Urja Pawar

Cork Institute of Technology

H-index: 5

Europe-Ireland

About Urja Pawar

Urja Pawar, With an exceptional h-index of 5 and a recent h-index of 5 (since 2020), a distinguished researcher at Cork Institute of Technology, specializes in the field of AI, ML, XAI, Healthcare.

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

Optimal Neighborhood Contexts in Explainable AI: An Explanandum-Based Evaluation

On the Impact of Neighbourhood Sampling to Satisfy Sufficiency and Necessity Criteria in Explainable AI

Classification of Stress via Ambulatory ECG and GSR Data

Evaluating hierarchical medical workflows using feature importance

Explainable AI in Healthcare

Incorporating Explainable Artificial Intelligence (XAI) to aid the Understanding of Machine Learning in the Healthcare Domain

Urja Pawar Information

University	Cork Institute of Technology
Position	PhD Student (2019-Present)
Citations(all)	491
Citations(since 2020)	489
Cited By	84
hIndex(all)	5
hIndex(since 2020)	5
i10Index(all)	4
i10Index(since 2020)	4
Email	Access Email
University Profile Page	Cork Institute of Technology
Google Scholar	View Google Scholar Profile

Urja Pawar Skills & Research Interests

XAI

Healthcare

Top articles of Urja Pawar

Title	Journal	Author(s)	Publication Date
Optimal Neighborhood Contexts in Explainable AI: An Explanandum-Based Evaluation	IEEE Open Journal of the Computer Society	Urja Pawar Donna O'Shea Ruairi O'Reilly Maebh Costello Christian Beder	2024/4/18
On the Impact of Neighbourhood Sampling to Satisfy Sufficiency and Necessity Criteria in Explainable AI		Urja Pawar Christian Beder O Ruairi O Donna	2024/3/15
Classification of Stress via Ambulatory ECG and GSR Data		Zachary Dair Muhammad Saad Urja Pawar Ruairi O'Reilly Samantha Dockray	2022/7/19
Evaluating hierarchical medical workflows using feature importance		Urja Pawar Christopher T Culbert Ruairi O'Reilly	2021/6/7
Explainable AI in Healthcare		Hritik Rao Arshia Khan	2022/12/14
Incorporating Explainable Artificial Intelligence (XAI) to aid the Understanding of Machine Learning in the Healthcare Domain		Urja Pawar Donna O'Shea Susan Rea Ruairi O'Reilly	2020/12