Dr Kulvinder Panesar
Dr Kulvinder Panesar is a Assistant Professor in Applied Artificial Intelligence in the Faculty of Engineering and Informatics, in the School of Computer Science, AI and Electronics at the University of Bradford.
Kulvinder worked previously as a Senior Lecturer in Computer Science at York St University. She has been an academic for over twenty years, and a strategically focused senior computing professional wearing different hats including programmer, professional practice co-ordinator, research scientist, computational linguistic, software and website developer, database designer and developer, systems analyst, project manager and technical consultant.
Her teaching interests are in the branches of AI more specifically NLP (statistical and linguistic - (semantic)), computer vision (object detection), data mining, analytics (databases to AI), intelligent agents and knowledge representation and reasoning, project management, project supervision and AI project design and development, AI ethics and more recently conversational AI solutions, AI agent building and AI powered solutions.
Her PhD was titled ‘a linguistically centred text-based conversational software Agent’. Her research area is multi-disciplinary spanning AI, data science, agent thinking, linguistics, computational linguistics, NLP, KR, and the Semantic Web. She has conceptually designed and developed a linguistically text based conversational software agent (LING-CSA) framework, addressing the integration, intersection, and interface of language, knowledge, and speech act constructions (SAC). LING-CSA is a Java based prototype developed in Eclipse.
Her research contributions included: (i) extending the theoretical and computational adequacy of the linguistic theory - Role and Reference Grammar (RRG); (ii) integrating the RRG language model with concept of speech act constructions (SAC) as the linguistic engine; (iii) motivating an agent framework intersecting with the linguistic engine, an agent cognitive and dialogue model to facilitate conversation implemented as a proof-of-concept; (4) insights into the language/knowledge representation interface.
Previous research interest involves demystifying statistical vs linguistic NLP for conversational software agents, with the goal to investigating linguistic NLP with statistical NLP learning and support – for forward-thinking hybrid approach to conversational AI.
A strategic academic leader and AI researcher driving innovation at the intersection of AI, Natural Language Processing (NLP), and Healthcare Technology. Spearheading research initiatives and cross-disciplinary collaborations focused on leveraging AI to address real-world challenges, particularly within healthcare, cognitive assessment, and ethical AI deployment.
Involved in AI research Leadership & grant development for several projects as PI on multiple high-profile AI research projects, leading proposal development for funding applications ranging from £1M to £2M. Further developed research on AI-powered pre-screening tools for dementia and cognitive function, integrating NLP, speech analysis, and conversational agents. Successfully designed conceptual architecture and hybrid AI frameworks, combining traditional linguistic models with advanced state-of-the-art NLP and speech synthesis techniques.
Major research highlights: (1) Led a preliminary study on a language & cognition AI assessment model for early dementia detection — presented at the RRG Conference (2021). (2) Developed a 36-month EPSRC New Investigator Grant proposal (2022), exploring the hybridisation of linguistic NLP with conversational AI for cognitive healthcare solutions. (3) Presented architectural frameworks at the KMR Conference (2022), focusing on multi-modal AI for health screening. (4) Published key research findings in the Journal of Language and Health (Elsevier, Dec 2023).
Submitted research proposals to prestigious bodies as the PI including: (1) UKRI AI Health (2023); (2) NIHR Researcher-Led Call (2023): Multimodal AI Agent for Cognitive Pre-Screening in Older Adults (3) EPSRC & NIHR (2024): MATI – Multimodal AI Assistance Tool for home-based dementia support. (4) In collaboration - UK National Crime Agency - AI4SOC: duality of AI in tackling Serious Organised Crime, with specific intervention strategies for Child Sexual Exploitation and Abuse (CSE/A)
Currrent co-Investigator on a British Council International Science Partnerships Fund grant (Early Career Researcher Collaboration), further strengthening global AI research networks.
Kulvinder is a MBCS member of the British Computer Society, a UKRI Talent Peer Review College Reviewer (Sept 2023 to date), STEM ambassador, an AI Ambassador to AI Expert for AI-Tech.UK, Start-up in Leeds, UK (Voluntary); AI Smart Ethics tool contributor for 2yrs (AI Tech.UK), Mentor for 4yrs (Reed recruitment) and WeAreTechWomen100 - 2019 winner listed awarded by J P Morgan.
Supervisors: Dr Brian Nolan, Institute of Blanchardtown, Dublin, Ireland, Dr Mark Dixon, School of Computing, Leeds Beckett University, and UK
Phone: +447737569913
Address: Richmond Road
Kulvinder worked previously as a Senior Lecturer in Computer Science at York St University. She has been an academic for over twenty years, and a strategically focused senior computing professional wearing different hats including programmer, professional practice co-ordinator, research scientist, computational linguistic, software and website developer, database designer and developer, systems analyst, project manager and technical consultant.
Her teaching interests are in the branches of AI more specifically NLP (statistical and linguistic - (semantic)), computer vision (object detection), data mining, analytics (databases to AI), intelligent agents and knowledge representation and reasoning, project management, project supervision and AI project design and development, AI ethics and more recently conversational AI solutions, AI agent building and AI powered solutions.
Her PhD was titled ‘a linguistically centred text-based conversational software Agent’. Her research area is multi-disciplinary spanning AI, data science, agent thinking, linguistics, computational linguistics, NLP, KR, and the Semantic Web. She has conceptually designed and developed a linguistically text based conversational software agent (LING-CSA) framework, addressing the integration, intersection, and interface of language, knowledge, and speech act constructions (SAC). LING-CSA is a Java based prototype developed in Eclipse.
Her research contributions included: (i) extending the theoretical and computational adequacy of the linguistic theory - Role and Reference Grammar (RRG); (ii) integrating the RRG language model with concept of speech act constructions (SAC) as the linguistic engine; (iii) motivating an agent framework intersecting with the linguistic engine, an agent cognitive and dialogue model to facilitate conversation implemented as a proof-of-concept; (4) insights into the language/knowledge representation interface.
Previous research interest involves demystifying statistical vs linguistic NLP for conversational software agents, with the goal to investigating linguistic NLP with statistical NLP learning and support – for forward-thinking hybrid approach to conversational AI.
A strategic academic leader and AI researcher driving innovation at the intersection of AI, Natural Language Processing (NLP), and Healthcare Technology. Spearheading research initiatives and cross-disciplinary collaborations focused on leveraging AI to address real-world challenges, particularly within healthcare, cognitive assessment, and ethical AI deployment.
Involved in AI research Leadership & grant development for several projects as PI on multiple high-profile AI research projects, leading proposal development for funding applications ranging from £1M to £2M. Further developed research on AI-powered pre-screening tools for dementia and cognitive function, integrating NLP, speech analysis, and conversational agents. Successfully designed conceptual architecture and hybrid AI frameworks, combining traditional linguistic models with advanced state-of-the-art NLP and speech synthesis techniques.
Major research highlights: (1) Led a preliminary study on a language & cognition AI assessment model for early dementia detection — presented at the RRG Conference (2021). (2) Developed a 36-month EPSRC New Investigator Grant proposal (2022), exploring the hybridisation of linguistic NLP with conversational AI for cognitive healthcare solutions. (3) Presented architectural frameworks at the KMR Conference (2022), focusing on multi-modal AI for health screening. (4) Published key research findings in the Journal of Language and Health (Elsevier, Dec 2023).
Submitted research proposals to prestigious bodies as the PI including: (1) UKRI AI Health (2023); (2) NIHR Researcher-Led Call (2023): Multimodal AI Agent for Cognitive Pre-Screening in Older Adults (3) EPSRC & NIHR (2024): MATI – Multimodal AI Assistance Tool for home-based dementia support. (4) In collaboration - UK National Crime Agency - AI4SOC: duality of AI in tackling Serious Organised Crime, with specific intervention strategies for Child Sexual Exploitation and Abuse (CSE/A)
Currrent co-Investigator on a British Council International Science Partnerships Fund grant (Early Career Researcher Collaboration), further strengthening global AI research networks.
Kulvinder is a MBCS member of the British Computer Society, a UKRI Talent Peer Review College Reviewer (Sept 2023 to date), STEM ambassador, an AI Ambassador to AI Expert for AI-Tech.UK, Start-up in Leeds, UK (Voluntary); AI Smart Ethics tool contributor for 2yrs (AI Tech.UK), Mentor for 4yrs (Reed recruitment) and WeAreTechWomen100 - 2019 winner listed awarded by J P Morgan.
Supervisors: Dr Brian Nolan, Institute of Blanchardtown, Dublin, Ireland, Dr Mark Dixon, School of Computing, Leeds Beckett University, and UK
Phone: +447737569913
Address: Richmond Road
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