Dr Vinod Kumar Chauhan Kumar
黑料正能量 Chancellor's Fellow
Computer and Information Sciences
Personal statement
I am a 黑料正能量 Chancellor's Fellow in AI (Lecturer/Assistant Professor) in the Department of Computer and Information Sciences at the University of 黑料正能量. My primary research interests are in Causality, Healthcare, and Artificial Intelligence, with a long-term vision of realising personalised treatments through data-driven Causal AI. Before joining 黑料正能量, I was a Postdoctoral Researcher at the Department of Engineering Science, University of Oxford, and the Department of Engineering, University of Cambridge, where I worked for over six years. During this time, I had the opportunity to collaborate with world-renowned clinicians and industry leaders, including Boeing and Rolls-Royce. At Cambridge, I was honoured to receive the Institute for Manufacturing Postdoctoral Award for Research Excellence in recognition of the practical impact of my work. I completed my PhD in optimisation for large-scale machine learning at Panjab University, Chandigarh, supported by the University Grants Commission鈥檚 JRF and SRF fellowships. I actively contribute to the research community and have reviewed over 200 articles for more than 50 international conferences and journals. I currently serve as an Associate Editor for PLOS Digital Health and as an Editorial Board Member for the International Journal of Artificial Intelligence in Healthcare. I welcome enquiries from motivated MSc (Research) and PhD students interested in causal AI, machine learning, and healthcare applications. I am also open to collaborations with academic, clinical, and industry partners who are committed to developing impactful solutions for real-world healthcare challenges.
Prize And Awards
- Recipient
- 2025
- Recipient
- 2021
- Recipient
- 2020
- Recipient
- 11/2017
- Recipient
- 2017
- Recipient
- 2015
Publications
- , Clifton Lei, Sala眉n Achille, Lu Huiqi Yvonne, Branson Kim, Schwab Patrick, Nigam Gaurav, Clifton David A
- ACM Transactions on Computing for Healthcare Vol 6, pp. 1-24 (2025)
- , Zhou Jiandong, Lu Ping, Molaei Soheila, Clifton David A
- Artificial Intelligence Review Vol 57 (2024)
- , Clifton Lei, Nigam Gaurav, Clifton David A
- 2025 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (2025)
- de Fabritiis F, Gryllias K, , Clifton D A
- Proceedings of the 31th International Congress on Sound and Vibration, ICSV 2025 31th International Congress on Sound and Vibration, ICSV 2025 Proceedings of the International Congress on Sound and Vibration (2025)
- , Singh Sukhdeep, Sharma Anuj
- Multimedia Tools and Applications Vol 83, pp. 78433-78467 (2024)
- Molaei Soheila, Niknam Ghazaleh, Ghosheh Ghadeer O, , Zare Hadi, Zhu Tingting, Pan Shirui, Clifton David A
- Knowledge-Based Systems Vol 299 (2024)
Research Interests
I have over a decade of research experience in AI and machine learning, spanning foundational methodology and applications in healthcare, manufacturing, aviation, supply chains, and handwriting recognition. While I am happy to lend my AI expertise to other disciplines, my primary interests are in AI for Healthcare with special interest in Causal AI, situated at the intersection of causality, medicine, and machine learning. My work combines theory and practice to develop robust methodologies for real-world clinical challenges, with a particular focus on data-driven personalised treatments.
Topics of interest include, but are not limited to:
- Personalised treatments and individualised treatment effect estimation
- Causal inference and discovery from observational data at scale
- Counterfactual reasoning for fairness, explainability, and clinical decision support
- Causal foundation models
- Causal digital twins
- Uncertainty quantification and conformal prediction
- Multimodal, federated, and continual learning
- Synthetic data generation, causal benchmarking, and evaluation
- Optimisation methods for causal and AI models
- Domain adaptation and out-of-distribution detection
Professional Service & Leadership
I actively contribute to advancing Causal AI and AI for Healthcare through research leadership, peer review, and editorial service.
- Reviewed over 200 manuscripts for more than 50 international journals and conferences, including ICML and AI in Medicine
- Associate Editor: PLOS Digital Health
- Editorial Board Member: International Journal of Artificial Intelligence in Healthcare
- Guest Editor: Special Issue on for the Frontiers in AI, Frontiers in Digital Health听补苍诲 Frontiers in Big Data journals, with full manuscript submissions by 27 May 2026.
Opportunities for Students and Collaborators
I welcome collaborations with academic, clinical (including NHS), and industry partners who share the goal of addressing real-world healthcare challenges with robust and trustworthy AI.
I also invite applications from motivated MSc and PhD students interested in causal AI, personalised treatments, and healthcare applications of machine learning.
A fully funded PhD studentship in Causal AI for Personalised Healthcare is currently available; interested candidates are encouraged to get in touch for an informal discussion.
Professional Memberships
- Association for Computing Machinery (ACM)
- IEEE & IEEE Engineering in Medicine and Biology Society (EMBS)
- EMBS Technical Committee on Biomedical and Health Informatics
- Computer Society of India (Lifetime Member)
- Indian Society for Technical Education (Lifetime Member)
Professional Activities
- Guest editor
- 24/7/2025
- Editorial board member
- 11/7/2026
- Speaker
- 16/4/2026
- Peer reviewer
- 12/3/2026
- Peer reviewer
- 2026
- Editorial board member
- 6/12/2025
Projects
- Kumar, Vinod (Principal Investigator)
- 01-Jan-2025 - 30-Jan-2027
Contact
Dr
Vinod Kumar Chauhan
Kumar
黑料正能量 Chancellor's Fellow
Computer and Information Sciences
Email: vinod.kumar@strath.ac.uk
Tel: Unlisted