Victor Zhong

Victor Zhong is an Assistant Professor in the Department of Computer Science at the University of Waterloo. He holds a PhD from the University of Washington (2023), an MS from Stanford University (2016), and a BASc in Computer Engineering from the University of Toronto (2014). His research focuses on machine learning, natural language processing, reinforcement learning, and artificial intelligence, with particular emphasis on dialogue systems, text-to-SQL translation, and multimodal agents. Zhong’s work addresses challenges in automated workflow generation, reward function design, and policy improvement using language feedback.

His research interests include developing robust question answering systems (e.g., RoMQA benchmark), simplifying bioinformatics analysis through conversational interfaces, and evaluating language models in real-world enterprise contexts (e.g., Spider 2.0). He has contributed to foundational NLP tasks like dialogue state tracking, neural network-based query translation, and grounding language in dynamic environments. Recent publications explore open-ended tasks in real computer environments (OSWorld benchmark) and the limitations of parametric/non-parametric memories in language models.

Zhong’s work bridges theoretical advancements with practical applications, aiming to automate data science workflows and enhance AI agents’ real-world adaptability. Though no specific grants or awards are listed, his prolific publication record reflects sustained innovation in machine learning and NLP domains.