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

Runner-up 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
CIS Postgraduate Research Conference, Best Paper and Best Poster Awards (linked to the Euan Minto Prize): Recipient; 2025
Best Presentation Award, Scottish Dementia Research Consortium Conference: Recipient; 2025
Scottish Knowledge Exchange Awards (Powerful Partnership Award): Recipient; 2025

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Publications

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Publications

Electroencephalography subject detection : opportunity or threat?: McGuire Niall, Moshfeghi Yashar; Human-centric Computing and Information Sciences Vol 16 (2026); https://doi.org/10.22967/HCIS.2026.16.030
On the use of electroencephalography in query performance prediction: Tenedios Iakovos, McGuire Niall, Moshfeghi Yashar; ACM Transactions on Information Systems, pp. 1-33 (2026); https://doi.org/10.1145/3816244
Exploring information access in aging populations and those with dementia and mild cognitive impairment in the United Kingdom : survey and focus group study: Rogers Claire, McGeown William J, Moshfeghi Yashar; JMIR Aging Vol 9 (2026); https://doi.org/10.2196/85626
Learning the limits : how data, diversity, and representation control machine-learning predictions of reorganisation energy: Zollner Malin, Moshfeghi Yashar, Nematiaram Tahereh; Journal of Materials Chemistry. C Vol 14, pp. 5999-6011 (2026); https://doi.org/10.1039/D5TC04408A
Empowering stakeholders with participatory auditing of predictive AI : perspectives from end-users and decision subjects without AI expertise: Di Campli San Vito Patrizia, Fringi Eva, Johnston Penny S, Bezerra Leonardo CT, Aristodemou Marios, Shahandashti Siamak F, O'Hara Emily, Whyte Laura Fiona, Luo Lin, Wong Mark, Soufan Ayah, Moshfeghi Yashar, Stumpf Simone; CHI '26 2026 CHI Conference on Human Factors in Computing Systems, CHI 2026 Conference on Human Factors in Computing Systems - Proceedings, pp. 1-35 (2026); https://doi.org/10.1145/3772318.3791757
To bot or not? Conversational agents and authentic heritage experiences: Kist Cassandra, Moshfeghi Yashar; CHI EA '26: Proceedings of the Extended Abstracts of the 2026 CHI Conference on Human Factors in Computing Systems ACM CHI Conference in Human Factors in Computing Systems 2026, pp. 1-5 (2026); https://doi.org/10.1145/3772363.3798924

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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.