Xiaodan Zhuمشاهده پروفایل
دانشیار
Xiaodan Zhu is an Associate Professor in the Department of Electrical and Computer Engineering at Queen's University, holding the Mitchell Professorship at the Ingenuity Labs Research Institute and serving as a Faculty Affiliate at the Vector Institute for Artificial Intelligence. He earned his Ph.D. in Computer Science from the University of Toronto (2010) and a Master's from Tsinghua University (2000). His research focuses on Natural Language Processing (NLP), Machine Learning, and AI, with notable contributions to sentiment analysis, adversarial attacks, legal decision-making, and medical text mining. Key research interests include semantic compositionality, calibration attacks on models, and robust reasoning in financial text. He has led projects funded by NSERC (Discovery Accelerator Supplement, Discovery Grants), JP Morgan, and the New Frontiers in Research Fund. Notable awards include the Adam Kilgarriff *SEM Best Paper Award (2015) and the Best Long Paper Award at the NAACL-2024 TrustNLP Workshop. Zhu supervises a dynamic team of graduate and undergraduate students, contributing to over 150 publications. His work spans adversarial machine learning, legal judgment prediction, and healthcare applications, with collaborations extending to industry partners like IBM, Amazon, and Samsung. He actively contributes to the academic community through editorial roles (e.g., Co-Editor-in-Chief of ACL Rolling Review) and organizing major conferences (e.g., SEMEVAL, EMNLP). Current research includes exploring robust reasoning models for financial text, legal AI applications, and advancing ensemble methods for NLP tasks. His lab’s innovations in calibration attacks and spatial reasoning with large language models reflect cutting-edge advancements in AI safety and capability.
