Hello! I am a senior researcher at Microsoft Research working on AI for health, working with Hoifung Poon. Prior to this, I was an applied scientist at Amazon AWS working on large language models with clinical applications. I obtained my PhD in Computation, Cognition and Language from Language Technology Lab (LTL) at the University of Cambridge.

Research Output (* equal contributions)

HealthAgentBench: A Unified Benchmark Suite of Realistic Agentic Healthcare Environments for Challenging Frontier AI Agents
Qianchu Liu*, Sheng Zhang*, Guanghui Qin*, Jeya Maria Jose Valanarasu, Maximilian Rokuss, Mingyu Lu, Timothy Ossowski, Juan Manuel Zambrano Chaves, Cliff Wong, Peniel Argaw, Yashna Hasija, Mu Wei, Wen-wai Yim, Qin Liu, Zilin Jing, Jason Entenmann, Naoto Usuyama, Tristan Naumann, Hoifung Poon, website , benchmark , 2026

Scaling medical imaging report generation with multimodal reinforcement learning
Qianchu Liu*, Sheng Zhang*, Guanghui Qin*, Yu Gu, Ying Jin, Sam Preston, Yanbo Xu, Sid Kiblawi, Wen-wai Yim, Tim Ossowski, Tristan Naumann, Mu Wei, Hoifung Poon, 2026
The proposed UniRG-CXR model is ranked as #1 model in ReXrank leaderboard for radiology report generation leaderboard result , 2026

OctoMed: Data Recipes for State-of-the-Art Multimodal Medical Reasoning
Timothy Ossowski*, Sheng Zhang*, Qianchu Liu, Guanghui Qin, Reuben Tan, Tristan Naumann, Junjie Hu, Hoifung Poon, model
In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2026), pp. 26251–26261.

X-Reasoner: Towards Generalizable Reasoning Across Modalities and Domains
Qianchu Liu*, Sheng Zhang*, Guanghui Qin*, Timothy Ossowski, Yu Gu, Ying Jin, Sid Kiblawi, Sam Preston, Mu Wei, Paul Vozila, Tristan Naumann, Hoifung Poon model , 2025

Med-RLVR: Emerging Medical Reasoning from a 3B Base Model via Reinforcement Learning
Sheng Zhang*, Qianchu Liu*, Guanghui Qin*, Tristan Naumann, Hoifung Poon, 2025

CriSPO: Multi-Aspect Critique-Suggestion-Guided Automatic Prompt Optimization for Text Generation
Han He*, Qianchu Liu*, Lei Xu*, Chaitanya Shivade, Yi Zhang, Sundararajan Srinivasan, Katrin Kirchhoff
In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2025) code

Exploring the Boundaries of GPT-4 in Radiology
Qianchu Liu, Stephanie L. Hyland, Shruthi Bannur, Kenza Bouzid, Daniel C. Castro, Maria Teodora Wetscherek, Robert Tinn, Harshita Sharma, Fernando Pérez-García,Anton Schwaighofer, Pranav Rajpurkar, Sameer Tajdin Khanna, Hoifung Poon, Naoto Usuyama, Anja Thieme, Aditya Nori, Matthew P. Lungren, Ozan Oktay, Javier Alvarez-Valle
In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023) Also see the blog post from Microsoft Research Health Futures, and Greg Brockman’s twitter post

Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing
Shruthi Bannur, Stephanie Hyland, Qianchu Liu, Fernando Pérez-García, Maximilian Ilse, Daniel C. Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Wetscherek, Matthew P. Lungren, Aditya Nori, Javier Alvarez-Valle, Ozan Oktay
In Proceedings of the 2023 Computer Vision and Pattern Recognition Conference (CVPR 2023)

Measuring Context-Word Biases in Lexical Semantic Datasets
Qianchu Liu, Diana McCarthy, Anna Korhonen
In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022)

AM2iCo: Evaluating Word Meaning in Context across Low-Resource Languages with Adversarial Examples
Qianchu Liu, Edoardo M. Ponti, Diana McCarthy, Ivan Vulić, Anna Korhonen
In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021)

Towards Better Context-aware Lexical Semantics: Adjusting Contextualized Representations through Static Anchors
Qianchu Liu, Diana McCarthy, Anna Korhonen
In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020)

XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
Edoardo M. Ponti, Goran Glavaš, Olga Majewska, Qianchu Liu, Ivan Vulić, Anna Korhonen
In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP 2020)

Investigating Cross-lingual Alignment Methods for Contextualized Embeddings with Token-Level Evaluation
Qianchu Liu, Diana McCarthy, Ivan Vulić, Anna Korhonen
In Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL 2019)