91 citations · 120 across the 8 of their papers we have counts for
8 papers
Identifying Damage-Sensitive Spatial Vibration Characteristics of Bridges from Widespread Smartphone Data
Liam Cronin, Soheil Sadeghi Eshkevari, Thomas J. Matarazzo +5
The knowledge gap in the expected and actual conditions of bridges has created worldwide deficits in infrastructure service and funding challenges. Despite rapid advances over the…
Golfer: Trajectory Prediction with Masked Goal Conditioning MnM Network
Xiaocheng Tang, Soheil Sadeghi Eshkevari, Haoyu Chen +3
Transformers have enabled breakthroughs in NLP and computer vision, and have recently began to show promising performance in trajectory prediction for Autonomous Vehicle (AV). How…
Reinforcement Learning in the Wild: Scalable RL Dispatching Algorithm Deployed in Ridehailing Marketplace
Soheil Sadeghi Eshkevari, Xiaocheng Tang, Zhiwei Qin +4
In this study, a real-time dispatching algorithm based on reinforcement learning is proposed and for the first time, is deployed in large scale. Current dispatching methods in ride…
RL-Controller: a reinforcement learning framework for active structural control
Soheila Sadeghi Eshkevari, Soheil Sadeghi Eshkevari, Debarshi Sen +1
To maintain structural integrity and functionality during the designed life cycle of a structure, engineers are expected to accommodate for natural hazards as well as operational l…
Transfer Learning for Input Estimation of Vehicle Systems
Liam M. Cronin, Soheil Sadeghi Eshkevari, Debarshi Sen +1
This study proposes a learning-based method with domain adaptability for input estimation of vehicle suspension systems. In a crowdsensing setting for bridge health monitoring, veh…
Crowdsourcing Bridge Vital Signs with Smartphone Vehicle Trips
Thomas J. Matarazzo, Dániel Kondor, Sebastiano Milardo +5
A key challenge in monitoring and managing the structural health of bridges is the high-cost associated with specialized sensor networks. In the past decade, researchers predicted…
DynNet: Physics-based neural architecture design for linear and nonlinear structural response modeling and prediction
Soheil Sadeghi Eshkevari, Martin Takáč, Shamim N. Pakzad +1
Data-driven models for predicting dynamic responses of linear and nonlinear systems are of great importance due to their wide application from probabilistic analysis to inverse pro…
Bridge Structural Health Monitoring using Asynchronous Mobile Sensing Data
Soheil Sadeghi Eshkevari, Liam Cronin, Shamim N. Pakzad +1
This study presents a flexible approach for bridge modal identification using smartphone data collected by a large pool of passing vehicles. With each trip of a mobile sensor, the…