ProfessorsProfessors of University of North Carolina at CharlotteGabriel A. Terejanu

Gabriel A. Terejanu

University of North Carolina at Charlotte

H-index: 18

North America-United States

About Gabriel A. Terejanu

Gabriel A. Terejanu, With an exceptional h-index of 18 and a recent h-index of 15 (since 2020), a distinguished researcher at University of North Carolina at Charlotte, specializes in the field of Causal Inference, Deep Learning, Bayesian Inference, Uncertainty Quantification, Model Validation.

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

Invariant Molecular Representations for Heterogeneous Catalysis

Causal Feature Selection: Methods and a Novel Causal Metric Evaluation Framework

Modeling the Effect of Surface Platinum–Tin Alloys on Propane Dehydrogenation on Platinum–Tin Catalysts

Machine fault classification using hamiltonian neural networks

Evaluation of induced expert knowledge in causal structure learning by NOTEARS

CD-NOTEARS: Concept Driven Causal Structure Learning Using NOTEARS

Propane dehydrogenation on platinum catalysts: identifying the active sites through Bayesian analysis

From causal pairs to causal graphs

Gabriel A. Terejanu Information

University	University of North Carolina at Charlotte
Position	Associate Professor
Citations(all)	1642
Citations(since 2020)	933
Cited By	1080
hIndex(all)	18
hIndex(since 2020)	15
i10Index(all)	29
i10Index(since 2020)	20
Email	Access Email
University Profile Page	University of North Carolina at Charlotte
Google Scholar	View Google Scholar Profile

Gabriel A. Terejanu Skills & Research Interests

Causal Inference

Deep Learning

Bayesian Inference

Uncertainty Quantification

Model Validation

Top articles of Gabriel A. Terejanu

Title	Journal	Author(s)	Publication Date
Invariant Molecular Representations for Heterogeneous Catalysis	Journal of Chemical Information and Modeling	Jawad Chowdhury Charles Fricke Olajide Bamidele Mubarak Bello Wenqiang Yang ...	2024/1/10
Causal Feature Selection: Methods and a Novel Causal Metric Evaluation Framework		Rezaur Rashid Jawad Chowdhury Gabriel Terejanu	2023/10/9
Modeling the Effect of Surface Platinum–Tin Alloys on Propane Dehydrogenation on Platinum–Tin Catalysts	ACS Catalysis	Charles H Fricke Olajide H Bamidele Mubarak Bello Jawad Chowdhury Gabriel Terejanu ...	2023/7/31
Machine fault classification using hamiltonian neural networks	arXiv preprint arXiv:2301.02243	Jeremy Shen Jawad Chowdhury Sourav Banerjee Gabriel Terejanu	2023/1/4
Evaluation of induced expert knowledge in causal structure learning by NOTEARS	arXiv preprint arXiv:2301.01817	Jawad Chowdhury Rezaur Rashid Gabriel Terejanu	2023/1/4
CD-NOTEARS: Concept Driven Causal Structure Learning Using NOTEARS		Jawad Chowdhury Gabriel Terejanu	2023/12/15
Propane dehydrogenation on platinum catalysts: identifying the active sites through Bayesian analysis	ACS Catalysis	Charles Fricke Biplab Rajbanshi Eric A Walker Gabriel Terejanu Andreas Heyden	2022/2/3
From causal pairs to causal graphs		Rezaur Rashid Jawad Chowdhury Gabriel Terejanu	2022/12/12
Comparative study on the machine learning-based prediction of adsorption energies for ring and chain species on metal catalyst surfaces	The Journal of Physical Chemistry C	Asif J Chowdhury Wenqiang Yang Andreas Heyden Gabriel A Terejanu	2021/8/10
Explainable deep modeling of tabular data using tablegraphnet	arXiv preprint arXiv:2002.05205	Gabriel Terejanu Jawad Chowdhury Rezaur Rashid Asif Chowdhury	2020/2/12
A multiple filter based neural network approach to the extrapolation of adsorption energies on metal surfaces for catalysis applications	Journal of Chemical Theory and Computation	Asif J Chowdhury Wenqiang Yang Kareem E Abdelfatah Mehdi Zare Andreas Heyden ...	2020/1/21