Anshul Thakur
Departmental Lecturer
Develops machine learning for clinical data, building on work in audio pattern analysis and weakly supervised event detection.
Anshul Thakur's lab at Oxford works on medical imaging & healthcare AI and recognition, detection & segmentation. 23 papers since 2023, 8 at top venues, mostly AISTATS and npj Digit. Medicine. Applications close .
At a glance
- papers, 2023–2026
- 6/ year
- at T1 venues
- 35%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 4 papers2026 · T1 1 · collecting
- 6 papers2025 · T1 4
- 10 papers2024 · T1 2
- 3 papers2023 · T1 1
T1 venuesOtherVenues: AISTATS, npj Digit. Medicine, AAAI, CVPR, EMNLP
Research focuspaper titles that use each topic's words
- Medical imaging & healthcare AI7 papers
- Recognition, detection & segmentation0 papers
- event detection0 papers
- clinical data0 papers
- weakly0 papers
Paper list
From DBLP.
20264 papers
- SAGTBribery's Influence on Ranked Aggregation (opens in a new tab)
- Trans. Mach. Learn. Res.Geometric Uncertainty for Detecting and Correcting Hallucinations in LLMs (opens in a new tab)
- IEEE J. Biomed. Health InformaticsLearning Across the Divide: Personalised Federated Learning for Robust Clinical Modelling Under Data-View Heterogeneity (opens in a new tab)
- AAAI (T1)Neuro-Symbolic Federated Learning over Heterogeneous Data-Views: A Structured Approach to Distributive EHR Modelling (opens in a new tab)
20256 papers
- npj Digit. MedicineA multimodal multidomain multilingual medical foundation model for zero shot clinical diagnosis (opens in a new tab)
- TPAMI (T1)Efficient Task Grouping Through Sample-Wise Optimisation Landscape Analysis (opens in a new tab)
- CVPR (T1)F^3OCUS - Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics (opens in a new tab)
- AISTATS (T1)Information Transfer Across Clinical Tasks via Adaptive Parameter Optimisation (opens in a new tab)
- AISTATS (T1)Optimising Clinical Federated Learning through Mode Connectivity-based Model Aggregation (opens in a new tab)
- CVPR WorkshopTowards exploring continual learning for toxicologic pathology in pharmaceutical drug discovery (opens in a new tab)
202410 papers
- ML4H@NeurIPSAre Time Series Foundation Models Ready for Vital Sign Forecasting in Healthcare? (opens in a new tab)
- J. Heal. Informatics Res.CliqueFluxNet: Unveiling EHR Insights with Stochastic Edge Fluxing and Maximal Clique Utilisation Using Graph Neural Networks (opens in a new tab)
- BMC Medical Informatics Decis. Mak.Continuous patient state attention model for addressing irregularity in electronic health records (opens in a new tab)
- AISTATS (T1)Federated Learning For Heterogeneous Electronic Health Records Utilising Augmented Temporal Graph Attention Networks (opens in a new tab)
- IEEE Trans. Neural Networks Learn. Syst.Incremental Trainable Parameter Selection in Deep Neural Networks (opens in a new tab)
- npj Digit. MedicineKnowledge abstraction and filtering based federated learning over heterogeneous data views in healthcare (opens in a new tab)
- EMNLP (T1)Large Language Models Are Poor Clinical Decision-Makers: A Comprehensive Benchmark (opens in a new tab)
- ISCASOn-chip Data Compression Techniques for High-Density Implantable Neural Recording (opens in a new tab)
- npj Digit. MedicinePublisher Correction: Knowledge abstraction and filtering based federated learning over heterogeneous data views in healthcare (opens in a new tab)
- ICPRSampling Rate Adaptive Speaker Verification from Raw Waveforms (opens in a new tab)
20233 papers
- AISTATS (T1)Adversarial De-confounding in Individualised Treatment Effects Estimation (opens in a new tab)
- NeurRepsPitfalls in Measuring Neural Transferability (opens in a new tab)
- IEEE J. Biomed. Health InformaticsSelf-Aware SGD: Reliable Incremental Adaptation Framework for Clinical AI Models (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to Oxford2027-28
DPhil in Computer Science
- Round
- 2027-28 entry (January round)
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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Data
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- The member list could not be found on the lab site.
- The alumni list could not be found on the lab site.
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