Meng Zhou

Welcome!

I am an Senior AI Research Scientist at AstraZeneca working on frontier methods in biomedical AI. If you are interested in what we do or our team in general, please feel free to reach out!

Previously, I was an Applied Machine Learning Scientist at TD Bank, worked on building machine learning and LLM/Agentic-AI solutions. I have also worked as a Machine Learning Engineer at a Medical AI startup company, focused on multilingual LLMs (Technical Report) and LLM-applications on medical document analysis.

Before my transition to industry, I was in academia where I obtained my Master of Science (MSc.) degree in Computer Science at the University of Toronto in March, 2024. I am very fortunate to be advised by Prof. Farzad Khalvati at the Intelligent Medical Informatics Computing Systems Lab. I was affiliated with The Hospital for Sick Children (SickKids) Research Institute, one of the top three pediatric health-care centres in the world, where I worked in the Department of Neurosciences & Mental Health. I have also spent a wonderful four months at AltaML Government AI lab, working on an Aerial Image Segmentation project for the public sector.

I am open to any collaborations on (Multimodal) Foundation Models for Medical Imaging

🔥🔥🔥 News

📖 Research

My current research interests focus on Biomedical Agents, particularly their self-evolving capabilities through skills, memory, and feedback-driven improvement for drug discovery and complex biomedical tasks. I am also interested in World Models and JEPA-style representation learning for biomedical data, especially how these ideas can be extended to 3D medical image generation. In addition, I am interested in multimodal foundation models for medical imaging, including vision-language and large vision models for biomedical applications.

My previous work includes medical LLM post-training for multilingual medical question answering, autoregressive 3D medical image generation for rare disease diagnosis, and sequential decision-making research on contextual multi-armed bandits.

More broadly, my work spans several connected areas:

• Biomedical agents and self-evolving AI systems for complex biomedical reasoning
• World models and JEPA-style representation learning for biomedical data and agentic task modeling
• Medical image analysis and generation, including image transformers, diffusion models, vision-language models, and large vision models
• LLM post-training for clinical and biomedical text
• Contextual Multi-armed Bandit Problems

I was previously funded by the Department of Computer Science and Temerty Faculty of Medicine at the University of Toronto; Mitacs Research Grant; The Hospital for Sick Children Research Institute, and the Ontario Graduate Scholarship.

🏆 Honors and Awards

• Mitacs Research Grant, Department of Computer Science & AltaML Inc., University of Toronto, 2024
• Ontario Graduate Scholarship Recipient, Department of Computer Science, University of Toronto, 2023
• Graduate Program Fellowship, Department of Computer Science, University of Toronto, 2023
• Mergelas Family Graduate Award, Temerty Faculty of Medicine, University of Toronto, 2022
• Dean’s Honor List, Queen’s University, 2019-2022
• John Ursell Tutor Award, Queen’s University, 2020

🚩 Other Milestones

• I obtained my Honours Bachelor’s degree in Computing, Specialized in Computing and Mathematics from Queen’s University. During my undergrad years, I have the privilege to work under the supervision of Prof. Parvin Mousavi at the Medical Informatics Laboratory on my undergraduate honours thesis, “Domain Transfer Through Image-to-Image Translation in Prostate Cancer Detection”; and Prof. Yanglei Song on the Contextual Multi-Armed Bandit problem. You can see more details in the Publicaton section on the top.
• I graduated from the Advanced Placement Program, Yale Secondary School, a beautiful high school in British Columbia in June 2017.
• I used to participated in high-school Mathematics (UWaterloo, BC Province), Chemistry (UWaterloo, BC Olympiad), and Physics (UBC Physics Olympics) contests across Canada.
• I come from Beijing, China, a beautiful city with rich history and culture.

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