collaborators

6 papers

cs.AI2026

Universal Quantum Transformer

Sungyong Chung, Alireza Talebpour

Classical continuous-space neural networks fundamentally struggle to lock into exact formal rules, whether mathematical, such as modular arithmetic and non-Abelian group algebra, o…

cs.GT2026

Evolution of Lane-Changing Behavior in Mixed Traffic: A Quantum Game Theory Approach

Sungyong Chung, Tina Radvand, Alireza Talebpour

As automated vehicles (AVs) enter mixed traffic, proactively anticipating the evolution of human driving behavior during critical interactions, such as lane changes, is essential.…

eess.SY2026

Data is All You Need: Markov Chain Car-Following (MC-CF) Model

Sungyong Chung, Yanlin Zhang, Nachuan Li +2

Car-following behavior is fundamental to traffic flow theory, yet traditional models often fail to capture the stochasticity of naturalistic driving. This paper introduces a new ca…

cs.MA2025

Characterizing Lane-Changing Behavior in Mixed Traffic

Sungyong Chung, Alireza Talebpour, Samer H. Hamdar

Characterizing and understanding lane-changing behavior in the presence of automated vehicles (AVs) is crucial to ensuring safety and efficiency in mixed traffic. Accordingly, this…

cs.CY2025

PAPPL: Personalized AI-Powered Progressive Learning Platform

Shayan Bafandkar, Sungyong Chung, Homa Khosravian +1

Engineering education has historically been constrained by rigid, standardized frameworks, often neglecting students' diverse learning needs and interests. While significant advanc…

cs.ET2025

Charging While Driving Lanes: A Boon to Electric Vehicle Owners or a Disruption to Traffic Flow

Shayan Bafandkar, Alireza Talebpour

Large-scale adoption of commercial and personal Electric Vehicles (EVs) is expected to significantly affect traffic flow dynamics, emissions, and energy consumption in the transpor…