Yaoyu Zhang ⚡️
Profile
Allan (Yaoyu) Zhang is a Ph.D. student at the University of Toronto, researching deep learning, time series classification, and feature learning. He has hands-on experience applying AI to real-world challenges including emergency response, healthcare, and smart manufacturing.
Education

Ph.D. in Mechanical and Industrial Engineering

Jan 2023 – Present, University of Toronto, Canada

Research: Deep learning, time series classification, feature learning
Supervisor: Prof. Chi-Guhn Lee

M.Sc. in Mathematics and Statistics (Stochastic Processes)

Mar 2021 – Dec 2022, University of Melbourne, Australia

With Distinction

B.Math in Actuarial Science and Statistics

Sep 2017 – Oct 2020, University of Waterloo, Canada

With Distinction

Research Experience

Research Collaborator at NRC Canada

Jan 2023 – Aug 2024, Ottawa, Canada

- Developed TSC algorithms for fire safety data using hybrid, distance-based, and deep learning models.
- Applied contrastive learning and adversarial-based latent construction.
- Created novel algorithms to classify burning materials in fire scenes.

Research Collaborator at LG Electronics

Jun 2023 – Apr 2024, Toronto, Canada

- Built SOTA TSC models for fabric type recognition in washing machines.
- Developed domain generalization techniques to address distributional shift.

Research Collaborator at Baker Heart & Diabetes Institute

Mar 2021 – Oct 2022, Melbourne, Australia

- Applied statistical models and transfer learning to chronic disease prediction.
- Developed logistic regression and clustering for personalized risk assessment.

Internships

Data Analyst at ByteDance

Oct 2021 – Dec 2021, Shanghai, China

- Analyzed sales growth data for Dali smart learning lamps using SQL, Excel, and Aeolus platform.
- Applied A/B testing, KNN, and SVM for marketing and user segmentation.

Publications
  • Tian, S., Zhang, Y., Feng, Y., et al. (2023). Time series classification, augmentation and AI-enabled software for emergency response in freight transportation fires. Expert Systems with Applications, 233, 120914. [DOI]
  • Liu, D., Shangguan, X., Wei, K., Wu, C., Zhao, X., Sun, Q., Zhang, Y., & Bai, R. (2023). Research on the standardization strategy of granular computing. International Journal of Cognitive Computing in Engineering, 4, 340–348. [DOI]
Grants & Awards
  • Mathematics and Statistics Masters Scholarship – University of Melbourne (2021, 2022)
  • Science Graduate Scholarship – University of Melbourne (2021)
  • Melbourne Research Scholarships – University of Melbourne (2021)
  • President’s Scholarship – University of Waterloo (2018)
Skills
  • Python
  • R
  • SLURM
  • PyTorch
  • TensorFlow
  • SQL
  • Machine Learning
  • Deep Learning
  • Time Series Analysis
  • Feature Learning
  • LaTeX
  • Git
Professional Associations
  • Society of Actuaries: Passed Exams P, FM, IFM, SRM, STAM, VEE (Math Stats, Economics, Finance)