CV

Postdoctoral Research Scientist

Northeastern University

Research on NLP for low-resource languages, focusing on Hausa and other African languages. Collaborating with a team of researchers to develop innovative solutions for NLP challenges.

• Developed a novel datasets for hate speech detection and emotion analysis.
• Published multiple papers in top-tier NLP conferences and journals.
• Developed multiple funding proposals for research projects.

PhD

Universiti Kebangsaan Malaysia

Natural Language Processing

Best Paper Award

International Conference on Affective Computing and Intelligent Interaction (ACII 2025)

The paper titled: Analyzing Cultural Representations of Emotions in LLMs through Mixed Emotion Survey selected as best paper in ACII 2025 conference held at Glasgow, UK.

SemRel2024: A Collection of Semantic Textual Relatedness Datasets for 13 Languages

Findings of the Association for Computational Linguistics: ACL 2024

Introduces a collection of semantic textual relatedness datasets covering 13 different languages.

HausaHate: An Expert Annotated Corpus for Hausa Hate Speech Detection

Proceedings of the 8th Workshop on Online Abuse and Harms (WOAH 2024)

Presents a corpus of Hausa language text annotated by experts for hate speech detection.

Impact of social media posts' characteristics on movie performance prior to release: an explainable machine learning approach

Electronic Commerce Research

Explores how characteristics of social media posts about movies before their release correlate with movie performance using explainable machine learning methods.

Analyzing COVID-19 Vaccination Sentiments in Nigerian Cyberspace: Insights from a Manually Annotated Twitter Dataset

arXiv preprint

Analysis of public sentiment regarding COVID-19 vaccination in Nigeria using a manually annotated Twitter dataset.

Analyzing Cultural Representations of Emotions in LLMs through Mixed Emotion Survey

Proceedings of the 12th International Conference on Affective Computing and Intelligent Interaction (ACII)

A study examining how large language models represent emotions across different cultures through a mixed emotion survey methodology.

No Culture Left Behind: ArtELingo-28, a Benchmark of WikiArt with Captions in 28 Languages

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing

Introduces ArtELingo-28, a benchmark dataset of WikiArt with captions translated into 28 languages to support multilingual art description research.

Are generative language models multicultural? A study on Hausa culture and emotions using ChatGPT

Proceedings of the 2nd Workshop on Cross-Cultural Considerations in NLP

An analysis of how generative language models handle multicultural contexts, specifically examining Hausa culture and emotions through ChatGPT.

Findings of the IWSLT 2024 Evaluation Campaign

Proceedings of the 21st International Conference on Spoken Language Translation (IWSLT 2024)

This paper reports on shared tasks addressing seven scientific challenges in spoken language translation, attracting 18 teams with 26 system papers and showing growing interest in the field across industry and academia.

NaijaSenti: A Nigerian Twitter Sentiment Corpus for Multilingual Sentiment Analysis

Proceedings of the Thirteenth Language Resources and Evaluation Conference

Presents a corpus of Nigerian Twitter data for multilingual sentiment analysis.

A hybrid metaheuristic method in training artificial neural network for bankruptcy prediction

IEEE Access

Proposes a hybrid metaheuristic approach for training artificial neural networks specifically for bankruptcy prediction applications.

Beyond sentiment classification: A novel approach for utilizing social media data for business intelligence

International Journal of Advanced Computer Science and Applications

Presents a novel approach that goes beyond traditional sentiment classification to extract business intelligence from social media data.

A survey on machine learning techniques in movie revenue prediction

SN Computer Science

A comprehensive overview of machine learning approaches used in predicting movie revenue.

Movie revenue prediction based on purchase intention mining using YouTube trailer reviews

Information Processing & Management

A method for predicting movie revenues by analyzing purchase intention from YouTube trailer reviews.