Dr Jabir Alshehabi Al-Ani

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Contact

profile_image:

Name:

Dr Jabir Alshehabi Al-Ani

Email:

j.alshehabialani@yorksj.ac.uk

Department:

School of Science, Technology & Health

Organisation:

York St. John University

Address:

York St John University, Lord Mayor’s Walk, York, YO31 7EX

Country:

United Kingdom

Homepage:

https://www.yorksj.ac.uk/our-staff/staff-profiles/jabir-alshehabi-al-ani.php

Biography

Expertise:

Natural Language Processing, Machine Learning, Artificial Intelligence, Image Processing, Neural Networks, Data Science

Job title:

Lecturer

Biography:

My name is Jabir Alshehabi Al-Ani and I am a lecturer at York St. John University, Data Science department. I have a PhD in computer science from the department of Computer Science and Electronic Engineering - University of Essex, UK .I have over 10 years knowledge in Machine Learning, AI, NLP, Data Retrieval, and Information Extraction both in academic and research environments, and industry.

Qualifications:

Ph. D. in Computer Science - University of Essex, M. Sc. in Computer Science - Al-Nahrain University, B. Sc. in Computer Science - Al-Nahrain University

My Latest

Mohammad, Ahmad Saeed and Alshehabi Al-Ani, Jabir ORCID: https://orcid.org/0000-0002-0553-2538 (2019) Convolutional Neural Network for Ethnicity Classification using Ocular Region in Mobile Environment. In: Proceedings of 2018 10th Computer Science and Electronic Engineering (CEEC. IEEE, pp. 293-298
Konnikov, Alla, Denier, Nicole, Hu, Yang, Hughes, Karen D., Alshehabi Al-Ani, Jabir ORCID: https://orcid.org/0000-0002-0553-2538, Ding, Lei, Rets, Irina and Tarafdar, Monideepa (2022) BIAS Word inventory for work and employment diversity, (in)equality and inclusivity (Version 1.0). SocArXiv.
Mohammad, Ahmad Saeed, Alshehabi Al-Ani, Jabir ORCID: https://orcid.org/0000-0002-0553-2538 and Zaghar, Dhafer (2021) Machine Learning for Prediction of Wind Power and Resources in Hot Climate Region. In: Proceedings 2021 International Conference on Computing and Communications Applications and Technologies (I3CAT). IEEE
Alshehabi Al-Ani, Jabir ORCID: https://orcid.org/0000-0002-0553-2538 and Fasli, Maria (2019) Probabilistic Relational Supervised Topic Modelling using Word Embeddings. In: Proceedings 2018 IEEE International Conference on Big Data (Big Data). IEEE
Mohammad, Ahmad Saeed and Alshehabi Al-Ani, Jabir ORCID: https://orcid.org/0000-0002-0553-2538 (2017) Towards ethnicity detection using learning based classifiers. In: Proceedings of the 2017 9th Computer Science and Electronic Engineering (CEEC). IEEE
Shenggang Hu, Shenggang Hu, Alshehabi Al-Ani, Jabir ORCID: https://orcid.org/0000-0002-0553-2538, Hughes, Karen D., Denier, Nicole, Konnikov, Alla, Ding, Lei, Jinhan, Jinhan, Yang, Yang, Monideepa, Monideepa, Bei, Bei, Linglong, Linglong and Hongsheng, Hongsheng (2022) Balancing Gender Bias in Job Advertisements with Text-Level Bias Mitigation. Frontiers in Big Data, 5.
Hu, Shenggang, Alshehabi Al-Ani, Jabir ORCID: https://orcid.org/0000-0002-0553-2538, Hughes, Karen D., Denier, Nicole, Konnikov, Alla, Ding, Lei, Xie, Jinhan, Hu, Yang, Tarafdar, Monideepa, Jiang, Bei, Kong, Linglong and Dai, Hongsheng (2022) Balancing Gender Bias in Job Advertisements With Text-Level Bias Mitigation. Frontiers in Big Data, 5.
Alshehabi Al-Ani, Jabir ORCID: https://orcid.org/0000-0002-0553-2538 and Fasli, M. (2020) Probabilistic Named Entity Recognition for nonstandard format entities using cooccurrence word embeddings. In: Proceedings - 2019 IEEE International Conference on Big Data, Big Data 2019. IEEE

My Most Viewed

#	Item title
1	BIAS Word inventory for work and employment diversity, (in)equality and inclusivity (Version 1.0)	29	13
2	Probabilistic Named Entity Recognition for nonstandard format entities using cooccurrence word embeddings	4
3	Machine Learning for Prediction of Wind Power and Resources in Hot Climate Region	3
4	Towards ethnicity detection using learning based classifiers	3
5	Balancing Gender Bias in Job Advertisements with Text-Level Bias Mitigation	2	3
6	Balancing Gender Bias in Job Advertisements With Text-Level Bias Mitigation	1	3
7	Probabilistic Relational Supervised Topic Modelling using Word Embeddings	1