I am a PhD candidate at the Department of Computer Science in University of Toronto. I am privileged to work under the supervision of Michael Brudno and Frank Rudzicz.
I am interested in machine learning and deep learning and their applications in speech, natural language processing and health care.
My resume can be found here.
Encoding syntactic knowledge in transformer encoder for intent detection and slot filling Jixuan Wang, Kai Wei, Martin Radfar, Weiwei Zhang, Clement Chung. AAAI, 2021.
Speaker attribution with profiles by graph-based semi-supervised learning Jixuan Wang, Xiong Xiao, Jian Wu, Ranjani Ramamurthy, Frank Rudzicz, Michael Brudno INTERSPEECH, 2020.
Speaker diarization with session-level speaker embedding refinement using graph neural networks Jixuan Wang, Xiong Xiao, Jian Wu, Ranjani Ramamurthy, Frank Rudzicz, Michael Brudno International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2020.
Training without training data: Improving the generalizability of automated medical abbreviation disambiguation Marta Skreta, Aryan Arbabi, Jixuan Wang, Michael Brudno Conference on Neural Information Processing Systems (NeurIPS) Machine Learning for Health (ML4H) Workshop, 2019.
Centroid-based deep metric learning for speaker recognition Jixuan Wang*, Kuan-Chieh Wang*, Marc Law, Frank Rudzicz, Michael Brudno. International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019.
Customizable facial gesture recognition for improved assistive technology Kuan-Chieh Wang, Jixuan Wang, Khai Truong, Richard Zemel International Conference on Learning Representations (ICLR) AI for Social Good Workshop, 2019.
PhenoPad We develop PhenoPad, an AI-based clinical tool enables the digitization of highly structured patient data and facilitates patient interaction while providing physicians with enough freedom to perform their jobs efficiently. We implemented a prototype and test it in real clinical settings.
Template adopted from here.