Yuhao
Chen

I am a Research Scientist in Embodied Intelligence at SENAD, where I work on state-of-the-art embodied intelligence technologies, including Vision-Language-Action (VLA) models and world models. My broader research interests include large language models (LLMs), conversational AI, retrieval-augmented generation, summarization, and LLM-based evaluation.

I earned my Ph.D. in Computing from Queen's University under the supervision of Dr. Farhana Zulkernine, after completing my M.Sc. in Computer Science and Artificial Intelligence at Queen's University in 2021. During my Ph.D., I built cross-sector research experience through collaborations and internships with Roche, Pfizer, and IBM Thomas J. Watson Research Center, connecting academic AI research with healthcare, enterprise, and applied research environments.

Across my work, I focus on building reliable and deployable AI systems under real-world constraints, including limited training resources and constrained data settings. I am particularly interested in improving model accuracy and reliability through targeted training, evaluation, and continuous improvement informed by user feedback and performance signals.