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

BAE Stars Award: Recipient; 9/2024
Honorary Senior Research Fellow, School of Computing Science, University of Glasgow: Recipient; 9/2024
SICSA Director of Research: Recipient; 2024
SICSA Artificial Intelligence & Data Science Theme Leader: Recipient; 2023
BCS-IRSG Inclusion Officer: Recipient; 2021
SICSA Data Science Theme Leader: Recipient; 2018

More prizes and awards

Publications

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Publications

On error classification from physiological signals within airborne environment: McGuire Niall, Moshfeghi Yashar; ACM CHI Conference on Human Factors in Computing Systems (2025)
Mental workload assessment using deep learning models from EEG Signals : a systematic review: Kingphai Kunjira, Moshfeghi Yashar; IEEE Transactions on Cognitive and Developmental Systems Vol 17, pp. 40-60 (2025); https://doi.org/10.1109/TCDS.2024.3460750
Accelerating the discovery of high-mobility molecular semiconductors : a machine learning approach: Nematiaram Tahereh, Lamprou Zenon, Moshfeghi Yashar; Chemical Communications Vol 61, pp. 3676-3679 (2025); https://doi.org/10.1039/D4CC04200J
Random Forest Classifiers to predict psychotic symptoms in Alzheimer's disease: Scarfo Sara, Moshfeghi Yashar, McGeown William; Alzheimer's & Dementia: The Journal of the Alzheimer's Association Vol 20 (2025); https://doi.org/10.1002/alz.092242
FAST functional connectivity implicates P300 connectivity in working memory deficits in Alzheimer’s disease: Roy Om, Moshfeghi Yashar, Ibanez Agustin, Lopera Francisco, Parra Mario A, Smith Keith; Network Neuroscience Vol 8, pp. 1467-1490 (2024); https://doi.org/10.1162/netn_a_00411
Neuroanatomical correlates and predictors of psychotic symptoms in Alzheimer's disease : a systematic review and meta-analysis: Scarfo Sara, Marsella Antonella MA, Grigoriadou Loulouda, Moshfeghi Yashar, McGeown William; Neuropsychologia Vol 204 (2024); https://doi.org/10.1016/j.neuropsychologia.2024.109006

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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.

Professional Activities

Strategic Themes: EPSRC Critical Mass Programmes to Drive a Sustainable Future: Participant; 30/1/2025
Shaping Dementia Care with Generative AI: Host; 10/2024
Dementia in the Age of Gen-AI: Host; 27/9/2024
Strategic Themes - Bioimaging Workshop: Participant; 17/9/2024
Alzheimer's Association International Conference (AAIC) 2024: Participant; 28/7/2024
Generative AI Mini Symposium: Organiser; 7/2024

More professional activities

Projects

£1,230 - Funded by Festival of Social Sciences - Shaping Dementia Care with Generative AI: Moshfeghi, Yashar (Principal Investigator) Rogers, Claire (Post Grad Student); 01-Jan-2024 - 31-Jan-2024
£300 - Funded by Explorathon - Dementia in the Age of Gen-AI: Moshfeghi, Yashar (Principal Investigator) Rogers, Claire (Post Grad Student); 11-Jan-2024 - 27-Jan-2024
£913.29 - Externally Funded by SICSA - Generative AI Mini Symposium: Moshfeghi, Yashar (Principal Investigator) Rogers, Claire (Post Grad Student); 01-Jan-2024 - 09-Jan-2024
Participatory Harm Auditing Workbenches and Methodologies (PHAWM): Moshfeghi, Yashar (Principal Investigator) Azzopardi, Leif (Co-investigator) Ruthven, Ian (Co-investigator); 01-Jan-2024 - 31-Jan-2028
Industrial CASE Account - University of Strathclyde 2021 | McGuire, Niall: Moshfeghi, Yashar (Principal Investigator) Goodfellow, Martin (Co-investigator) McGuire, Niall (Research Co-investigator); 01-Jan-2022 - 01-Jan-2027
EPSRC iCase PhD Studentships: Moshfeghi, Yashar (Principal Investigator); 01-Jan-2020 - 01-Jan-2023