Biography
Dr. Vinod Kumar Chauhan is a postdoctoral research fellow in the Institute of Biomedical Engineering at the University of Oxford UK. His primary research interests lie in Causal Machine Learning with applications to healthcare. Additionally, he is broadly interested in machine learning for healthcare. Prior to his current role, he served as a postdoctoral research fellow at the University of Cambridge UK, and completed his PhD at the Panjab University Chandigarh, India.
Most Recent Publications
Exploitation of material consolidation trade-offs in multi-tier complex supply networks
Exploitation of material consolidation trade-offs in multi-tier complex supply networks
1567P The effect of SGLT2i and DPP4i on new-onset gastric cancer and gastric diseases in type 2 diabetes mellitus: A population-based cohort study
1567P The effect of SGLT2i and DPP4i on new-onset gastric cancer and gastric diseases in type 2 diabetes mellitus: A population-based cohort study
Comparing the risks of new-onset gastric cancer or gastric diseases in type 2 diabetes mellitus patients exposed to SGLT2I, DPP4I or GLP1A: a population-based cohort study
Comparing the risks of new-onset gastric cancer or gastric diseases in type 2 diabetes mellitus patients exposed to SGLT2I, DPP4I or GLP1A: a population-based cohort study
Improving Diagnostics with Deep Forest Applied to Electronic Health Records
Improving Diagnostics with Deep Forest Applied to Electronic Health Records
Network science approach for identifying disruptive elements of an airline
Network science approach for identifying disruptive elements of an airline
Research Interests
Causal Inference and Machine Learning for Healthcare
Current Projects
- Postoperative prediction of Atrial Fibrillation for Heart Patients
- Address Sample Selection Bias in Machine Learning
- Individualised Treatment Effects Estimation
Research Groups
Related Academics
Most Recent Publications
Exploitation of material consolidation trade-offs in multi-tier complex supply networks
Exploitation of material consolidation trade-offs in multi-tier complex supply networks
1567P The effect of SGLT2i and DPP4i on new-onset gastric cancer and gastric diseases in type 2 diabetes mellitus: A population-based cohort study
1567P The effect of SGLT2i and DPP4i on new-onset gastric cancer and gastric diseases in type 2 diabetes mellitus: A population-based cohort study
Comparing the risks of new-onset gastric cancer or gastric diseases in type 2 diabetes mellitus patients exposed to SGLT2I, DPP4I or GLP1A: a population-based cohort study
Comparing the risks of new-onset gastric cancer or gastric diseases in type 2 diabetes mellitus patients exposed to SGLT2I, DPP4I or GLP1A: a population-based cohort study
Improving Diagnostics with Deep Forest Applied to Electronic Health Records
Improving Diagnostics with Deep Forest Applied to Electronic Health Records
Network science approach for identifying disruptive elements of an airline
Network science approach for identifying disruptive elements of an airline
Awards and Prizes
2021 Institute for Manufacturing Postdoctoral Award for Research Excellence, at University of Cambridge UK.
Travel Grant Award to present paper in Asian Conference on Machine Learning 2017
Most Recent Publications
Exploitation of material consolidation trade-offs in multi-tier complex supply networks
Exploitation of material consolidation trade-offs in multi-tier complex supply networks
1567P The effect of SGLT2i and DPP4i on new-onset gastric cancer and gastric diseases in type 2 diabetes mellitus: A population-based cohort study
1567P The effect of SGLT2i and DPP4i on new-onset gastric cancer and gastric diseases in type 2 diabetes mellitus: A population-based cohort study
Comparing the risks of new-onset gastric cancer or gastric diseases in type 2 diabetes mellitus patients exposed to SGLT2I, DPP4I or GLP1A: a population-based cohort study
Comparing the risks of new-onset gastric cancer or gastric diseases in type 2 diabetes mellitus patients exposed to SGLT2I, DPP4I or GLP1A: a population-based cohort study
Improving Diagnostics with Deep Forest Applied to Electronic Health Records
Improving Diagnostics with Deep Forest Applied to Electronic Health Records
Network science approach for identifying disruptive elements of an airline
Network science approach for identifying disruptive elements of an airline
Publications
1. Vinod Kumar Chauhan, Jiandong Zhou, Ghadeer Ghosheh, Soheila Molaei, David A. Clifton (2024) Dynamic Inter-treatment Information Sharing for Individualized Treatment Effects Estimation. The 27th International Conference on Artificial Intelligence and Statistics (AISTATS), May 2-4, 2024, Valencia, Spain, preprint (to present).
2. Vinod Kumar Chauhan, Soheila Molaei, Marzia Hoque Tania, Anshul Thakur, Tingting Zhu and David Clifton (2023) Adversarial De-confounding in Individualised Treatment Effects Estimation, The 26th International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR 206:837-849, 2023, paper, code, preprint, video.
Most Recent Publications
Exploitation of material consolidation trade-offs in multi-tier complex supply networks
Exploitation of material consolidation trade-offs in multi-tier complex supply networks
1567P The effect of SGLT2i and DPP4i on new-onset gastric cancer and gastric diseases in type 2 diabetes mellitus: A population-based cohort study
1567P The effect of SGLT2i and DPP4i on new-onset gastric cancer and gastric diseases in type 2 diabetes mellitus: A population-based cohort study
Comparing the risks of new-onset gastric cancer or gastric diseases in type 2 diabetes mellitus patients exposed to SGLT2I, DPP4I or GLP1A: a population-based cohort study
Comparing the risks of new-onset gastric cancer or gastric diseases in type 2 diabetes mellitus patients exposed to SGLT2I, DPP4I or GLP1A: a population-based cohort study
Improving Diagnostics with Deep Forest Applied to Electronic Health Records
Improving Diagnostics with Deep Forest Applied to Electronic Health Records
Network science approach for identifying disruptive elements of an airline
Network science approach for identifying disruptive elements of an airline
Talks
1. Keynote Speaker, “Prediction of Post-operative Atrial Fibrillation in Patients undergoing Heart Surgery”, Artificial Intelligence (AI) and Digital Transformation in Various Academic Disciplines & Teacher Training, 15th Feb 2024, Government College RaipurRani, India.
2. Keynote Speaker, “HyperNetworks: A new Approach for Training and Designing Neural Networks”, International Conference on Artificial Intelligence and Machine Learning, Department of Computer Science and Applications, Panjab University, Chandigarh, November 28-29, 2023.
3. Invited talk, “Dynamic Inter-Treatment Information Sharing for Individualised Treatment Effects Estimation”, IISER Pune, India, October 04, 2023, link
Most Recent Publications
Exploitation of material consolidation trade-offs in multi-tier complex supply networks
Exploitation of material consolidation trade-offs in multi-tier complex supply networks
1567P The effect of SGLT2i and DPP4i on new-onset gastric cancer and gastric diseases in type 2 diabetes mellitus: A population-based cohort study
1567P The effect of SGLT2i and DPP4i on new-onset gastric cancer and gastric diseases in type 2 diabetes mellitus: A population-based cohort study
Comparing the risks of new-onset gastric cancer or gastric diseases in type 2 diabetes mellitus patients exposed to SGLT2I, DPP4I or GLP1A: a population-based cohort study
Comparing the risks of new-onset gastric cancer or gastric diseases in type 2 diabetes mellitus patients exposed to SGLT2I, DPP4I or GLP1A: a population-based cohort study
Improving Diagnostics with Deep Forest Applied to Electronic Health Records
Improving Diagnostics with Deep Forest Applied to Electronic Health Records
Network science approach for identifying disruptive elements of an airline
Network science approach for identifying disruptive elements of an airline
Other roles
Member of departmental EDI committee
Most Recent Publications
Exploitation of material consolidation trade-offs in multi-tier complex supply networks
Exploitation of material consolidation trade-offs in multi-tier complex supply networks
1567P The effect of SGLT2i and DPP4i on new-onset gastric cancer and gastric diseases in type 2 diabetes mellitus: A population-based cohort study
1567P The effect of SGLT2i and DPP4i on new-onset gastric cancer and gastric diseases in type 2 diabetes mellitus: A population-based cohort study
Comparing the risks of new-onset gastric cancer or gastric diseases in type 2 diabetes mellitus patients exposed to SGLT2I, DPP4I or GLP1A: a population-based cohort study
Comparing the risks of new-onset gastric cancer or gastric diseases in type 2 diabetes mellitus patients exposed to SGLT2I, DPP4I or GLP1A: a population-based cohort study
Improving Diagnostics with Deep Forest Applied to Electronic Health Records
Improving Diagnostics with Deep Forest Applied to Electronic Health Records
Network science approach for identifying disruptive elements of an airline
Network science approach for identifying disruptive elements of an airline
