Back to all members...

Suhaas Bhat

Associate Member (PhD), started 2024

Suhaas Bhat is pursuing a DPhil in Theoretical Physics, supervised by Ard Louis and Yarin Gal. He is interested in the interface between physics, biology, and machine learning, and applying insights from these fields to medicine. Previously, he worked on machine learning applied to peptide drug design with Pranam Chatterjee, at the Church Lab at Harvard and the Chatterjee Lab at Duke. He has also worked on small molecule binding prediction at DE Shaw Research, and machine learning for automated DRAM verification at Normal Computing.

Suhaas holds an AB in Social Studies and Physics from Harvard, and wrote his undergraduate thesis on the ethics and viability of automating psychotherapy. He is funded by a Rhodes scholarship.


Publications while at OATMLNews items mentioning Suhaas BhatReproducibility and CodeBlog Posts

Publications while at OATML:

Building Reliable Long-Form Generation via Hallucination Rejection Sampling

Large language models (LLMs) have achieved remarkable progress in open-ended text generation, yet they remain prone to hallucinating incorrect or unsupported content, which undermines their reliability. This issue is exacerbated in long-form generation due to hallucination snowballing, a phenomenon where early errors propagate and compound into subsequent outputs. To address this challenge, we propose a novel inference-time hallucination mitigation framework, named Segment-wise HAllucination Rejection Sampling (SHARS), which uses an arbitrary hallucination detector to identify and reject hallucinated segments during generation and resample until faithful content is produced. By retaining only confident information and building subsequent generations upon it, the framework mitigates hallucination accumulation and enhances factual consistency. To instantiate this framework, we adopt semantic uncertainty as the detector and introduce several vital modifications to address its limitati... [full abstract]


Lin Li, Georgia Channing, Suhaas Bhat, Gabriel Jones, Yarin Gal
arxiv
[paper]
More publications on Google Scholar.

Blog Posts

OATML at ICML 2026

OATML group members and collaborators are proud to present 5 papers at ICML 2026. …

Full post...


Yarin Gal, Sergio Calvo Ordoñez, Sören Mindermann, Panagiotis Tigas, Lin Li, Suhaas Bhat, Gabriel Jones, 08 Jul 2026

Are you looking to do a PhD in machine learning? Did you do a PhD in another field and want to do a postdoc in machine learning? Would you like to visit the group?

How to apply


Contact

We are located at
Department of Computer Science, University of Oxford
Wolfson Building
Parks Road
OXFORD
OX1 3QD
UK
Twitter: @OATML_Oxford
Github: OATML
Email: oatml@cs.ox.ac.uk