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Achieving robust dexterous manipulation in unstructured domestic environments remains a significant challenge in robotics. Even with state-of-the-art robot learning methods, haptic-oblivious control strategies (i.e. those relying only on…
Cellular Vehicle-to-Everything (C-V2X) technology promises to provide ultra-reliable low latency communication (URLLC) framework for connected vehicles. Connected vehicles can help us improve traffic safety, congestion and reduce fatal…
Modern communication devices are often equipped with multiple wireless communication interfaces with diverse characteristics. This enables exploiting a form of multi-connectivity known as interface diversity to provide path diversity with…
We introduce Parametric Density Path Optimization (PDPO), a novel method for computing action-minimizing paths between probability densities. The core idea is to represent the target probability path as the pushforward of a reference…
Operating large-scale anycast networks is challenging because client-to-site mappings often misalign with operator's expectation due to opaque inter-domain routing. We present AnyPro, the first system to unlock the full potential of AS-path…
In Autonomous Driving (AD), real-time perception is a critical component responsible for detecting surrounding objects to ensure safe driving. While researchers have extensively explored the integrity of AD perception due to its safety and…
Advanced traffic navigation systems, which provide routing recommendations to drivers based on real-time congestion information, are nowadays widely adopted by roadway transportation users. Yet, the emerging effects on the traffic dynamics…
Predicting the future behavior of road users is one of the most challenging and important problems in autonomous driving. Applying deep learning to this problem requires fusing heterogeneous world state in the form of rich perception…
Traffic intersections are important scenes that can be seen almost everywhere in the traffic system. Currently, most simulation methods perform well at highways and urban traffic networks. In intersection scenarios, the challenge lies in…
Controlling humanoids in complex physically simulated worlds is a long-standing challenge with numerous applications in gaming, simulation, and visual content creation. In our setup, given a rich and complex 3D scene, the user provides a…
Modern autonomous applications are increasingly utilizing multiple heterogeneous processors (XPUs) to accelerate different stages of algorithm modules. However, existing runtime systems for these applications, such as ROS, can only perform…
We introduce a learning-guided motion planning framework that generates seed trajectories using a diffusion model for trajectory optimization. Given a workspace, our method approximates the configuration space (C-space) obstacles through an…
Public transportation plays a critical role in people's daily life. It has been proven that public transportation is more environmentally sustainable, efficient, and economical than any other forms of travel. However, due to the increasing…
Traffic simulators are important tools for tasks such as urban planning and transportation management. Microscopic simulators allow per-vehicle movement simulation, but require longer simulation time. The simulation overhead is exacerbated…
Personalized PageRank (PPR) is a graph algorithm that evaluates the importance of the surrounding nodes from a source node. Widely used in social network related applications such as recommender systems, PPR requires real-time responses…
We address the problem of planning collision-free paths for multiple agents using optimization methods known as proximal algorithms. Recently this approach was explored in Bento et al. 2013, which demonstrated its ease of parallelization…
Almost all of the current process scheduling algorithms which are used in modern operating systems (OS) have their roots in the classical scheduling paradigms which were developed during the 1970's. But modern computers have different types…
AI has led to significant advancements in computer vision and image processing tasks, enabling a wide range of applications in real-life scenarios, from autonomous vehicles to medical imaging. Many of those applications require efficient…
The aim of this thesis was the design and development of an interactive system enhancing collaborative sensemaking. The system design was based on related work research and preliminary user study. The system is based on multiple…
The computation of resistance distance is pivotal in a wide range of graph analysis applications, including graph clustering, link prediction, and graph neural networks. Despite its foundational importance, efficient algorithms for…