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Building on the base of the existing telescopes of the Event Horizon Telescope (EHT) and ALMA, the next-generation EHT (ngEHT) aspires to deploy ∼10 more stations. The ngEHT targets an angular resolution of ∼15 microarcseconds. This resolution is achieved using Very Long Baseline Interferometry (VLBI) at the shortest radio wavelengths ∼1 mm. The Submillimeter Array (SMA) is both a standalone radio
Robust autonomy stacks require tight integration of perception, motion planning, and control layers, but these layers often inadequately incorporate inherent perception and prediction uncertainties, either ignoring them altogether or making questionable assumptions of Gaussianity. Robots with nonlinear dynamics and complex sensing modalities operating in an uncertain environment demand more carefu
We present property probes, a mechanism for helping a developer interactively explore partial program analysis results in terms of the source program, and as the program is edited. A node locator data structure is introduced that maps between source code spans and program representation nodes, and that helps identify probed nodes in a robust way, after modifications to the source code. We have dev
In this paper, we linear quadratic team decision problems, where a team of agents minimizes a convex quadratic cost function over T time steps subject to possibly distinct linear measurements of the state of nature. We assume that the state of nature is a Gaussian random variable and that the agents do not know the cost function nor the linear functions mapping the state of nature to their measure
We study network SIR (Susceptible - Infected - Recovered) epidemic models in the case of two interacting populations. We analyze the dynamics behavior of the fractions of infected individuals in the two populations. In contrast to the classical scalar SIR epidemic model, where the fraction of infected individuals is known to have an unimodal behavior (either decreasing throughout time or initially
System level synthesis is a promising approach that formulates structured optimal controller synthesis problems as convex problems. This work solves the distributed linear-quadratic regulator problem under communication constraints directly in infinite-dimensional space, without the finite-impulse response relaxation common in related work. Our method can also be used to construct optimal distribu
We present a new, scalable alternative to the structured singular value, which we call v, provide a convex upper bound, study their properties and compare them to l1 robust control. The analysis relies on a novel result on the relationship between robust control of dynamical systems and non-negative constant matrices.
In this paper we investigate simultaneous radial distortion calibration and motion estimation for vehicles travelling parallel to planar surfaces. This is done by estimating the inter-image homography between two poses, as well as the distortion parameter. Radial distortion correction is often performed as a pre-calibration step; however, accurately estimating the distortion profile without specia
We extend the generalized information criteria for high-dimensional penalizedmodels to sparse statistical jump models, a new class of statistically robust and computationally efficient alternatives to hidden Markov models. In a simulation study, we demonstrate that the new generalized information criteria selects the correct hyperparameters with high probability. Finally, providing an empirical ap
We apply the statistical sparse jump model, a recently developed, interpretable and robust regime-switching model, to infer key features that drive the return dynamics of the largest cryptocurrencies. The algorithm jointly performs feature selection, parameter estimation, and state classification. Our large set of candidate features are based on cryptocurrency, sentiment and financial market-based
The MeerKAT radio telescope consists of 64 Gregorian-offset antennas located in the Karoo in the Northern Cape in South Africa. The antenna system consists of multiple subsystems working collaboratively to form a cohesive instrument capable of operating in multiple modes for defined science cases. We focus on the channelizing subsystem (F-engine), the correlation subsystem (X-engine), and the beam
Dynamic resource management is a difficult problem in modern microservice applications. Many proposed methods rely on the availability of an analytical performance model, often based on queueing theory. Such models can always be hand-crafted, but this takes time and requires expert knowledge. Various methods have been proposed that can automatically extract models from logs or tracing data. Howeve
Low-dimensional parametric models are the de-facto standard in computer vision for intrinsic camera calibration. These models explicitly describe the mapping between incoming viewing rays and image pixels. In this paper, we explore an alternative approach which implicitly models the lens distortion. The main idea is to replace the parametric model with a regularization term that ensures the latent
In this thesis, we focus on the problem of estimating receiver and sender node positions given some form of distance measurements between them. This kind of localization problem has several applications, e.g., global and indoor positioning, sensor network calibration, molecular conformations, data visualization, graph embedding, and robot kinematics. More concretely, this thesis makes contribution
Cloud computing has quickly grown to become an essential component in many modern-day software applications. It allows consumers, such as a provider of some web service, to quickly and on demand obtain the necessary computational resources to run their applications. It is desirable for these service providers to keep the running cost of their cloud application low while adhering to various perform
Motivated by a need to characterize transient behaviors in large network systems in terms of relevant signal norms and worst-case input scenarios, we propose a novel approach based on existing theory for matrix pseudospectra. We extend pseudospectral theorems, pertaining to matrix exponentials, to an input-output setting, where matrix exponentials are pre- and post-multiplied by input and output m
This essay takes those exhibits in RÊVE (Romantic Europe: The Virtual Exhibition) that are connected to “air” as points of departure for a survey of the renewed interest in air in Romantic-period cultural texts from across Europe. Scholarly interest in Romantic air has burgeoned of late but has often tended to prioritise metaphorical senses of the term or cognate terms such as atmosphere. This ess
We investigate the problem of risk averse robot path planning using the deep reinforcement learning and distributionally robust optimization perspectives. Our problem formulation involves modelling the robot as a stochastic linear dynamical system, assuming that a collection of process noise samples is available. We cast the risk averse motion planning problem as a Markov decision process and prop
