activity
20192022
most citedBridge Modal Identification using Acceleration Measurements within Moving Vehicles

130 citations · 143 across the 5 of their papers we have counts for

collaborators

9 papers

physics.app-ph20223 cited

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…

eess.SY20214 cited

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…

cs.LG2020

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…

cs.LG2020

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…

eess.SP2020

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…

stat.ML20201 cited

Finite Difference Neural Networks: Fast Prediction of Partial Differential Equations

Zheng Shi, Nur Sila Gulgec, Albert S. Berahas +2

Discovering the underlying behavior of complex systems is an important topic in many science and engineering disciplines. In this paper, we propose a novel neural network framework…