Dr Yashar Moshfeghi

Reader

Computer and Information Sciences

Personal statement

I am a Reader (Associate Professor) in Artificial Intelligence and Data Science at the University of Strathclyde, where I have founded and lead the NeuraSearch Laboratory. Our laboratory bridges human intelligence to artificial intelligence by operating at the forefront of Neuroscience, Data Science, and AI.

Within the NeuraSearch Laboratory, our focus is on the development of cutting-edge Recommender Systems and Information Retrieval Systems. We specialize in harnessing Natural Language Processing, Language Modeling, Machine Learning, and Deep Learning techniques to create innovative solutions. Specifically, we concentrate on identifying, understanding, and modelling brain activities related to complex information search processes.

These innovative areas of research have yielded more than 90 publications to date, including peer-reviewed journals and full conference papers. Our research has a wider appeal beyond academia, fostering collaborations with various companies through initiatives like KTP, KE, and consultancy projects.

If you are a highly motivated individual seeking opportunities for PhD, Post-doc, Fellowships (e.g. Newton International Fellowship, Marie-Curie Postdoctoral Fellowship, etc.) or short-term projects (e.g., ERASMUS, Commonwealth, etc.) within the dynamic environment of the NeuraSearch Laboratory, I encourage you to reach out. Your enthusiasm for advancing knowledge in these fields would be a valuable addition to our collaborative and forward-thinking team.

Expertise

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Prize And Awards

Poster Prize: Recipient; 2/6/2026
Multiparty Collaboration Award at the Scottish Knowledge Exchange Awards: Recipient; 2026
People's Choice Poster Prize: Recipient; 19/6/2025
ACM SIGIR Conference Outstanding Reviewer Award: Recipient; 2025
Scottish Knowledge Exchange Awards (Powerful Partnership Award): Recipient; 2025
Best Presentation Award, Scottish Dementia Research Consortium Conference: Recipient; 2025

More prizes and awards

Publications

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Publications

On length bias in EEG-to-text decoding: Tenedios Iakovos, Moshfeghi Yashar; The Fortieth Annual Conference on Neural Information Processing Systems (2026)
Neural correlates of information gain during search revealed by fMRI: Paisalnan Sakrapee, Moshfeghi Yashar, Pollick Frank; iScience Vol 29 (2026); https://doi.org/10.1016/j.isci.2026.117445
TVGL-CFM: Generating and forecasting time-varying trajectories of dynamic networks with conditional flow matching: Roy Om, Moshfeghi Yashar, Smith Keith Malcolm; Learning on Graphs Conference 2026 (2026)
Psychological vulnerability in conversational AI : how incentive and urgency manipulations alter trust formation and privacy behaviour across healthcare, financial, commercial, and security contexts: Aboshi Stephen, Thomas Daniel R, Moshfeghi Yashar; International Journal of Human Computer Studies Vol 218 (2026); https://doi.org/10.1016/j.ijhcs.2026.103941
Cross-sensory comparison of EEG signals for brain-based information retrieval: McGuire Niall, Moshfeghi Yashar; SIGIR 2026 - Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval 49th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2026, pp. 3988-3993 (2026); https://doi.org/10.1145/3805712.3809922
Towards inclusive retrieval-augmented generation : challenges and opportunities for cognitively impaired users: Rogers Claire, Z A M Alqadri Asmaa, Beaton Fiona A, Moshfeghi Yashar; SIGIR '26: Proceedings of the 49th International ACM SIGIR Conference on Research and Development in Information Retrieval 49th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2026, pp. 2708-2720 (2026); https://doi.org/10.1145/3805712.3808546

More publications

Teaching

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Teaching

Current Modules:

Fundamentals of Machine Learning for Data Analytics
Advance Machine Learning Techniques

Past Modules:

Big Data Fundamentals
Big Data Tools and Techniques

Research

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Research Interests

My research vision has been to develop the underlying and core technology of "pro-active" information systems, which has an essential and challenging data science task: accurately infer and predict the immediate information needs of users by processing, analysing, and learning from abundant big data gathered from various sources including brain activation data gathered via MRI and EEG devices. My research interests and expertise are in line with Neuroscience, Information Retrieval, Natural Language Processing, Data Mining, Machine Learning and Deep Learning. My interests, however, are extended beyond Information Retrieval and pertain to rigorously understanding the world of Data Science and Artificial Intelligence.