensing in […]

ESE Seminar: “Safe Real-World Autonomy in Uncertain and Unstructured Environments”

Abstract In this talk I will present my current and future work towards enabling safe real-world autonomy. My core focus is to enable efficient and safe decision-making in complex autonomous systems, while reasoning about uncertainty in real-world environments, including those involving human interactions. First I will discuss safety for complex systems in simple environments. Traditional […]

ESE Seminar: “Engineering Quantum Processors in Silicon”

Abstract Across the globe, physicists in academia and industry alike are competing to be the first to build a scalable universal quantum computer. Amongst the multitudes of quantum computing architectures, solid-state quantum processors based on spins in silicon are emerging as a strong contender. Silicon is an ideal material to host spin qubits: it supports […]

ESE Seminar: “Quantum information processing with superconducting circuits: Purcell effect and the measurement problem”

Abstract With recent advances in state preparation, gate, and measurement operations, superconducting circuit architectures are now leading candidates for quantum information processing. As micro-fabricated circuits are scaled up towards a practical quantum processor, strict requirements on the fidelity of operations required for quantum computation are imposed. For theorists, this mandates the development of accurate models […]

ESE Seminar: “Nanophotonics: A High Bandwidth Optical Neural Interface”

Abstract Light is a powerful tool for interrogating and manipulating biological systems, enabling targeted stimulation, sensing, and imaging. Optical methods such as optogenetics have transformed the study of neural circuits by making it possible to control neural activity using light. However, there remains a critical demand in research and medicine for miniaturized high resolution optical […]

ESE Seminar: “Adapting black-box machine learning methods for causal inference”

Abstract: I’ll discuss the use of observational data to estimate the causal effect of a treatment on an outcome. This task is complicated by the presence of ‘confounders’ that influence both treatment and outcome, inducing observed associations that are not causal. Causal estimation is achieved by adjusting for this confounding by using observed covariate information. I’ll […]

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