Logo-Breda_University_of_Applied_Sciences-Colour

Peiman Barnaghi, Ph.D.

Peiman is a Lecturer in Computer Science, specializing in Machine Learning and Natural Language Processing (NLP). His PhD research focused on developing advanced methods for aspect-based sentiment analysis across diverse domains, contributing to the growing field of explainable and domain-adaptive NLP.
In addition to his research, Peiman holds an Associate Fellowship of the Higher Education Academy (HEA), awarded through the UK Professional Standards Framework (PGCert), recognizing his commitment to high-quality teaching and learning support in higher education. He has taught extensively as a Graduate Teaching Assistant (GTA) at Edge Hill University, and currently teaches modules for first- and second-year students in machine learning and NLP.

Before commencing his doctoral studies, Peiman was actively involved in industry-led research and development projects. Notably, he contributed to the Horizon 2020-funded project on complex stream data management, where he developed techniques for pattern detection in heterogeneous data streams using open data. He also worked on the News API project, focusing on social media analytics, where he implemented systems for language detection, entity and keyword extraction, feature engineering, and content filtering.

Peiman’s academic and professional trajectory bridges cutting-edge research with practical applications, aiming to equip students with the tools and critical thinking skills needed to thrive in the evolving fields of AI and data science.

 

Expertise

  • Artificial Intelligence
  • Data Science
  • Deep Learning
  • Machine Learning
  • Natural Language Processing

 

Teaching

  • Machine Learning
  • Natural Language Processing (NLP)

 

Education

  • Ph.D. Artificial Intelligence, Edge Hill University, 2022
  • M.Sc. Artificial Intelligence, National University of Malaysia, 2013

 

Publications

  • P. Barnaghi, Y. Korkontzelos, Aspect Based Sentiment Analysis in Reviews using Word Embeddings and Deep Learning, Knowledge-Based Systems, 2022
  • P. Barnaghi, P. Ghaffari, JG Breslin, Opinion Mining and Sentiment Polarity on Twitter and Correlation between Events and Sentiment, IEEE Second International Conference on Big Data Computing Service and Applications, 2016
  • P Barnaghi, P Ghaffari, J G. Breslin, Text Analysis and Sentiment Polarity on FIFA World Cup 2014 Tweets, Conference ACM SIGKDD, 2015
  • PM Barnaghi, VA Sahzabi, AA Bakar, A comparative study for various methods of classification, International Conference on Information and Computer Networks, 2012

 

Highlights