Qingkai Kong

Qingkai Kong

Northern Illinois University

H-index: 31

North America-United States

About Qingkai Kong

Qingkai Kong, With an exceptional h-index of 31 and a recent h-index of 16 (since 2020), a distinguished researcher at Northern Illinois University, specializes in the field of Ordinary differential equations.

His recent articles reflect a diverse array of research interests and contributions to the field:

Evaluating Physics Informed Neural Network Performance for Seismic Discrimination Between Earthquakes and Explosions

Multi-fidelity Fourier neural operator for fast modeling of large-scale geological carbon storage

Crowdsourcing felt reports using the MyShake smartphone app

Advanced Methods for Flexible, Fast, and High-Fidelity Fluid Flow Predictions

Oscillation criteria for advanced half-linear differential equations of second order

Predicting wind-driven spatial deposition through simulated color images using deep autoencoders

Physics-Informed Neural Network with P/S ratios in Explosion-Earthquake Discrimination

Applications of smartphone seismic data for rapid structural health assessment

Qingkai Kong Information

University

Position

___

Citations(all)

4539

Citations(since 2020)

1015

Cited By

4445

hIndex(all)

31

hIndex(since 2020)

16

i10Index(all)

84

i10Index(since 2020)

29

Email

University Profile Page

Google Scholar

Qingkai Kong Skills & Research Interests

Ordinary differential equations

Top articles of Qingkai Kong

Evaluating Physics Informed Neural Network Performance for Seismic Discrimination Between Earthquakes and Explosions

arXiv preprint arXiv:2403.04952

2024/3/7

Qingkai Kong
Qingkai Kong

H-Index: 19

Brandon Schmandt
Brandon Schmandt

H-Index: 29

Multi-fidelity Fourier neural operator for fast modeling of large-scale geological carbon storage

Journal of Hydrology

2024/2/1

Qingkai Kong
Qingkai Kong

H-Index: 19

Crowdsourcing felt reports using the MyShake smartphone app

Seismological Research Letters

2023/9/1

Advanced Methods for Flexible, Fast, and High-Fidelity Fluid Flow Predictions

2023/8/28

Oscillation criteria for advanced half-linear differential equations of second order

Mathematics

2023/3/13

Qingkai Kong
Qingkai Kong

H-Index: 19

Predicting wind-driven spatial deposition through simulated color images using deep autoencoders

Scientific Reports

2023/1/25

Qingkai Kong
Qingkai Kong

H-Index: 19

Physics-Informed Neural Network with P/S ratios in Explosion-Earthquake Discrimination

AGU Fall Meeting Abstracts

2022/12

Qingkai Kong
Qingkai Kong

H-Index: 19

Applications of smartphone seismic data for rapid structural health assessment

Authorea Preprints

2022/11/25

Qingkai Kong
Qingkai Kong

H-Index: 19

Richard Allen
Richard Allen

H-Index: 62

New Hille Type and Ohriska Type Criteria for Nonlinear Third-Order Dynamic Equations

Mathematics

2022/11/6

Qingkai Kong
Qingkai Kong

H-Index: 19

Combining deep learning with physics based features in explosion‐earthquake discrimination

Geophysical Research Letters

2022

Qingkai Kong
Qingkai Kong

H-Index: 19

Brandon Schmandt
Brandon Schmandt

H-Index: 29

Detecting damaged buildings using real-time crowdsourced images and transfer learning

Scientific reports

2022/5/27

Preliminary Transfer Learning Results on Israel Data

2022/3/31

Qingkai Kong
Qingkai Kong

H-Index: 19

Learning Physics Through Images: An Application To Wind-Driven Spatial Patterns

2022/3/17

Qingkai Kong
Qingkai Kong

H-Index: 19

Understanding the Seismic Ground Motion Spatial Variability Using Network Analysis Community Detection

2022/3/14

Qingkai Kong
Qingkai Kong

H-Index: 19

Cross-platform analysis of public responses to the 2019 Ridgecrest earthquake sequence on Twitter and Reddit

Scientific reports

2022/1/31

Lyapunov-type inequalities for third-order linear and half-linear difference equations and extensions

Journal of Difference Equations and Applications

2021/1/2

Sougata Dhar
Sougata Dhar

H-Index: 6

Qingkai Kong
Qingkai Kong

H-Index: 19

Deep Learning Based Approach to Integrate MyShake's Trigger Data with ShakeAlert for Faster and Robust EEW Alerts

2021/12/14

Qingkai Kong
Qingkai Kong

H-Index: 19

MyShake+ ShakeAlert: Incorporating Smartphone Seismic Data for Improved Earthquake Early Warning Performance

AGU Fall Meeting Abstracts

2021/12

Qingkai Kong
Qingkai Kong

H-Index: 19

Richard Allen
Richard Allen

H-Index: 62

Predicting Wind-Driven Spatial Patterns via Deep Convolutional Autoencoders

AGU Fall Meeting Abstracts

2021/12

Qingkai Kong
Qingkai Kong

H-Index: 19

Gemma Anderson
Gemma Anderson

H-Index: 17

Combining deep learning with physics extracted features in Explosion event discrimination

AGU Fall Meeting Abstracts

2021/12

Qingkai Kong
Qingkai Kong

H-Index: 19

Brandon Schmandt
Brandon Schmandt

H-Index: 29

See List of Professors in Qingkai Kong University(Northern Illinois University)