Yutian Pang

Yutian Pang

Arizona State University

H-index: 10

North America-United States

About Yutian Pang

Yutian Pang, With an exceptional h-index of 10 and a recent h-index of 10 (since 2020), a distinguished researcher at Arizona State University, specializes in the field of Aviation Safety, AI in Aviation, System Engineering.

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

PIGAT: Physics-Informed Graph Attention Transformer for Air Traffic State Prediction

Decentralized graph-based multi-agent reinforcement learning using reward machines

Machine learning-enhanced aircraft landing scheduling under uncertainties

Epistemic and aleatoric uncertainty quantification for crack detection using a Bayesian Boundary Aware Convolutional Network

Air traffic controller workload level prediction using conformalized dynamical graph learning

Air traffic density prediction using Bayesian ensemble graph attention network (BEGAN)

Posterior Regularized Bayesian Neural Network incorporating soft and hard knowledge constraints

Artificial Intelligence-Enhanced Predictive Modeling in Air Traffic Management

Yutian Pang Information

University

Position

___

Citations(all)

353

Citations(since 2020)

353

Cited By

41

hIndex(all)

10

hIndex(since 2020)

10

i10Index(all)

11

i10Index(since 2020)

11

Email

University Profile Page

Google Scholar

Yutian Pang Skills & Research Interests

Aviation Safety

AI in Aviation

System Engineering

Top articles of Yutian Pang

PIGAT: Physics-Informed Graph Attention Transformer for Air Traffic State Prediction

IEEE Transactions on Intelligent Transportation Systems

2024/4/19

Decentralized graph-based multi-agent reinforcement learning using reward machines

Neurocomputing

2024/1/7

Machine learning-enhanced aircraft landing scheduling under uncertainties

Transportation Research Part C: Emerging Technologies

2024/1/1

Epistemic and aleatoric uncertainty quantification for crack detection using a Bayesian Boundary Aware Convolutional Network

Reliability Engineering & System Safety

2023/12/1

Air traffic controller workload level prediction using conformalized dynamical graph learning

Advanced Engineering Informatics

2023/8/1

Air traffic density prediction using Bayesian ensemble graph attention network (BEGAN)

Transportation Research Part C: Emerging Technologies

2023/8/1

Yutian Pang
Yutian Pang

H-Index: 4

Yongming Liu
Yongming Liu

H-Index: 29

Posterior Regularized Bayesian Neural Network incorporating soft and hard knowledge constraints

Knowledge-Based Systems

2023/1/10

Artificial Intelligence-Enhanced Predictive Modeling in Air Traffic Management

2023

Yutian Pang
Yutian Pang

H-Index: 4

ProspectNet: Weighted conditional attention for future interaction modeling in behavior prediction

arXiv preprint arXiv:2208.13848

2022/8/29

Yutian Pang
Yutian Pang

H-Index: 4

Binnan Zhuang
Binnan Zhuang

H-Index: 6

Bayesian spatio-temporal graph transformer network (b-star) for multi-aircraft trajectory prediction

Knowledge-Based Systems

2022/8/5

Fracture pattern prediction with random microstructure using a physics-informed deep neural networks

Engineering Fracture Mechanics

2022/6/1

Robust satellite image classification with Bayesian deep learning

2022/4/5

Optimal maintenance scheduling under uncertainties using Linear Programming-enhanced Reinforcement Learning

Engineering Applications of Artificial Intelligence

2022/3/1

Data-driven trajectory prediction with weather uncertainties: A Bayesian deep learning approach

Transportation Research Part C: Emerging Technologies

2021/9/1

Uncertainty quantification and reduction in aircraft trajectory prediction using Bayesian-Entropy information fusion

Reliability Engineering & System Safety

2021/8/1

Evaluating the Robustness of Bayesian Neural Networks Against Different Types of Attacks

arXiv preprint arXiv:2106.09223

2021/6/17

A voice communication-augmented simulation framework for aircraft trajectory simulation

IEEE Transactions on Intelligent Transportation Systems

2021/3/30

Conditional generative adversarial networks (CGAN) for aircraft trajectory prediction considering weather effects

2020

Yutian Pang
Yutian Pang

H-Index: 4

Yongming Liu
Yongming Liu

H-Index: 29

Probabilistic aircraft trajectory prediction with weather uncertainties using approximate Bayesian variational inference to neural networks

2020

Probabilistic aircraft trajectory prediction considering weather uncertainties using dropout as Bayesian approximate variational inference

2020

Yutian Pang
Yutian Pang

H-Index: 4

Yongming Liu
Yongming Liu

H-Index: 29

See List of Professors in Yutian Pang University(Arizona State University)