🎲Joe (Jiazhou) Liang
Data Scientist | Master Student @ University of Toronto
University of Toronto Data Driven Decision Making Lab
Welcome to the personal website of Joe Liang, a dedicated data scientist and student researcher currently pursuing a Master of Applied Science (MASc) degree at the University of Toronto under the guidance of Professors Scott Sanner and Ethan Fosse.
Joe’s expertise lies in the domains of data science and machine learning, where he possesses a robust understanding of statistical analysis and proficiency in various coding languages and data science packages including Pytorch, Scikit-Learn, PySpark, and SQL.
Check out Joe’s resume and previous projects. Let’s connect and explore the possibilities together!
Recent News
Purposed a novel framework for Multivariate Time Series Clustering With Transformer using the learnable representations in latent spaces of Transformer Encoder to achieve superior and efficient clustering re- sults in real-world experiments.
Applied a deep learning ResNet model with transfer learning techniques to classify spectrograms of human and AI-generated voices, achieving high test accuracy in the ASVspoof2019 competition.
Leveraging fine-tuned LLMs and the GPT-4 model to identify and highlight unfair or significant clauses within the Terms of Service agreements of major service providers.
