58+ open-access research outputs.
Three-dimensional (3D) ultrasound promises various medical applications for abdominal, obstetrics, and breast imaging. However, ultrasound matrix arrays have extremely high element counts limiting the…
Robotic deep anterior lamellar keratoplasty (DALK) requires accurate real time depth feedback to approach Descemet's membrane (DM) without perforation. M-mode intraoperative optical coherence tomograp…
The rapid development of technology has led to an increase in the number of devices that rely on position, velocity, and time (PVT) information to perform their functions. As such, the Global Navigati…
Despite improvements in automatic speaker verification (ASV), vulnerability against spoofing attacks remains a major concern. In this study, we investigate the integration of ASV and countermeasure (C…
Achieving optimal synchronization accuracy between two White Rabbit devices hinges on the proper selection of transceivers, which act as electro-optical converters connecting WR devices to the optical…
We present an adaptive Finite State Projection (FSP) method for efficiently solving the Chemical Master Equation (CME) with rigorous error control. Our approach integrates time-stepping with dynamic s…
Power Doppler ultrasound is in widespread clinical use for non-invasive vascular imaging but the most common current method - Delay and Sum (DAS) beamforming - suffers from limited resolution and high…
Deep Anterior Lamellar Keratoplasty (DALK) is a partial-thickness corneal transplant procedure used to treat corneal stromal diseases. A crucial step in this procedure is the precise separation of the…
Early detection of neurocognitive disorders (NCDs) is crucial for timely intervention and disease management. Given that language impairments manifest early in NCD progression, visual-stimulated narra…
Autonomous surgical robots have demonstrated significant potential to standardize surgical outcomes, driving innovations that enhance safety and consistency regardless of individual surgeon experience…
Trajectory optimization is an essential tool for generating efficient, dynamically consistent gaits in legged locomotion. This paper explores the indirect method of trajectory optimization, emphasizin…
Quantifying axon and myelin properties (e.g., axon diameter, myelin thickness, g-ratio) in histology images can provide useful information about microstructural changes caused by neurodegenerative dis…
Reinforcement learning (RL) has progressed substantially over the past decade, with much of this progress being driven by benchmarks. Many benchmarks are focused on video or board games, and a large n…
This study presents a novel methodology incorporating safety constraints into a robotic simulation during the training of deep reinforcement learning (DRL). The framework integrates specific parts of …
This study explores how wearable accelerometers, small devices that measure acceleration, can help monitor the activity of growing rabbits. We equipped 16 rabbits with these devices and filmed them fo…
Risk assessment of a robot in controlled environments, such as laboratories and proving grounds, is a common means to assess, certify, validate, verify, and characterize the robots' safety performance…
This paper introduces RABBIT, a novel robot-assisted bed bathing system designed to address the growing need for assistive technologies in personal hygiene tasks. It combines multimodal perception and…
In an environment with certain locations of higher priority, it is required to patrol these locations as frequently as possible due to their importance. However, the Non-Priority locations are often n…
This work presents a hierarchical framework for bipedal locomotion that combines a Reinforcement Learning (RL)-based high-level (HL) planner policy for the online generation of task space commands wit…
Data collected at Hurricane Ian (2022) quantifies the demands that small uncrewed aerial systems (UAS), or drones, place on the network communication infrastructure and identifies gaps in the field. D…
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