Dr Vinod Kumar Chauhan Kumar
Strathclyde Chancellor's Fellow
Computer and Information Sciences
Prize And Awards
- MPLS Enterprise and Innovation Fellow 2025-26, University of Oxford
- Recipient
- 2025
- The Institute for Manufacturing Postdoctoral Award for Research Excellence
- Recipient
- 2021
- Junior Research Fellow (non-stipendiary) - Lucy Cavendish College, University of Cambridge UK
- Recipient
- 2020
- Student Travel Grant Award
- Recipient
- 11/2017
- University Grants Commission - Senior Research Fellowship
- Recipient
- 2017
- University Grants Commission - Junior Research Fellowship
- Recipient
- 2015
Publications
- Sample selection bias in machine learning for healthcare
- Chauhan Vinod Kumar, Clifton Lei, Salaün 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)
- https://doi.org/10.1145/3761822
- A brief review of hypernetworks in deep learning
- Chauhan Vinod Kumar, Zhou Jiandong, Lu Ping, Molaei Soheila, Clifton David A
- Artificial Intelligence Review Vol 57 (2024)
- https://doi.org/10.1007/s10462-024-10862-8
- HCR-Net : a deep learning based script independent handwritten character recognition network
- Chauhan Vinod Kumar, Singh Sukhdeep, Sharma Anuj
- Multimedia Tools and Applications Vol 83, pp. 78433-78467 (2024)
- https://doi.org/10.1007/s11042-024-18655-5
- Temporal dynamics unleashed : elevating variational graph attention
- Molaei Soheila, Niknam Ghazaleh, Ghosheh Ghadeer O, Chauhan Vinod Kumar, Zare Hadi, Zhu Tingting, Pan Shirui, Clifton David A
- Knowledge-Based Systems Vol 299 (2024)
- https://doi.org/10.1016/j.knosys.2024.112110
- Comparative effectiveness of sodium-glucose cotransporter-2 inhibitors for new-onset gastric cancer and gastric diseases in patients with type 2 diabetes mellitus : a population-based cohort study
- Chou Oscar Hou In, Chauhan Vinod Kumar, Chung Cheuk To Skylar, Lu Lei, Lee Teddy Tai Loy, Ng Zita Man Wai, Wang Karin Kai Wing, Lee Sharen, Liu Haipeng, Pang Ronald Ting Kai, Kaewdech Apichat, Cheung Bernard Man Yung, Tse Gary, Zhou Jiandong
- Gastric Cancer Vol 27, pp. 947-970 (2024)
- https://doi.org/10.1007/s10120-024-01512-7
- CliqueFluxNet : unveiling EHR insights with stochastic edge fluxing and maximal clique utilisation using graph neural networks
- Molaei Soheila, Bousejin Nima Ghanbari, Ghosheh Ghadeer O, Thakur Anshul, Chauhan Vinod Kumar, Zhu Tingting, Clifton David A
- Journal of Healthcare Informatics Research Vol 8, pp. 555-575 (2024)
- https://doi.org/10.1007/s41666-024-00169-2
Research Interests
My research focuses on Causal AI, situated at the intersection of causality, healthcare, and artificial intelligence. I draw on a blend of theory and practice to develop robust methodologies that address real-world healthcare challenges, with a particular emphasis on enabling data-driven personalised treatments that are transparent and impactful. Through interdisciplinary collaborations with clinicians, industry partners, and healthcare providers, my work aims to translate advances in causality and AI into tangible improvements in patient outcomes and healthcare delivery.
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 Causal AI: Integrating Causality and Machine Learning for Robust Intelligent Systems for the Frontiers in AI, Frontiers in Digital Health and Frontiers in Big Data journals, with manuscript abstract submissions due by 15 November 2025 and full manuscript submissions by 27 February 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
- Frontiers in Artificial Intelligence (Journal)
- Guest editor
- 24/7/2025
- International Conference on Learning Representations (Event)
- Peer reviewer
- 2026
- Area Chair for NeurIPS AI4Science (Event)
- Editorial board member
- 6/12/2025
- Session Chair: Tuning for Patient Specific Care at the 47th EMBC 2025 (Event)
- Peer reviewer
- 14/7/2025
- Annual Conference on Neural Information Processing Systems (Event)
- Peer reviewer
- 2025
- PLOS Digital Health (Journal)
- Editor
- 2025
Contact
Dr
Vinod Kumar Chauhan
Kumar
Strathclyde Chancellor's Fellow
Computer and Information Sciences
Email: vinod.kumar@strath.ac.uk
Tel: Unlisted