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Shenyang Huang

Preferred name: Andy
Master of Science, School of Computer Science, McGill University
Graduate Student, Mila - Quebec Artificial Intelligence Institute
E-mail: shenyang.huang@mail.mcgill.ca
Github: https://github.com/shenyangHuang
CV: Shenyang Huang
Linkedin: https://www.linkedin.com/in/shenyang-huang

Bio

I am a master student at Mila and McGill University , supervised by Professor Reihaneh Rabbany and Professor Guillaume Rabusseau . Previously I obtained an Honours in Computer Science from McGill University in 2019. My current research focus on anomaly detection in dynamic graph using spectral techniques. I have also worked on integrating autoML techniques into continual learning settings.


Publication

2020

  • Huang, S., Hitti, Y., Rabusseau, G. & Rabbany, R. Laplacian Change Point Detection for Dynamic Graphs. (KDD 2020) [KDD] [arXiv preprint] [github] [blog]
  • Ding, X., Huang, S., Leung, A., Rabbany, R. Incorporating Dynamic Flight Network in SEIR to Model Mobility between Populations. (under review) [arXiv preprint]
  • Leung, A., Ding, X., Huang, S., Rabbany, R. Contact Graph Epidemic Modelling of COVID-19 for Transmission and Intervention Strategies. (under review) [arXiv preprint]
  • Alletto, S., Huang, S., François-Lavet, V., Nakata, Y., & Rabusseau, G. RandomNet: Towards Fully Automatic Neural Architecture Design for Multimodal Learning. AAAI 2020 Meta-Eval Workshop [Paper]
  • 2019

  • Huang, S., François-Lavet, V., & Rabusseau, G. (2019). Neural Architecture Search for Class-incremental Learning [Paper]
  • 2018

  • Huang, S., François-Lavet, V., Rabusseau, G. & Pineau, J. Exploring Continual Learning Using Incremental Architecture Search NeuIPS Continual Learning Workshop 2018. [Paper] [github]