225 citations · 547 across the 29 of their papers we have counts for
32 papers
Jacobi-Anger Method for Deterministic Initialization in Implicit Neural Representation
Mohammed Alsakabi, Kejia Hu, John M. Dolan +1
Existing implicit neural representation (INR) approaches suffer from stochastic initialization that does not guarantee consistent or high-quality performance across runs, with vari…
Reproducing and Extending RaDelft 4D Radar with Camera-Assisted Labels
Kejia Hu, Mohammed Alsakabi, John M. Dolan +1
Recent advances in 4D radar highlight its potential for robust environment perception under adverse conditions, yet progress in radar semantic segmentation remains constrained by t…
Quantifying Distribution Shift in Traffic Signal Control with Histogram-Based GEH Distance
Federico Taschin, Ozan K. Tonguz
Traffic signal control algorithms are vulnerable to distribution shift, where performance degrades under traffic conditions that differ from those seen during design or training. T…
CFL: On the Use of Characteristic Function Loss for Domain Alignment in Machine Learning
Abdullah Almansour, Ozan Tonguz
Machine Learning (ML) models are extensively used in various applications due to their significant advantages over traditional learning methods. However, the developed ML models of…
Edge-Based Speech Transcription and Synthesis for Kinyarwanda and Swahili Languages
Pacome Simon Mbonimpa, Diane Tuyizere, Azizuddin Ahmed Biyabani +1
This paper presents a novel framework for speech transcription and synthesis, leveraging edge-cloud parallelism to enhance processing speed and accessibility for Kinyarwanda and Sw…
Using Kolmogorov-Smirnov Distance for Measuring Distribution Shift in Machine Learning
Ozan K. Tonguz, Federico Taschin
One of the major problems in Machine Learning (ML) and Artificial Intelligence (AI) is the fact that the probability distribution of the test data in the real world could deviate s…
The Impact of 2D Segmentation Backbones on Point Cloud Predictions Using 4D Radar
William Muckelroy, Mohammed Alsakabi, John Dolan +1
LiDAR's dense, sharp point cloud (PC) representations of the surrounding environment enable accurate perception and significantly improve road safety by offering greater scene awar…
The Distribution Shift Problem in Transportation Networks using Reinforcement Learning and AI
Federico Taschin, Abderrahmane Lazaraq, Ozan K. Tonguz +1
The use of Machine Learning (ML) and Artificial Intelligence (AI) in smart transportation networks has increased significantly in the last few years. Among these ML and AI approach…
Quantum deep reinforcement learning for humanoid robot navigation task
Romerik Lokossou, Birhanu Shimelis Girma, Ozan K. Tonguz +1
Classical reinforcement learning (RL) methods often struggle in complex, high-dimensional environments because of their extensive parameter requirements and challenges posed by sto…
FM-SIREN & FM-FINER: Implicit Neural Representation Using Nyquist-based Orthogonality
Mohammed Alsakabi, Wael Mobeirek, John M. Dolan +1
Existing periodic activation-based implicit neural representation (INR) networks, such as SIREN and FINER, suffer from hidden feature redundancy, where neurons within a layer captu…
Toward a Low-Cost Perception System in Autonomous Vehicles: A Spectrum Learning Approach
Mohammed Alsakabi, Aidan Erickson, John M. Dolan +1
We present a cost-effective new approach for generating denser depth maps for Autonomous Driving (AD) and Autonomous Vehicles (AVs) by integrating the images obtained from deep neu…
On the Use of Quantum Entanglement in Secure Communications: A Survey
Keith Shannon, Elias Towe, Ozan K. Tonguz
Quantum computing and quantum communications are exciting new frontiers in computing and communications. Indeed, the massive investments made by the governments of the US, China, a…
Using AI for Mitigating the Impact of Network Delay in Cloud-based Intelligent Traffic Signal Control
Rusheng Zhang, Xinze Zhou, Ozan K. Tonguz
The recent advancements in cloud services, Internet of Things (IoT) and Cellular networks have made cloud computing an attractive option for intelligent traffic signal control (ITS…
Leader selection in Vehicular Ad-hoc Networks: a Proactive Approach
Rusheng Zhang, Baptiste Jacquemot, Kagan Bakirci +6
With the rapid advancement in vehicle-to-vehicle (V2V) communications, there are growing interests in related fields to leverage V2V communications for different applications. A ro…
Partially Detected Intelligent Traffic Signal Control: Environmental Adaptation
Rusheng Zhang, Romain Leteurtre, Benjamin Striner +3
Partially Detected Intelligent Traffic Signal Control (PD-ITSC) systems that can optimize traffic signals based on limited detected information could be a cost-efficient solution f…
Using Ultra-Wideband Technology in Vehicles for Infrastructure-free Localization
Rusheng Zhang, Lin Song, Adhishree Jaiprakash +5
In this paper, we investigate using Ultra-Wideband (UWB) technology in vehicles for localization as well as other possible infrastructure-free applications. To that end, we first i…
Virtual Traffic Lights: System Design and Implementation
Rusheng Zhang, Frank Schmutz, Kyle Gerard +6
Traffic congestion is a daunting problem that is affecting the daily lives of billions of people across the world. Recently, a promising new traffic control scheme known as Virtual…
Using Reinforcement Learning with Partial Vehicle Detection for Intelligent Traffic Signal Control
Rusheng Zhang, Akihiro Ishikawa, Wenli Wang +2
Intelligent Transportation Systems (ITS) have attracted the attention of researchers and the general public alike as a means to alleviate traffic congestion. Recently, the maturity…
Impact of Communication Delay on Asynchronous Distributed Optimal Power Flow Using ADMM
Junyao Guo, Gabriela Hug, Ozan Tonguz
Distributed optimization has attracted lots of attention in the operation of power systems in recent years, where a large area is decomposed into smaller control regions each solvi…
Bluetooth 5: a concrete step forward towards the IoT
Mario Collotta, Giovanni Pau, Timothy Talty +1
Six years after the adoption of the standard 4.0, the Bluetooth Special Interest Group (SIG), a non-profit association that deals with the study and the development of technology s…
Asynchronous ADMM for Distributed Non-Convex Optimization in Power Systems
Junyao Guo, Gabriela Hug, Ozan Tonguz
Large scale, non-convex optimization problems arising in many complex networks such as the power system call for efficient and scalable distributed optimization algorithms. Existin…
Smarter Cities with Parked Cars as Roadside Units
Andre B. Reis, Susana Sargento, Ozan K. Tonguz
Real-time monitoring of traffic density, road congestion, public transportation, and parking availability are key to realizing the vision of a smarter city and, with the advent of…
Parked Cars are Excellent Roadside Units
Andre B. Reis, Susana Sargento, Ozan K. Tonguz
A comprehensive implementation of the envisioned traffic safety and efficiency applications of the IEEE 802.11p and WAVE standards assume the premise of the use of DSRC technology…
Impact of Power System Partitioning on the Efficiency of Distributed Multi-Step Optimization
Junyao Guo, Gabriela Hug, Ozan Tonguz
Recent studies have shown that multi-step optimization based on Model Predictive Control (MPC) can effectively coordinate the increasing number of distributed renewable energy and…