Sonali Parbhoo
Assistant Professor
Develops probabilistic machine learning, reinforcement learning and causal inference for reliable decision making in healthcare.
Sonali Parbhoo's lab at Imperial works on reinforcement learning, probabilistic & causal inference and efficient training & inference. 15 papers since 2023, 6 at top venues, mostly AISTATS and ICLR. Applications close .
At a glance
- papers, 2023–2026
- 4/ year
- at T1 venues
- 40%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 3 papers2026 · T1 2 · collecting
- 4 papers2025 · T1 2
- 3 papers2024 · T1 1
- 5 papers2023 · T1 1
T1 venuesOtherVenues: AISTATS, ICLR, ICML, JMLR, KDD
Research focuspaper titles that use each topic's words
- Reinforcement learning6 papers
- Probabilistic & causal inference2 papers
- Efficient training & inference0 papers
- develops probabilistic0 papers
- probabilistic machine0 papers
Paper list
From DBLP.
20263 papers
- KDD (T1)Causal Methods for LLM Development and Evaluation (opens in a new tab)
- npj Digit. MedicineOff by a beat: the effects of temporal misalignment in reinforcement learning for sepsis treatment (opens in a new tab)
- ICLR (T1)The Alignment Auditor: A Bayesian Framework for Verifying and Refining LLM Objectives (opens in a new tab)
20254 papers
- AISTATS (T1)Decision-Point Guided Safe Policy Improvement (opens in a new tab)
- AISTATS (T1)Do Regularization Methods for Shortcut Mitigation Work As Intended? (opens in a new tab)
- MLHCImproving ARDS Diagnosis Through Context-Aware Concept Bottleneck Models (opens in a new tab)
- IUI WorkshopUser Studies in Human-Feature-Integration (opens in a new tab)
20243 papers
- MLHCDecision-Focused Model-based Reinforcement Learning for Reward Transfer (opens in a new tab)
- JMLR (T1)Rethinking Discount Regularization: New Interpretations, Unintended Consequences, and Solutions for Regularization in Reinforcement Learning (opens in a new tab)
- Trans. Mach. Learn. Res.Task-Relevant Feature Selection with Prediction Focused Mixture Models (opens in a new tab)
20235 papers
- CAMLISAdaptive Experimental Design for Intrusion Data Collection (opens in a new tab)
- Trans. Mach. Learn. Res.Learning-to-defer for sequential medical decision-making under uncertainty (opens in a new tab)
- Trans. Mach. Learn. Res.Risk Sensitive Dead-end Identification in Safety-Critical Offline Reinforcement Learning (opens in a new tab)
- ICML (T1)The Unintended Consequences of Discount Regularization: Improving Regularization in Certainty Equivalence Reinforcement Learning (opens in a new tab)
- MLHCWhich Explanation Makes Sense? A Critical Evaluation of Local Explanations for Assessing Cervical Cancer Risk (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to Imperial2027 (Apr/Oct)
Computing PhD
- Round
- Round 2 (1 Dec 2026)
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- none
Confirmed on the program page.
Similar labsnearest by research summary
- USUCSD
Benjamin Smarr
- Medical imaging & healthcare AI
- GBImperial
Wenjia Bai
- Medical imaging & healthcare AI
- SGNUS
Juan Helen Zhou
- Neuroscience & brain-computer interfaces
- USUW
Eli Shlizerman
- Computational neuroscience & cognition
- CHEPFL
Alexander Mathis
- Neuroscience & brain-computer interfaces
- GBUCL
Simon Arridge
- Medical imaging & healthcare AI
Your notes
Save this lab to keep notes.
Data
Some numbers could not be verified:
- The member list could not be found on the lab site.
- The alumni list could not be found on the lab site.
- Collected
- Verified
- Papers
- DBLP
- Members
- Not collected
- Alumni
- Not collected
Tiers are venue classifications, not lab rankings.
Imperialcloses