papers

Publications (8)

cs.LG2026

Metropolis-Scale Resilient and Trustworthy Traffic Flow Inference Using Multi-Source Data

Qishen Zhou, Yifan Zhang, Michail A. Makridis +3

Inferring network-wide traffic states from sparse observations with high accuracy and trustworthy uncertainty quantification is essential for intelligent transportation systems, ye…

eess.SY2023

A Four-stage Heuristic Algorithm for Solving On-demand Meal Delivery Routing Problem

Lejun Zhou, Anke Ye, Simon Hu

Meal delivery services provided by platforms with integrated delivery systems are becoming increasingly popular. This paper adopts a rolling horizon approach to solve the meal deli…

cs.LG2026

Network-wide Freeway Traffic Estimation Using Sparse Sensor Data: A Dirichlet Graph Auto-Encoder Approach

Qishen Zhou, Yifan Zhang, Michail A. Makridis +3

Network-wide Traffic State Estimation (TSE), which aims to infer a complete image of network traffic states with sparsely deployed sensors, plays a vital role in intelligent transp…

cs.AI2026

ORThought: Benchmarking and Automating Logistics Optimization Modeling

Beinuo Yang, Qishen Zhou, Junyi Li +3

Optimization modeling stands as the engine of scientific decision-making in logistics and transportation, yet its adoption is hindered by a steep expertise threshold and the latenc…

cs.LG2026

MoGERNN: An Inductive Traffic Predictor for Unobserved Locations

Qishen Zhou, Yifan Zhang, Michail A. Makridis +3

Given a partially observed road network, how can we predict the traffic state of interested unobserved locations? Traffic prediction is crucial for advanced traffic management syst…

eess.SY2020

Identifying Critical Fleet Sizes Using a Novel Agent-Based Modelling Framework for Autonomous Ride-Sourcing

Renos Karamanis, He-in Cheong, Simon Hu +2

Ride-sourcing platforms enable an on-demand shared transport service by solving decision problems often related to customer matching, pricing and vehicle routing. These problems ha…